Several Guaranteed Descent Conjugate Gradient Methods for Unconstrained Optimization
Directory of Open Access Journals (Sweden)
San-Yang Liu
2014-01-01
Full Text Available This paper investigates a general form of guaranteed descent conjugate gradient methods which satisfies the descent condition gkTdk≤-1-1/4θkgk2 θk>1/4 and which is strongly convergent whenever the weak Wolfe line search is fulfilled. Moreover, we present several specific guaranteed descent conjugate gradient methods and give their numerical results for large-scale unconstrained optimization.
Directory of Open Access Journals (Sweden)
San-Yang Liu
2014-01-01
Full Text Available Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combined with the hyperplane projection method of Solodov and Svaiter, they are extended to solve convex constrained nonlinear monotone equations. Their global convergence is proven under some mild conditions. Numerical results illustrate that these methods are efficient and can be applied to solve large-scale nonsmooth equations.
Ionospheric forecasting model using fuzzy logic-based gradient descent method
Directory of Open Access Journals (Sweden)
D. Venkata Ratnam
2017-09-01
Full Text Available Space weather phenomena cause satellite to ground or satellite to aircraft transmission outages over the VHF to L-band frequency range, particularly in the low latitude region. Global Positioning System (GPS is primarily susceptible to this form of space weather. Faulty GPS signals are attributed to ionospheric error, which is a function of Total Electron Content (TEC. Importantly, precise forecasts of space weather conditions and appropriate hazard observant cautions required for ionospheric space weather observations are limited. In this paper, a fuzzy logic-based gradient descent method has been proposed to forecast the ionospheric TEC values. In this technique, membership functions have been tuned based on the gradient descent estimated values. The proposed algorithm has been tested with the TEC data of two geomagnetic storms in the low latitude station of KL University, Guntur, India (16.44°N, 80.62°E. It has been found that the gradient descent method performs well and the predicted TEC values are close to the original TEC measurements.
A conjugate gradient method with descent properties under strong Wolfe line search
Zull, N.; ‘Aini, N.; Shoid, S.; Ghani, N. H. A.; Mohamed, N. S.; Rivaie, M.; Mamat, M.
2017-09-01
The conjugate gradient (CG) method is one of the optimization methods that are often used in practical applications. The continuous and numerous studies conducted on the CG method have led to vast improvements in its convergence properties and efficiency. In this paper, a new CG method possessing the sufficient descent and global convergence properties is proposed. The efficiency of the new CG algorithm relative to the existing CG methods is evaluated by testing them all on a set of test functions using MATLAB. The tests are measured in terms of iteration numbers and CPU time under strong Wolfe line search. Overall, this new method performs efficiently and comparable to the other famous methods.
Loizou, Nicolas
2017-12-27
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.
Loizou, Nicolas; Richtarik, Peter
2017-01-01
In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these methods are studied. We choose to perform our analysis in a setting in which all of the above methods are equivalent. We prove global nonassymptotic linear convergence rates for all methods and various measures of success, including primal function values, primal iterates (in L2 sense), and dual function values. We also show that the primal iterates converge at an accelerated linear rate in the L1 sense. This is the first time a linear rate is shown for the stochastic heavy ball method (i.e., stochastic gradient descent method with momentum). Under somewhat weaker conditions, we establish a sublinear convergence rate for Cesaro averages of primal iterates. Moreover, we propose a novel concept, which we call stochastic momentum, aimed at decreasing the cost of performing the momentum step. We prove linear convergence of several stochastic methods with stochastic momentum, and show that in some sparse data regimes and for sufficiently small momentum parameters, these methods enjoy better overall complexity than methods with deterministic momentum. Finally, we perform extensive numerical testing on artificial and real datasets, including data coming from average consensus problems.
MODIFIED ARMIJO RULE ON GRADIENT DESCENT AND CONJUGATE GRADIENT
Directory of Open Access Journals (Sweden)
ZURAIDAH FITRIAH
2017-10-01
Full Text Available Armijo rule is an inexact line search method to determine step size in some descent method to solve unconstrained local optimization. Modified Armijo was introduced to increase the numerical performance of several descent algorithms that applying this method. The basic difference of Armijo and its modified are in existence of a parameter and estimating the parameter that is updated in every iteration. This article is comparing numerical solution and time of computation of gradient descent and conjugate gradient hybrid Gilbert-Nocedal (CGHGN that applying modified Armijo rule. From program implementation in Matlab 6, it's known that gradient descent was applying modified Armijo more effectively than CGHGN from one side: iteration needed to reach some norm of the gradient (input by the user. The amount of iteration was representing how long the step size of each algorithm in each iteration. In another side, time of computation has the same conclusion.
An online supervised learning method based on gradient descent for spiking neurons.
Xu, Yan; Yang, Jing; Zhong, Shuiming
2017-09-01
The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.
Tripathi, Ashish; McNulty, Ian; Shpyrko, Oleg G
2014-01-27
Ptychographic coherent x-ray diffractive imaging is a form of scanning microscopy that does not require optics to image a sample. A series of scanned coherent diffraction patterns recorded from multiple overlapping illuminated regions on the sample are inverted numerically to retrieve its image. The technique recovers the phase lost by detecting the diffraction patterns by using experimentally known constraints, in this case the measured diffraction intensities and the assumed scan positions on the sample. The spatial resolution of the recovered image of the sample is limited by the angular extent over which the diffraction patterns are recorded and how well these constraints are known. Here, we explore how reconstruction quality degrades with uncertainties in the scan positions. We show experimentally that large errors in the assumed scan positions on the sample can be numerically determined and corrected using conjugate gradient descent methods. We also explore in simulations the limits, based on the signal to noise of the diffraction patterns and amount of overlap between adjacent scan positions, of just how large these errors can be and still be rendered tractable by this method.
Directory of Open Access Journals (Sweden)
Chein-Shan Liu
2012-04-01
Full Text Available It is well known that the numerical algorithms of the steepest descent method (SDM, and the conjugate gradient method (CGM are effective for solving well-posed linear systems. However, they are vulnerable to noisy disturbance for solving ill-posed linear systems. We propose the modifications of SDM and CGM, namely the modified steepest descent method (MSDM, and the modified conjugate gradient method (MCGM. The starting point is an invariant manifold defined in terms of a minimum functional and a fictitious time-like variable; however, in the final stage we can derive a purely iterative algorithm including an acceleration parameter. Through the Hopf bifurcation, this parameter indeed plays a major role to switch the situation of slow convergence to a new situation that the functional is stepwisely decreased very fast. Several numerical examples are examined and compared with exact solutions, revealing that the new algorithms of MSDM and MCGM have good computational efficiency and accuracy, even for the highly ill-conditioned linear equations system with a large noise being imposed on the given data.
Bhaya, Amit; Kaszkurewicz, Eugenius
2004-01-01
It is pointed out that the so called momentum method, much used in the neural network literature as an acceleration of the backpropagation method, is a stationary version of the conjugate gradient method. Connections with the continuous optimization method known as heavy ball with friction are also made. In both cases, adaptive (dynamic) choices of the so called learning rate and momentum parameters are obtained using a control Liapunov function analysis of the system.
Directory of Open Access Journals (Sweden)
Bakhtawar Baluch
2017-01-01
Full Text Available A new modified three-term conjugate gradient (CG method is shown for solving the large scale optimization problems. The idea relates to the famous Polak-Ribière-Polyak (PRP formula. As the numerator of PRP plays a vital role in numerical result and not having the jamming issue, PRP method is not globally convergent. So, for the new three-term CG method, the idea is to use the PRP numerator and combine it with any good CG formula’s denominator that performs well. The new modification of three-term CG method possesses the sufficient descent condition independent of any line search. The novelty is that by using the Wolfe Powell line search the new modification possesses global convergence properties with convex and nonconvex functions. Numerical computation with the Wolfe Powell line search by using the standard test function of optimization shows the efficiency and robustness of the new modification.
On the Strong Convergence of a Sufficient Descent Polak-Ribière-Polyak Conjugate Gradient Method
Directory of Open Access Journals (Sweden)
Min Sun
2014-01-01
Full Text Available Recently, Zhang et al. proposed a sufficient descent Polak-Ribière-Polyak (SDPRP conjugate gradient method for large-scale unconstrained optimization problems and proved its global convergence in the sense that lim infk→∞∥∇f(xk∥=0 when an Armijo-type line search is used. In this paper, motivated by the line searches proposed by Shi et al. and Zhang et al., we propose two new Armijo-type line searches and show that the SDPRP method has strong convergence in the sense that limk→∞∥∇f(xk∥=0 under the two new line searches. Numerical results are reported to show the efficiency of the SDPRP with the new Armijo-type line searches in practical computation.
On Nonconvex Decentralized Gradient Descent
2016-08-01
and J. Bolte, On the convergence of the proximal algorithm for nonsmooth functions involving analytic features, Math . Program., 116: 5-16, 2009. [2] H...splitting, and regularized Gauss-Seidel methods, Math . Pro- gram., Ser. A, 137: 91-129, 2013. [3] P. Bianchi and J. Jakubowicz, Convergence of a multi-agent...subgradient method under random communication topologies , IEEE J. Sel. Top. Signal Process., 5:754-771, 2011. [11] A. Nedic and A. Ozdaglar, Distributed
Preconditioned stochastic gradient descent optimisation for monomodal image registration
Klein, S.; Staring, M.; Andersson, J.P.; Pluim, J.P.W.; Fichtinger, G.; Martel, A.; Peters, T.
2011-01-01
We present a stochastic optimisation method for intensity-based monomodal image registration. The method is based on a Robbins-Monro stochastic gradient descent method with adaptive step size estimation, and adds a preconditioning matrix. The derivation of the pre-conditioner is based on the
Gradient descent learning algorithm overview: a general dynamical systems perspective.
Baldi, P
1995-01-01
Gives a unified treatment of gradient descent learning algorithms for neural networks using a general framework of dynamical systems. This general approach organizes and simplifies all the known algorithms and results which have been originally derived for different problems (fixed point/trajectory learning), for different models (discrete/continuous), for different architectures (forward/recurrent), and using different techniques (backpropagation, variational calculus, adjoint methods, etc.). The general approach can also be applied to derive new algorithms. The author then briefly examines some of the complexity issues and limitations intrinsic to gradient descent learning. Throughout the paper, the author focuses on the problem of trajectory learning.
Applying Gradient Descent in Convolutional Neural Networks
Cui, Nan
2018-04-01
With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.
Fastest Rates for Stochastic Mirror Descent Methods
Hanzely, Filip
2018-03-20
Relative smoothness - a notion introduced by Birnbaum et al. (2011) and rediscovered by Bauschke et al. (2016) and Lu et al. (2016) - generalizes the standard notion of smoothness typically used in the analysis of gradient type methods. In this work we are taking ideas from well studied field of stochastic convex optimization and using them in order to obtain faster algorithms for minimizing relatively smooth functions. We propose and analyze two new algorithms: Relative Randomized Coordinate Descent (relRCD) and Relative Stochastic Gradient Descent (relSGD), both generalizing famous algorithms in the standard smooth setting. The methods we propose can be in fact seen as a particular instances of stochastic mirror descent algorithms. One of them, relRCD corresponds to the first stochastic variant of mirror descent algorithm with linear convergence rate.
Fastest Rates for Stochastic Mirror Descent Methods
Hanzely, Filip; Richtarik, Peter
2018-01-01
Relative smoothness - a notion introduced by Birnbaum et al. (2011) and rediscovered by Bauschke et al. (2016) and Lu et al. (2016) - generalizes the standard notion of smoothness typically used in the analysis of gradient type methods. In this work we are taking ideas from well studied field of stochastic convex optimization and using them in order to obtain faster algorithms for minimizing relatively smooth functions. We propose and analyze two new algorithms: Relative Randomized Coordinate Descent (relRCD) and Relative Stochastic Gradient Descent (relSGD), both generalizing famous algorithms in the standard smooth setting. The methods we propose can be in fact seen as a particular instances of stochastic mirror descent algorithms. One of them, relRCD corresponds to the first stochastic variant of mirror descent algorithm with linear convergence rate.
Efficient Sensor Placement Optimization Using Gradient Descent and Probabilistic Coverage
Directory of Open Access Journals (Sweden)
Vahab Akbarzadeh
2014-08-01
Full Text Available We are proposing an adaptation of the gradient descent method to optimize the position and orientation of sensors for the sensor placement problem. The novelty of the proposed method lies in the combination of gradient descent optimization with a realistic model, which considers both the topography of the environment and a set of sensors with directional probabilistic sensing. The performance of this approach is compared with two other black box optimization methods over area coverage and processing time. Results show that our proposed method produces competitive results on smaller maps and superior results on larger maps, while requiring much less computation than the other optimization methods to which it has been compared.
Error analysis of stochastic gradient descent ranking.
Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan
2013-06-01
Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.
Reference-shaping adaptive control by using gradient descent optimizers.
Directory of Open Access Journals (Sweden)
Baris Baykant Alagoz
Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.
Momentum-weighted conjugate gradient descent algorithm for gradient coil optimization.
Lu, Hanbing; Jesmanowicz, Andrzej; Li, Shi-Jiang; Hyde, James S
2004-01-01
MRI gradient coil design is a type of nonlinear constrained optimization. A practical problem in transverse gradient coil design using the conjugate gradient descent (CGD) method is that wire elements move at different rates along orthogonal directions (r, phi, z), and tend to cross, breaking the constraints. A momentum-weighted conjugate gradient descent (MW-CGD) method is presented to overcome this problem. This method takes advantage of the efficiency of the CGD method combined with momentum weighting, which is also an intrinsic property of the Levenberg-Marquardt algorithm, to adjust step sizes along the three orthogonal directions. A water-cooled, 12.8 cm inner diameter, three axis torque-balanced gradient coil for rat imaging was developed based on this method, with an efficiency of 2.13, 2.08, and 4.12 mT.m(-1).A(-1) along X, Y, and Z, respectively. Experimental data demonstrate that this method can improve efficiency by 40% and field uniformity by 27%. This method has also been applied to the design of a gradient coil for the human brain, employing remote current return paths. The benefits of this design include improved gradient field uniformity and efficiency, with a shorter length than gradient coil designs using coaxial return paths. Copyright 2003 Wiley-Liss, Inc.
Determination of accelerated factors in gradient descent iterations based on Taylor's series
Directory of Open Access Journals (Sweden)
Petrović Milena
2017-01-01
Full Text Available In this paper the efficiency of accelerated gradient descent methods regarding the way of determination of accelerated factor is considered. Due to the previous researches we assert that the use of Taylor's series of posed gradient descent iteration in calculation of accelerated parameter gives better final results than some other choices. We give a comparative analysis of efficiency of several methods with different approaches in obtaining accelerated parameter. According to the achieved results of numerical experiments we make a conclusion about the one of the most optimal way in defining accelerated parameter in accelerated gradient descent schemes.
Gradient descent for robust kernel-based regression
Guo, Zheng-Chu; Hu, Ting; Shi, Lei
2018-06-01
In this paper, we study the gradient descent algorithm generated by a robust loss function over a reproducing kernel Hilbert space (RKHS). The loss function is defined by a windowing function G and a scale parameter σ, which can include a wide range of commonly used robust losses for regression. There is still a gap between theoretical analysis and optimization process of empirical risk minimization based on loss: the estimator needs to be global optimal in the theoretical analysis while the optimization method can not ensure the global optimality of its solutions. In this paper, we aim to fill this gap by developing a novel theoretical analysis on the performance of estimators generated by the gradient descent algorithm. We demonstrate that with an appropriately chosen scale parameter σ, the gradient update with early stopping rules can approximate the regression function. Our elegant error analysis can lead to convergence in the standard L 2 norm and the strong RKHS norm, both of which are optimal in the mini-max sense. We show that the scale parameter σ plays an important role in providing robustness as well as fast convergence. The numerical experiments implemented on synthetic examples and real data set also support our theoretical results.
Practical gradient-descent for memristive crossbars
Nair, Manu V; Dudek, Piotr
2015-01-01
This paper discusses implementations of gradientdescent based learning algorithms on memristive crossbar arrays. The Unregulated Step Descent (USD) is described as a practical algorithm for feed-forward on-line training of large crossbar arrays. It allows fast feed-forward fully parallel on-line hardware based learning, without requiring accurate models of the memristor behaviour and precise control of the programming pulses. The effect of device parameters, training parameters, and device va...
Nonlinear System Identification Using Neural Networks Trained with Natural Gradient Descent
Directory of Open Access Journals (Sweden)
Ibnkahla Mohamed
2003-01-01
Full Text Available We use natural gradient (NG learning neural networks (NNs for modeling and identifying nonlinear systems with memory. The nonlinear system is comprised of a discrete-time linear filter followed by a zero-memory nonlinearity . The NN model is composed of a linear adaptive filter followed by a two-layer memoryless nonlinear NN. A Kalman filter-based technique and a search-and-converge method have been employed for the NG algorithm. It is shown that the NG descent learning significantly outperforms the ordinary gradient descent and the Levenberg-Marquardt (LM procedure in terms of convergence speed and mean squared error (MSE performance.
Accelerating deep neural network training with inconsistent stochastic gradient descent.
Wang, Linnan; Yang, Yi; Min, Renqiang; Chakradhar, Srimat
2017-09-01
Stochastic Gradient Descent (SGD) updates Convolutional Neural Network (CNN) with a noisy gradient computed from a random batch, and each batch evenly updates the network once in an epoch. This model applies the same training effort to each batch, but it overlooks the fact that the gradient variance, induced by Sampling Bias and Intrinsic Image Difference, renders different training dynamics on batches. In this paper, we develop a new training strategy for SGD, referred to as Inconsistent Stochastic Gradient Descent (ISGD) to address this problem. The core concept of ISGD is the inconsistent training, which dynamically adjusts the training effort w.r.t the loss. ISGD models the training as a stochastic process that gradually reduces down the mean of batch's loss, and it utilizes a dynamic upper control limit to identify a large loss batch on the fly. ISGD stays on the identified batch to accelerate the training with additional gradient updates, and it also has a constraint to penalize drastic parameter changes. ISGD is straightforward, computationally efficient and without requiring auxiliary memories. A series of empirical evaluations on real world datasets and networks demonstrate the promising performance of inconsistent training. Copyright © 2017 Elsevier Ltd. All rights reserved.
Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.
Guan, Naiyang; Tao, Dacheng; Luo, Zhigang; Yuan, Bo
2011-07-01
Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R(1600), FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.
Gradient descent learning in and out of equilibrium
International Nuclear Information System (INIS)
Caticha, Nestor; Araujo de Oliveira, Evaldo
2001-01-01
Relations between the off thermal equilibrium dynamical process of on-line learning and the thermally equilibrated off-line learning are studied for potential gradient descent learning. The approach of Opper to study on-line Bayesian algorithms is used for potential based or maximum likelihood learning. We look at the on-line learning algorithm that best approximates the off-line algorithm in the sense of least Kullback-Leibler information loss. The closest on-line algorithm works by updating the weights along the gradient of an effective potential, which is different from the parent off-line potential. A few examples are analyzed and the origin of the potential annealing is discussed
Robust Fully Distributed Minibatch Gradient Descent with Privacy Preservation
Directory of Open Access Journals (Sweden)
Gábor Danner
2018-01-01
Full Text Available Privacy and security are among the highest priorities in data mining approaches over data collected from mobile devices. Fully distributed machine learning is a promising direction in this context. However, it is a hard problem to design protocols that are efficient yet provide sufficient levels of privacy and security. In fully distributed environments, secure multiparty computation (MPC is often applied to solve these problems. However, in our dynamic and unreliable application domain, known MPC algorithms are not scalable or not robust enough. We propose a light-weight protocol to quickly and securely compute the sum query over a subset of participants assuming a semihonest adversary. During the computation the participants learn no individual values. We apply this protocol to efficiently calculate the sum of gradients as part of a fully distributed minibatch stochastic gradient descent algorithm. The protocol achieves scalability and robustness by exploiting the fact that in this application domain a “quick and dirty” sum computation is acceptable. We utilize the Paillier homomorphic cryptosystem as part of our solution combined with extreme lossy gradient compression to make the cost of the cryptographic algorithms affordable. We demonstrate both theoretically and experimentally, based on churn statistics from a real smartphone trace, that the protocol is indeed practically viable.
Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals
Cho, Myung
2016-06-24
We propose fast algorithms that speed up or improve the performance of recovering spectrally sparse signals from un-derdetermined measurements. Our algorithms are based on a non-convex approach of using alternating projected gradient descent for structured matrix recovery. We apply this approach to two formulations of structured matrix recovery: Hankel and Toeplitz mosaic structured matrix, and Hankel structured matrix. Our methods provide better recovery performance, and faster signal recovery than existing algorithms, including atomic norm minimization.
Fast alternating projected gradient descent algorithms for recovering spectrally sparse signals
Cho, Myung; Cai, Jian-Feng; Liu, Suhui; Eldar, Yonina C.; Xu, Weiyu
2016-01-01
We propose fast algorithms that speed up or improve the performance of recovering spectrally sparse signals from un-derdetermined measurements. Our algorithms are based on a non-convex approach of using alternating projected gradient descent for structured matrix recovery. We apply this approach to two formulations of structured matrix recovery: Hankel and Toeplitz mosaic structured matrix, and Hankel structured matrix. Our methods provide better recovery performance, and faster signal recovery than existing algorithms, including atomic norm minimization.
Minimizing convex functions by continuous descent methods
Directory of Open Access Journals (Sweden)
Sergiu Aizicovici
2010-01-01
Full Text Available We study continuous descent methods for minimizing convex functions, defined on general Banach spaces, which are associated with an appropriate complete metric space of vector fields. We show that there exists an everywhere dense open set in this space of vector fields such that each of its elements generates strongly convergent trajectories.
Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient Descent
De Sa, Christopher; Feldman, Matthew; Ré, Christopher; Olukotun, Kunle
2018-01-01
Stochastic gradient descent (SGD) is one of the most popular numerical algorithms used in machine learning and other domains. Since this is likely to continue for the foreseeable future, it is important to study techniques that can make it run fast on parallel hardware. In this paper, we provide the first analysis of a technique called Buckwild! that uses both asynchronous execution and low-precision computation. We introduce the DMGC model, the first conceptualization of the parameter space that exists when implementing low-precision SGD, and show that it provides a way to both classify these algorithms and model their performance. We leverage this insight to propose and analyze techniques to improve the speed of low-precision SGD. First, we propose software optimizations that can increase throughput on existing CPUs by up to 11×. Second, we propose architectural changes, including a new cache technique we call an obstinate cache, that increase throughput beyond the limits of current-generation hardware. We also implement and analyze low-precision SGD on the FPGA, which is a promising alternative to the CPU for future SGD systems. PMID:29391770
Understanding the Convolutional Neural Networks with Gradient Descent and Backpropagation
Zhou, XueFei
2018-04-01
With the development of computer technology, the applications of machine learning are more and more extensive. And machine learning is providing endless opportunities to develop new applications. One of those applications is image recognition by using Convolutional Neural Networks (CNNs). CNN is one of the most common algorithms in image recognition. It is significant to understand its theory and structure for every scholar who is interested in this field. CNN is mainly used in computer identification, especially in voice, text recognition and other aspects of the application. It utilizes hierarchical structure with different layers to accelerate computing speed. In addition, the greatest features of CNNs are the weight sharing and dimension reduction. And all of these consolidate the high effectiveness and efficiency of CNNs with idea computing speed and error rate. With the help of other learning altruisms, CNNs could be used in several scenarios for machine learning, especially for deep learning. Based on the general introduction to the background and the core solution CNN, this paper is going to focus on summarizing how Gradient Descent and Backpropagation work, and how they contribute to the high performances of CNNs. Also, some practical applications will be discussed in the following parts. The last section exhibits the conclusion and some perspectives of future work.
Directory of Open Access Journals (Sweden)
Qiuyu Wang
2014-01-01
descent method at first finite number of steps and then by conjugate gradient method subsequently. Under some appropriate conditions, we show that the algorithm converges globally. Numerical experiments and comparisons by using some box-constrained problems from CUTEr library are reported. Numerical comparisons illustrate that the proposed method is promising and competitive with the well-known method—L-BFGS-B.
On Scalable Deep Learning and Parallelizing Gradient Descent
AUTHOR|(CDS)2129036; Möckel, Rico; Baranowski, Zbigniew; Canali, Luca
Speeding up gradient based methods has been a subject of interest over the past years with many practical applications, especially with respect to Deep Learning. Despite the fact that many optimizations have been done on a hardware level, the convergence rate of very large models remains problematic. Therefore, data parallel methods next to mini-batch parallelism have been suggested to further decrease the training time of parameterized models using gradient based methods. Nevertheless, asynchronous optimization was considered too unstable for practical purposes due to a lacking understanding of the underlying mechanisms. Recently, a theoretical contribution has been made which defines asynchronous optimization in terms of (implicit) momentum due to the presence of a queuing model of gradients based on past parameterizations. This thesis mainly builds upon this work to construct a better understanding why asynchronous optimization shows proportionally more divergent behavior when the number of parallel worker...
Fractional-order gradient descent learning of BP neural networks with Caputo derivative.
Wang, Jian; Wen, Yanqing; Gou, Yida; Ye, Zhenyun; Chen, Hua
2017-05-01
Fractional calculus has been found to be a promising area of research for information processing and modeling of some physical systems. In this paper, we propose a fractional gradient descent method for the backpropagation (BP) training of neural networks. In particular, the Caputo derivative is employed to evaluate the fractional-order gradient of the error defined as the traditional quadratic energy function. The monotonicity and weak (strong) convergence of the proposed approach are proved in detail. Two simulations have been implemented to illustrate the performance of presented fractional-order BP algorithm on three small datasets and one large dataset. The numerical simulations effectively verify the theoretical observations of this paper as well. Copyright © 2017 Elsevier Ltd. All rights reserved.
Stochastic Spectral and Conjugate Descent Methods
Kovalev, Dmitry
2018-02-11
The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions. As we increase the number of extra directions to be sampled from, the rate of the method improves, and interpolates between the linear rate of RCD and a linear rate independent of the condition number. We develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only. We motivate the above development by proving several negative results which highlight the limitations of RCD with importance sampling.
Stochastic Spectral and Conjugate Descent Methods
Kovalev, Dmitry; Gorbunov, Eduard; Gasanov, Elnur; Richtarik, Peter
2018-01-01
The state-of-the-art methods for solving optimization problems in big dimensions are variants of randomized coordinate descent (RCD). In this paper we introduce a fundamentally new type of acceleration strategy for RCD based on the augmentation of the set of coordinate directions by a few spectral or conjugate directions. As we increase the number of extra directions to be sampled from, the rate of the method improves, and interpolates between the linear rate of RCD and a linear rate independent of the condition number. We develop and analyze also inexact variants of these methods where the spectral and conjugate directions are allowed to be approximate only. We motivate the above development by proving several negative results which highlight the limitations of RCD with importance sampling.
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Vlček, Jan
1998-01-01
Roč. 8, č. 3-4 (1998), s. 201-223 ISSN 1055-6788 R&D Projects: GA ČR GA201/96/0918 Keywords : nonlinear equations * Armijo-type descent methods * Newton-like methods * truncated methods * global convergence * nonsymmetric linear systems * conjugate gradient -type methods * residual smoothing * computational experiments Subject RIV: BB - Applied Statistics, Operational Research
Block-Based Gradient Descent for Local Backlight Dimming and Flicker Reduction
DEFF Research Database (Denmark)
Burini, Nino; Mantel, Claire; Nadernejad, Ehsan
2014-01-01
Local backlight dimming technology is a two-fold improvement for LED backlit LCD screens that allows to reduce power consumption and increase visual quality. This paper presents a fast version of an iterative backlight dimming algorithm based on gradient descent search. The speed is increased...
Steepest descent method implementation on unconstrained optimization problem using C++ program
Napitupulu, H.; Sukono; Mohd, I. Bin; Hidayat, Y.; Supian, S.
2018-03-01
Steepest Descent is known as the simplest gradient method. Recently, many researches are done to obtain the appropriate step size in order to reduce the objective function value progressively. In this paper, the properties of steepest descent method from literatures are reviewed together with advantages and disadvantages of each step size procedure. The development of steepest descent method due to its step size procedure is discussed. In order to test the performance of each step size, we run a steepest descent procedure in C++ program. We implemented it to unconstrained optimization test problem with two variables, then we compare the numerical results of each step size procedure. Based on the numerical experiment, we conclude the general computational features and weaknesses of each procedure in each case of problem.
Conjugate descent formulation of backpropagation error in ...
African Journals Online (AJOL)
nique of backpropagation was popularized in a paper by Rumelhart, et al. ... the training of a multilayer neural network using a gradient descent approach applied to a .... superior convergence of the conjugate descent method over a standard ...
Dynamic gradient descent learning algorithms for enhanced empirical modeling of power plants
International Nuclear Information System (INIS)
Parlos, A.G.; Atiya, Amir; Chong, K.T.
1991-01-01
A newly developed dynamic gradient descent-based learning algorithm is used to train a recurrent multilayer perceptron network for use in empirical modeling of power plants. The two main advantages of the proposed learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation, instead of one forward and one backward pass of the backpropagation algorithm. The latter advantage results in computational time saving because both passes can be performed simultaneously. The dynamic learning algorithm is used to train a hybrid feedforward/feedback neural network, a recurrent multilayer perceptron, which was previously found to exhibit good interpolation and extrapolation capabilities in modeling nonlinear dynamic systems. One of the drawbacks, however, of the previously reported work has been the long training times associated with accurate empirical models. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm are demonstrated by a case study of a steam power plant. The number of iterations required for accurate empirical modeling has been reduced from tens of thousands to hundreds, thus significantly expediting the learning process
The q-G method : A q-version of the Steepest Descent method for global optimization.
Soterroni, Aline C; Galski, Roberto L; Scarabello, Marluce C; Ramos, Fernando M
2015-01-01
In this work, the q-Gradient (q-G) method, a q-version of the Steepest Descent method, is presented. The main idea behind the q-G method is the use of the negative of the q-gradient vector of the objective function as the search direction. The q-gradient vector, or simply the q-gradient, is a generalization of the classical gradient vector based on the concept of Jackson's derivative from the q-calculus. Its use provides the algorithm an effective mechanism for escaping from local minima. The q-G method reduces to the Steepest Descent method when the parameter q tends to 1. The algorithm has three free parameters and it is implemented so that the search process gradually shifts from global exploration in the beginning to local exploitation in the end. We evaluated the q-G method on 34 test functions, and compared its performance with 34 optimization algorithms, including derivative-free algorithms and the Steepest Descent method. Our results show that the q-G method is competitive and has a great potential for solving multimodal optimization problems.
Large Airborne Full Tensor Gradient Data Inversion Based on a Non-Monotone Gradient Method
Sun, Yong; Meng, Zhaohai; Li, Fengting
2018-03-01
Following the development of gravity gradiometer instrument technology, the full tensor gravity (FTG) data can be acquired on airborne and marine platforms. Large-scale geophysical data can be obtained using these methods, making such data sets a number of the "big data" category. Therefore, a fast and effective inversion method is developed to solve the large-scale FTG data inversion problem. Many algorithms are available to accelerate the FTG data inversion, such as conjugate gradient method. However, the conventional conjugate gradient method takes a long time to complete data processing. Thus, a fast and effective iterative algorithm is necessary to improve the utilization of FTG data. Generally, inversion processing is formulated by incorporating regularizing constraints, followed by the introduction of a non-monotone gradient-descent method to accelerate the convergence rate of FTG data inversion. Compared with the conventional gradient method, the steepest descent gradient algorithm, and the conjugate gradient algorithm, there are clear advantages of the non-monotone iterative gradient-descent algorithm. Simulated and field FTG data were applied to show the application value of this new fast inversion method.
Convergence results for a class of abstract continuous descent methods
Directory of Open Access Journals (Sweden)
Sergiu Aizicovici
2004-03-01
Full Text Available We study continuous descent methods for the minimization of Lipschitzian functions defined on a general Banach space. We establish convergence theorems for those methods which are generated by approximate solutions to evolution equations governed by regular vector fields. Since the complement of the set of regular vector fields is $sigma$-porous, we conclude that our results apply to most vector fields in the sense of Baire's categories.
International Nuclear Information System (INIS)
Jia, Ningning; Lam, Edmund Y
2010-01-01
Inverse lithography technology (ILT) synthesizes photomasks by solving an inverse imaging problem through optimization of an appropriate functional. Much effort on ILT is dedicated to deriving superior masks at a nominal process condition. However, the lower k 1 factor causes the mask to be more sensitive to process variations. Robustness to major process variations, such as focus and dose variations, is desired. In this paper, we consider the focus variation as a stochastic variable, and treat the mask design as a machine learning problem. The stochastic gradient descent approach, which is a useful tool in machine learning, is adopted to train the mask design. Compared with previous work, simulation shows that the proposed algorithm is effective in producing robust masks
International Nuclear Information System (INIS)
Dong Bing; Ren Deqing; Zhang Xi
2011-01-01
An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of any pattern. A circular stepped pattern is used in our preliminary experiment and the image contrast shows improvement from 10 -3 to 10 -4.5 at an angular distance of 2λ/D after being corrected by SPGD based AO.
Distributed Coordinate Descent Method for Learning with Big Data
Richtárik, Peter; Takáč, Martin
2013-01-01
In this paper we develop and analyze Hydra: HYbriD cooRdinAte descent method for solving loss minimization problems with big data. We initially partition the coordinates (features) and assign each partition to a different node of a cluster. At every iteration, each node picks a random subset of the coordinates from those it owns, independently from the other computers, and in parallel computes and applies updates to the selected coordinates based on a simple closed-form formula. We give bound...
Modified Convolutional Neural Network Based on Dropout and the Stochastic Gradient Descent Optimizer
Directory of Open Access Journals (Sweden)
Jing Yang
2018-03-01
Full Text Available This study proposes a modified convolutional neural network (CNN algorithm that is based on dropout and the stochastic gradient descent (SGD optimizer (MCNN-DS, after analyzing the problems of CNNs in extracting the convolution features, to improve the feature recognition rate and reduce the time-cost of CNNs. The MCNN-DS has a quadratic CNN structure and adopts the rectified linear unit as the activation function to avoid the gradient problem and accelerate convergence. To address the overfitting problem, the algorithm uses an SGD optimizer, which is implemented by inserting a dropout layer into the all-connected and output layers, to minimize cross entropy. This study used the datasets MNIST, HCL2000, and EnglishHand as the benchmark data, analyzed the performance of the SGD optimizer under different learning parameters, and found that the proposed algorithm exhibited good recognition performance when the learning rate was set to [0.05, 0.07]. The performances of WCNN, MLP-CNN, SVM-ELM, and MCNN-DS were compared. Statistical results showed the following: (1 For the benchmark MNIST, the MCNN-DS exhibited a high recognition rate of 99.97%, and the time-cost of the proposed algorithm was merely 21.95% of MLP-CNN, and 10.02% of SVM-ELM; (2 Compared with SVM-ELM, the average improvement in the recognition rate of MCNN-DS was 2.35% for the benchmark HCL2000, and the time-cost of MCNN-DS was only 15.41%; (3 For the EnglishHand test set, the lowest recognition rate of the algorithm was 84.93%, the highest recognition rate was 95.29%, and the average recognition rate was 89.77%.
Hybrid Steepest-Descent Methods for Triple Hierarchical Variational Inequalities
Directory of Open Access Journals (Sweden)
L. C. Ceng
2015-01-01
Full Text Available We introduce and analyze a relaxed iterative algorithm by combining Korpelevich’s extragradient method, hybrid steepest-descent method, and Mann’s iteration method. We prove that, under appropriate assumptions, the proposed algorithm converges strongly to a common element of the fixed point set of infinitely many nonexpansive mappings, the solution set of finitely many generalized mixed equilibrium problems (GMEPs, the solution set of finitely many variational inclusions, and the solution set of general system of variational inequalities (GSVI, which is just a unique solution of a triple hierarchical variational inequality (THVI in a real Hilbert space. In addition, we also consider the application of the proposed algorithm for solving a hierarchical variational inequality problem with constraints of finitely many GMEPs, finitely many variational inclusions, and the GSVI. The results obtained in this paper improve and extend the corresponding results announced by many others.
A feasible DY conjugate gradient method for linear equality constraints
LI, Can
2017-09-01
In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.
An Optimized Method for Terrain Reconstruction Based on Descent Images
Directory of Open Access Journals (Sweden)
Xu Xinchao
2016-02-01
Full Text Available An optimization method is proposed to perform high-accuracy terrain reconstruction of the landing area of Chang’e III. First, feature matching is conducted using geometric model constraints. Then, the initial terrain is obtained and the initial normal vector of each point is solved on the basis of the initial terrain. By changing the vector around the initial normal vector in small steps a set of new vectors is obtained. By combining these vectors with the direction of light and camera, the functions are set up on the basis of a surface reflection model. Then, a series of gray values is derived by solving the equations. The new optimized vector is recorded when the obtained gray value is closest to the corresponding pixel. Finally, the optimized terrain is obtained after iteration of the vector field. Experiments were conducted using the laboratory images and descent images of Chang’e III. The results showed that the performance of the proposed method was better than that of the classical feature matching method. It can provide a reference for terrain reconstruction of the landing area in subsequent moon exploration missions.
Directory of Open Access Journals (Sweden)
Afan Galih Salman
2011-06-01
Full Text Available The artificial neural network (ANN technology in rainfall prediction can be done using the learning approach. The ANN prediction accuracy is measured by the determination coefficient (R2 and root mean square error (RMSE. This research implements Elman’s Recurrent ANN which is heuristically optimized based on el-nino southern oscilation (ENSO variables: wind, southern oscillation index (SOI, sea surface temperatur (SST dan outgoing long wave radiation (OLR to forecast regional monthly rainfall in Bongan Bali. The heuristic learning optimization done is basically a performance development of standard gradient descent learning algorithm into training algorithms: gradient descent momentum and adaptive learning rate. The patterns of input data affect the performance of Recurrent Elman neural network in estimation process. The first data group that is 75% training data and 25% testing data produce the maximum R2 leap 74,6% while the second data group that is 50% training data and 50% testing data produce the maximum R2 leap 49,8%.
Block-conjugate-gradient method
International Nuclear Information System (INIS)
McCarthy, J.F.
1989-01-01
It is shown that by using the block-conjugate-gradient method several, say s, columns of the inverse Kogut-Susskind fermion matrix can be found simultaneously, in less time than it would take to run the standard conjugate-gradient algorithm s times. The method improves in efficiency relative to the standard conjugate-gradient algorithm as the fermion mass is decreased and as the value of the coupling is pushed to its limit before the finite-size effects become important. Thus it is potentially useful for measuring propagators in large lattice-gauge-theory calculations of the particle spectrum
preconditioning the modified conjugate gradient method
African Journals Online (AJOL)
Admin
steepest descent method, the number of matrix-vector products per iteration .... modified CGM algorithm is used for large class of problems that is not ..... New Trends in the Mathematical and Computer Sciences with Applications to Real World.
Directory of Open Access Journals (Sweden)
Huiru Zhao
2016-09-01
Full Text Available An important goal of China’s electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs and demanders (represented by DisCOs compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP and each rival’s bidding strategy as common knowledge (in dynamic game market models, and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models, which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n. The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant’s profit or social welfare
Steepest descent moment method for three-dimensional magnetohydrodynamic equilibria
International Nuclear Information System (INIS)
Hirshman, S.P.; Whitson, J.C.
1983-11-01
An energy principle is used to obtain the solution of the magnetohydrodynamic (MHD) equilibrium equation J Vector x B Vector - del p = 0 for nested magnetic flux surfaces that are expressed in the inverse coordinate representation x Vector = x Vector(rho, theta, zeta). Here, theta and zeta are poloidal and toroidal flux coordinate angles, respectively, and p = p(rho) labels a magnetic surface. Ordinary differential equations in rho are obtained for the Fourier amplitudes (moments) in the doubly periodic spectral decomposition of x Vector. A steepest descent iteration is developed for efficiently solving these nonlinear, coupled moment equations. The existence of a positive-definite energy functional guarantees the monotonic convergence of this iteration toward an equilibrium solution (in the absence of magnetic island formation). A renormalization parameter lambda is introduced to ensure the rapid convergence of the Fourier series for x Vector, while simultaneously satisfying the MHD requirement that magnetic field lines are straight in flux coordinates. A descent iteration is also developed for determining the self-consistent value for lambda
Energy Technology Data Exchange (ETDEWEB)
Liu, Mingxue [Life Science and Engineering College, Southwest University of Science and Technology, Mianyang, 621010 (China); Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Dong, Faqin, E-mail: fqdong@swust.edu.cn [Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Zhang, Wei [Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Nie, Xiaoqin [Fundamental Science on Nuclear Wastes and Environmental Safety Laboratory, Mianyang, 621010 (China); Sun, Shiyong [Key Laboratory of Solid Waste Treatment and Resource Recycle, Ministry of Education of China, Mianyang, 621010 (China); Wei, Hongfu; Luo, Lang; Xiang, Sha; Zhang, Gege [Life Science and Engineering College, Southwest University of Science and Technology, Mianyang, 621010 (China)
2016-08-15
Highlights: • A programmed gradient descent biosorption process was designed. • The adsorption and bioaccumulation quantity of strontium ions by yeast cell were measured. • The decrement of biosorbents after biosorption by ashing was analyzed. • A technological flow process of decrement solution for waste disposal was proposed. - Abstract: One of the waste disposal principles is decrement. The programmed gradient descent biosorption of strontium ions by Saccaromyces cerevisiae regarding bioremoval and ashing process for decrement were studied in present research. The results indicated that S. cerevisiae cells showed valid biosorption for strontium ions with greater than 90% bioremoval efficiency for high concentration strontium ions under batch culture conditions. The S. cerevisiae cells bioaccumulated approximately 10% of strontium ions in the cytoplasm besides adsorbing 90% strontium ions on cell wall. The programmed gradient descent biosorption presented good performance with a nearly 100% bioremoval ratio for low concentration strontium ions after 3 cycles. The ashing process resulted in a huge volume and weight reduction ratio as well as enrichment for strontium in the ash. XRD results showed that SrSO{sub 4} existed in ash. Simulated experiments proved that sulfate could adjust the precipitation of strontium ions. Finally, we proposed a technological flow process that combined the programmed gradient descent biosorption and ashing, which could yield great decrement and allow the supernatant to meet discharge standard. This technological flow process may be beneficial for nuclides and heavy metal disposal treatment in many fields.
Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization
Directory of Open Access Journals (Sweden)
Jinkui Liu
2012-01-01
Full Text Available A new nonlinear spectral conjugate descent method for solving unconstrained optimization problems is proposed on the basis of the CD method and the spectral conjugate gradient method. For any line search, the new method satisfies the sufficient descent condition gkTdk<−∥gk∥2. Moreover, we prove that the new method is globally convergent under the strong Wolfe line search. The numerical results show that the new method is more effective for the given test problems from the CUTE test problem library (Bongartz et al., 1995 in contrast to the famous CD method, FR method, and PRP method.
A three-term conjugate gradient method under the strong-Wolfe line search
Khadijah, Wan; Rivaie, Mohd; Mamat, Mustafa
2017-08-01
Recently, numerous studies have been concerned in conjugate gradient methods for solving large-scale unconstrained optimization method. In this paper, a three-term conjugate gradient method is proposed for unconstrained optimization which always satisfies sufficient descent direction and namely as Three-Term Rivaie-Mustafa-Ismail-Leong (TTRMIL). Under standard conditions, TTRMIL method is proved to be globally convergent under strong-Wolfe line search. Finally, numerical results are provided for the purpose of comparison.
Ghani, N. H. A.; Mohamed, N. S.; Zull, N.; Shoid, S.; Rivaie, M.; Mamat, M.
2017-09-01
Conjugate gradient (CG) method is one of iterative techniques prominently used in solving unconstrained optimization problems due to its simplicity, low memory storage, and good convergence analysis. This paper presents a new hybrid conjugate gradient method, named NRM1 method. The method is analyzed under the exact and inexact line searches in given conditions. Theoretically, proofs show that the NRM1 method satisfies the sufficient descent condition with both line searches. The computational result indicates that NRM1 method is capable in solving the standard unconstrained optimization problems used. On the other hand, the NRM1 method performs better under inexact line search compared with exact line search.
A Gradient Taguchi Method for Engineering Optimization
Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song
2017-10-01
To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.
STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION
Directory of Open Access Journals (Sweden)
Nataša Krejić
2014-12-01
Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.
Directory of Open Access Journals (Sweden)
Zhongbo Sun
2014-01-01
Full Text Available Two modified three-term type conjugate gradient algorithms which satisfy both the descent condition and the Dai-Liao type conjugacy condition are presented for unconstrained optimization. The first algorithm is a modification of the Hager and Zhang type algorithm in such a way that the search direction is descent and satisfies Dai-Liao’s type conjugacy condition. The second simple three-term type conjugate gradient method can generate sufficient decent directions at every iteration; moreover, this property is independent of the steplength line search. Also, the algorithms could be considered as a modification of the MBFGS method, but with different zk. Under some mild conditions, the given methods are global convergence, which is independent of the Wolfe line search for general functions. The numerical experiments show that the proposed methods are very robust and efficient.
Preconditioning the modified conjugate gradient method ...
African Journals Online (AJOL)
In this paper, the convergence analysis of the conventional conjugate Gradient method was reviewed. And the convergence analysis of the modified conjugate Gradient method was analysed with our extension on preconditioning the algorithm. Convergence of the algorithm is a function of the condition number of M-1A.
Approximate error conjugation gradient minimization methods
Kallman, Jeffrey S
2013-05-21
In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.
Directory of Open Access Journals (Sweden)
Zhifeng Dai
2014-01-01
Full Text Available Combining the Rosen gradient projection method with the two-term Polak-Ribière-Polyak (PRP conjugate gradient method, we propose a two-term Polak-Ribière-Polyak (PRP conjugate gradient projection method for solving linear equality constraints optimization problems. The proposed method possesses some attractive properties: (1 search direction generated by the proposed method is a feasible descent direction; consequently the generated iterates are feasible points; (2 the sequences of function are decreasing. Under some mild conditions, we show that it is globally convergent with Armijio-type line search. Preliminary numerical results show that the proposed method is promising.
Gradient High Performance Liquid Chromatography Method ...
African Journals Online (AJOL)
Purpose: To develop a gradient high performance liquid chromatography (HPLC) method for the simultaneous determination of phenylephrine (PHE) and ibuprofen (IBU) in solid ..... nimesulide, phenylephrine. Hydrochloride, chlorpheniramine maleate and caffeine anhydrous in pharmaceutical dosage form. Acta Pol.
New hybrid conjugate gradient methods with the generalized Wolfe line search.
Xu, Xiao; Kong, Fan-Yu
2016-01-01
The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.
Nonlinear conjugate gradient methods in micromagnetics
Directory of Open Access Journals (Sweden)
J. Fischbacher
2017-04-01
Full Text Available Conjugate gradient methods for energy minimization in micromagnetics are compared. The comparison of analytic results with numerical simulation shows that standard conjugate gradient method may fail to produce correct results. A method that restricts the step length in the line search is introduced, in order to avoid this problem. When the step length in the line search is controlled, conjugate gradient techniques are a fast and reliable way to compute the hysteresis properties of permanent magnets. The method is applied to investigate demagnetizing effects in NdFe12 based permanent magnets. The reduction of the coercive field by demagnetizing effects is μ0ΔH = 1.4 T at 450 K.
Accelerated convergence of the steepest-descent method for magnetohydrodynamic equilibria
International Nuclear Information System (INIS)
Handy, C.R.; Hirshman, S.P.
1984-06-01
Iterative schemes based on the method of steepest descent have recently been used to obtain magnetohydrodynamic (MHD) equilibria. Such schemes generate asymptotic geometric vector sequences whose convergence rate can be improved through the use of the epsilon-algorithm. The application of this nonlinear recursive technique to stiff systems is discussed. In principle, the epsilon-algorithm is capable of yielding quadratic convergence and therefore represents an attractive alternative to other quadratic convergence schemes requiring Jacobian matrix inversion. Because the damped MHD equations have eigenvalues with negative real parts (in the neighborhood of a stable equilibrium), the epsilon-algorithm will generally be stable. Concern for residual monotonic sequences leads to consideration of alternative methods for implementing the algorithm
Dai-Kou type conjugate gradient methods with a line search only using gradient.
Huang, Yuanyuan; Liu, Changhe
2017-01-01
In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope. Under suitable conditions, the developed methods are globally convergent. Numerical tests and comparisons with the PRP+ conjugate gradient method only using gradient show that the methods are efficient.
A new family of Polak-Ribiere-Polyak conjugate gradient method with the strong-Wolfe line search
Ghani, Nur Hamizah Abdul; Mamat, Mustafa; Rivaie, Mohd
2017-08-01
Conjugate gradient (CG) method is an important technique in unconstrained optimization, due to its effectiveness and low memory requirements. The focus of this paper is to introduce a new CG method for solving large scale unconstrained optimization. Theoretical proofs show that the new method fulfills sufficient descent condition if strong Wolfe-Powell inexact line search is used. Besides, computational results show that our proposed method outperforms to other existing CG methods.
Verhoeven, Ronald; Dalmau Codina, Ramon; Prats Menéndez, Xavier; de Gelder, Nico
2014-01-01
1 Abstract In this paper an initial implementation of a real - time aircraft trajectory optimization algorithm is presented . The aircraft trajectory for descent and approach is computed for minimum use of thrust and speed brake in support of a “green” continuous descent and approach flight operation, while complying with ATC time constraints for maintaining runway throughput and co...
Energy Technology Data Exchange (ETDEWEB)
Tung, Wu-Hsiung, E-mail: wstong@iner.gov.tw; Lee, Tien-Tso; Kuo, Weng-Sheng; Yaur, Shung-Jung
2017-03-15
Highlights: • An optimization method for axial enrichment distribution in a BWR fuel was developed. • Block coordinate descent method is employed to search for optimal solution. • Scoping libraries are used to reduce computational effort. • Optimization search space consists of enrichment difference parameters. • Capability of the method to find optimal solution is demonstrated. - Abstract: An optimization method has been developed to search for the optimal axial enrichment distribution in a fuel assembly for a boiling water reactor core. The optimization method features: (1) employing the block coordinate descent method to find the optimal solution in the space of enrichment difference parameters, (2) using scoping libraries to reduce the amount of CASMO-4 calculation, and (3) integrating a core critical constraint into the objective function that is used to quantify the quality of an axial enrichment design. The objective function consists of the weighted sum of core parameters such as shutdown margin and critical power ratio. The core parameters are evaluated by using SIMULATE-3, and the cross section data required for the SIMULATE-3 calculation are generated by using CASMO-4 and scoping libraries. The application of the method to a 4-segment fuel design (with the highest allowable segment enrichment relaxed to 5%) demonstrated that the method can obtain an axial enrichment design with improved thermal limit ratios and objective function value while satisfying the core design constraints and core critical requirement through the use of an objective function. The use of scoping libraries effectively reduced the number of CASMO-4 calculation, from 85 to 24, in the 4-segment optimization case. An exhausted search was performed to examine the capability of the method in finding the optimal solution for a 4-segment fuel design. The results show that the method found a solution very close to the optimum obtained by the exhausted search. The number of
The multigrid preconditioned conjugate gradient method
Tatebe, Osamu
1993-01-01
A multigrid preconditioned conjugate gradient method (MGCG method), which uses the multigrid method as a preconditioner of the PCG method, is proposed. The multigrid method has inherent high parallelism and improves convergence of long wavelength components, which is important in iterative methods. By using this method as a preconditioner of the PCG method, an efficient method with high parallelism and fast convergence is obtained. First, it is considered a necessary condition of the multigrid preconditioner in order to satisfy requirements of a preconditioner of the PCG method. Next numerical experiments show a behavior of the MGCG method and that the MGCG method is superior to both the ICCG method and the multigrid method in point of fast convergence and high parallelism. This fast convergence is understood in terms of the eigenvalue analysis of the preconditioned matrix. From this observation of the multigrid preconditioner, it is realized that the MGCG method converges in very few iterations and the multigrid preconditioner is a desirable preconditioner of the conjugate gradient method.
Exploring the 3D Surfaces with Modified Method of Steepest Descent
Directory of Open Access Journals (Sweden)
Wioletta GRZENDA
2012-06-01
Full Text Available Aim: To prove expediency of the steepest descent method to divide a given cloud of (Y, X1, X2 points into the spatial clusters with purpose to estimate a simple regression model Y = f(Z|X1,X2 at each cluster. Material and Method: The exemplary data sets {Y, X1, X2} were drawn randomly from assumed 3D surface: Y = f(X1,X2, and then a random noise was added to variable Y. A polynomial model Y = f(X1,X2 and a set of models Y = f(Z|X1,X2 were estimated separately, both under Akaike information criterion (AIC, and then compared with respect to their determination coefficients R-square, and the residuals’ distributions. Results: In the artificial data set studied, the both compared methods after several iterations can provide regression models of the quite similar quality. Conclusions: Because the proposed novel method seems to be more robust to outliers, and easier to graphical presentations and to intuitive understanding than the conventional way of building a regression model, the proposed novel method can be recommended to use by non-statisticians, especially in situation when, besides usual moderate noise, the sporadic but influential measurement errors can occur.
M-step preconditioned conjugate gradient methods
Adams, L.
1983-01-01
Preconditioned conjugate gradient methods for solving sparse symmetric and positive finite systems of linear equations are described. Necessary and sufficient conditions are given for when these preconditioners can be used and an analysis of their effectiveness is given. Efficient computer implementations of these methods are discussed and results on the CYBER 203 and the Finite Element Machine under construction at NASA Langley Research Center are included.
Parente2: a fast and accurate method for detecting identity by descent
Rodriguez, Jesse M.
2014-10-01
Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort\\'s size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2\\'s performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency.
Parente2: a fast and accurate method for detecting identity by descent
Rodriguez, Jesse M.; Bercovici, Sivan; Huang, Lin; Frostig, Roy; Batzoglou, Serafim
2014-01-01
Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort's size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2's performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency.
Energy Technology Data Exchange (ETDEWEB)
Feng, Wenqiang, E-mail: wfeng1@vols.utk.edu [Department of Mathematics, The University of Tennessee, Knoxville, TN 37996 (United States); Salgado, Abner J., E-mail: asalgad1@utk.edu [Department of Mathematics, The University of Tennessee, Knoxville, TN 37996 (United States); Wang, Cheng, E-mail: cwang1@umassd.edu [Department of Mathematics, The University of Massachusetts, North Dartmouth, MA 02747 (United States); Wise, Steven M., E-mail: swise1@utk.edu [Department of Mathematics, The University of Tennessee, Knoxville, TN 37996 (United States)
2017-04-01
We describe and analyze preconditioned steepest descent (PSD) solvers for fourth and sixth-order nonlinear elliptic equations that include p-Laplacian terms on periodic domains in 2 and 3 dimensions. The highest and lowest order terms of the equations are constant-coefficient, positive linear operators, which suggests a natural preconditioning strategy. Such nonlinear elliptic equations often arise from time discretization of parabolic equations that model various biological and physical phenomena, in particular, liquid crystals, thin film epitaxial growth and phase transformations. The analyses of the schemes involve the characterization of the strictly convex energies associated with the equations. We first give a general framework for PSD in Hilbert spaces. Based on certain reasonable assumptions of the linear pre-conditioner, a geometric convergence rate is shown for the nonlinear PSD iteration. We then apply the general theory to the fourth and sixth-order problems of interest, making use of Sobolev embedding and regularity results to confirm the appropriateness of our pre-conditioners for the regularized p-Lapacian problems. Our results include a sharper theoretical convergence result for p-Laplacian systems compared to what may be found in existing works. We demonstrate rigorously how to apply the theory in the finite dimensional setting using finite difference discretization methods. Numerical simulations for some important physical application problems – including thin film epitaxy with slope selection and the square phase field crystal model – are carried out to verify the efficiency of the scheme.
Directory of Open Access Journals (Sweden)
Bighnaraj Naik
2018-01-01
Full Text Available All the higher order ANNs (HONNs including functional link ANN (FLANN are sensitive to random initialization of weight and rely on the learning algorithms adopted. Although a selection of efficient learning algorithms for HONNs helps to improve the performance, on the other hand, initialization of weights with optimized weights rather than random weights also play important roles on its efficiency. In this paper, the problem solving approach of the teaching learning based optimization (TLBO along with learning ability of the gradient descent learning (GDL is used to obtain the optimal set of weight of FLANN learning model. TLBO does not require any specific parameters rather it requires only some of the common independent parameters like number of populations, number of iterations and stopping criteria, thereby eliminating the intricacy in selection of algorithmic parameters for adjusting the set of weights of FLANN model. The proposed TLBO-FLANN is implemented in MATLAB and compared with GA-FLANN, PSO-FLANN and HS-FLANN. The TLBO-FLANN is tested on various 5-fold cross validated benchmark data sets from UCI machine learning repository and analyzed under the null-hypothesis by using Friedman test, Holm’s procedure and post hoc ANOVA statistical analysis (Tukey test & Dunnett test.
Du, Shouqiang; Chen, Miao
2018-01-01
We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.
2012-08-01
Sciandrone, On the convergence of the block nonlinear Gauss - Seidel method under convex constraints , Oper. Res. Lett., 26 (2000), pp. 127–136. [23] S.P...include nonsmooth functions. Our main interest is the block coordinate descent (BCD) method of the Gauss - Seidel type, which mini- mizes F cyclically over...original objective around the current iterate . They do not use extrapolation either and only have subsequence convergence . There are examples of ri
Accelerated gradient methods for constrained image deblurring
International Nuclear Information System (INIS)
Bonettini, S; Zanella, R; Zanni, L; Bertero, M
2008-01-01
In this paper we propose a special gradient projection method for the image deblurring problem, in the framework of the maximum likelihood approach. We present the method in a very general form and we give convergence results under standard assumptions. Then we consider the deblurring problem and the generality of the proposed algorithm allows us to add a energy conservation constraint to the maximum likelihood problem. In order to improve the convergence rate, we devise appropriate scaling strategies and steplength updating rules, especially designed for this application. The effectiveness of the method is evaluated by means of a computational study on astronomical images corrupted by Poisson noise. Comparisons with standard methods for image restoration, such as the expectation maximization algorithm, are also reported.
A method for easily customizable gradient gel electrophoresis.
Miller, Andrew J; Roman, Brandon; Norstrom, Eric
2016-09-15
Gradient polyacrylamide gel electrophoresis is a powerful tool for the resolution of polypeptides by relative mobility. Here, we present a simplified method for generating polyacrylamide gradient gels for routine analysis without the need for specialized mixing equipment. The method allows for easily customizable gradients which can be optimized for specific polypeptide resolution requirements. Moreover, the method eliminates the possibility of buffer cross contamination in mixing equipment, and the time and resources saved with this method in place of traditional gradient mixing, or the purchase of pre-cast gels, are noteworthy given the frequency with which many labs use gradient gel SDS-PAGE. Copyright © 2016 Elsevier Inc. All rights reserved.
An Efficient Hybrid Conjugate Gradient Method with the Strong Wolfe-Powell Line Search
Directory of Open Access Journals (Sweden)
Ahmad Alhawarat
2015-01-01
Full Text Available Conjugate gradient (CG method is an interesting tool to solve optimization problems in many fields, such as design, economics, physics, and engineering. In this paper, we depict a new hybrid of CG method which relates to the famous Polak-Ribière-Polyak (PRP formula. It reveals a solution for the PRP case which is not globally convergent with the strong Wolfe-Powell (SWP line search. The new formula possesses the sufficient descent condition and the global convergent properties. In addition, we further explained about the cases where PRP method failed with SWP line search. Furthermore, we provide numerical computations for the new hybrid CG method which is almost better than other related PRP formulas in both the number of iterations and the CPU time under some standard test functions.
Comparison of genetic algorithms with conjugate gradient methods
Bosworth, J. L.; Foo, N. Y.; Zeigler, B. P.
1972-01-01
Genetic algorithms for mathematical function optimization are modeled on search strategies employed in natural adaptation. Comparisons of genetic algorithms with conjugate gradient methods, which were made on an IBM 1800 digital computer, show that genetic algorithms display superior performance over gradient methods for functions which are poorly behaved mathematically, for multimodal functions, and for functions obscured by additive random noise. Genetic methods offer performance comparable to gradient methods for many of the standard functions.
Solving Optimal Control Problem of Monodomain Model Using Hybrid Conjugate Gradient Methods
Directory of Open Access Journals (Sweden)
Kin Wei Ng
2012-01-01
Full Text Available We present the numerical solutions for the PDE-constrained optimization problem arising in cardiac electrophysiology, that is, the optimal control problem of monodomain model. The optimal control problem of monodomain model is a nonlinear optimization problem that is constrained by the monodomain model. The monodomain model consists of a parabolic partial differential equation coupled to a system of nonlinear ordinary differential equations, which has been widely used for simulating cardiac electrical activity. Our control objective is to dampen the excitation wavefront using optimal applied extracellular current. Two hybrid conjugate gradient methods are employed for computing the optimal applied extracellular current, namely, the Hestenes-Stiefel-Dai-Yuan (HS-DY method and the Liu-Storey-Conjugate-Descent (LS-CD method. Our experiment results show that the excitation wavefronts are successfully dampened out when these methods are used. Our experiment results also show that the hybrid conjugate gradient methods are superior to the classical conjugate gradient methods when Armijo line search is used.
Directory of Open Access Journals (Sweden)
M. Peng
2017-07-01
Full Text Available The multi-source DEMs generated using the images acquired in the descent and landing phase and after landing contain supplementary information, and this makes it possible and beneficial to produce a higher-quality DEM through fusing the multi-scale DEMs. The proposed fusion method consists of three steps. First, source DEMs are split into small DEM patches, then the DEM patches are classified into a few groups by local density peaks clustering. Next, the grouped DEM patches are used for sub-dictionary learning by stochastic coordinate coding. The trained sub-dictionaries are combined into a dictionary for sparse representation. Finally, the simultaneous orthogonal matching pursuit (SOMP algorithm is used to achieve sparse representation. We use the real DEMs generated from Chang’e-3 descent images and navigation camera (Navcam stereo images to validate the proposed method. Through the experiments, we have reconstructed a seamless DEM with the highest resolution and the largest spatial coverage among the input data. The experimental results demonstrated the feasibility of the proposed method.
Minimum weight protection - Gradient method; Protection de poids minimum - Methode du gradient
Energy Technology Data Exchange (ETDEWEB)
Danon, R.
1958-12-15
After having recalled that, when considering a mobile installation, total weight has a crucial importance, and that, in the case of a nuclear reactor, a non neglectable part of weight is that of protection, this note presents an iterative method which results, for a given protection, to a configuration with a minimum weight. After a description of the problem, the author presents the theoretical formulation of the gradient method as it is applied to the concerned case. This application is then discussed, as well as its validity in terms of convergence and uniqueness. Its actual application is then reported, and possibilities of practical applications are evoked.
Modified conjugate gradient method for diagonalizing large matrices.
Jie, Quanlin; Liu, Dunhuan
2003-11-01
We present an iterative method to diagonalize large matrices. The basic idea is the same as the conjugate gradient (CG) method, i.e, minimizing the Rayleigh quotient via its gradient and avoiding reintroducing errors to the directions of previous gradients. Each iteration step is to find lowest eigenvector of the matrix in a subspace spanned by the current trial vector and the corresponding gradient of the Rayleigh quotient, as well as some previous trial vectors. The gradient, together with the previous trial vectors, play a similar role as the conjugate gradient of the original CG algorithm. Our numeric tests indicate that this method converges significantly faster than the original CG method. And the computational cost of one iteration step is about the same as the original CG method. It is suitable for first principle calculations.
A new method of determining moisture gradient in wood
Zhiyong Cai
2008-01-01
Moisture gradient in wood and wood composites is one of most important factors that affects both physical stability and mechanical performance. This paper describes a method for measuring moisture gradient in lumber and engineering wood composites as it varies across material thickness. This innovative method employs a collimated radiation beam (x rays or [gamma] rays...
New Conjugacy Conditions and Related Nonlinear Conjugate Gradient Methods
International Nuclear Information System (INIS)
Dai, Y.-H.; Liao, L.-Z.
2001-01-01
Conjugate gradient methods are a class of important methods for unconstrained optimization, especially when the dimension is large. This paper proposes a new conjugacy condition, which considers an inexact line search scheme but reduces to the old one if the line search is exact. Based on the new conjugacy condition, two nonlinear conjugate gradient methods are constructed. Convergence analysis for the two methods is provided. Our numerical results show that one of the methods is very efficient for the given test problems
Gradient porous hydroxyapatite ceramics fabricated by freeze casting method
International Nuclear Information System (INIS)
Zuo Kaihui; Zhang Yuan; Jiang Dongliang; Zeng Yuping
2011-01-01
By controlling the cooling rates and the composition of slurries, the gradient porous hydroxyapatite ceramics are fabricated by the freeze casting method. According to the different cooling rate, the pores of HAP ceramics fabricated by gradient freeze casting are divided into three parts: one is lamellar pores, another is column pore and the last one is fine round pores. The laminated freeze casting is in favour of obtaining the gradient porous ceramics composed of different materials and the ceramics have unclear interfaces.
Discrete gradient methods for solving variational image regularisation models
International Nuclear Information System (INIS)
Grimm, V; McLachlan, Robert I; McLaren, David I; Quispel, G R W; Schönlieb, C-B
2017-01-01
Discrete gradient methods are well-known methods of geometric numerical integration, which preserve the dissipation of gradient systems. In this paper we show that this property of discrete gradient methods can be interesting in the context of variational models for image processing, that is where the processed image is computed as a minimiser of an energy functional. Numerical schemes for computing minimisers of such energies are desired to inherit the dissipative property of the gradient system associated to the energy and consequently guarantee a monotonic decrease of the energy along iterations, avoiding situations in which more computational work might lead to less optimal solutions. Under appropriate smoothness assumptions on the energy functional we prove that discrete gradient methods guarantee a monotonic decrease of the energy towards stationary states, and we promote their use in image processing by exhibiting experiments with convex and non-convex variational models for image deblurring, denoising, and inpainting. (paper)
Gradient-type methods in inverse parabolic problems
International Nuclear Information System (INIS)
Kabanikhin, Sergey; Penenko, Aleksey
2008-01-01
This article is devoted to gradient-based methods for inverse parabolic problems. In the first part, we present a priori convergence theorems based on the conditional stability estimates for linear inverse problems. These theorems are applied to backwards parabolic problem and sideways parabolic problem. The convergence conditions obtained coincide with sourcewise representability in the self-adjoint backwards parabolic case but they differ in the sideways case. In the second part, a variational approach is formulated for a coefficient identification problem. Using adjoint equations, a formal gradient of an objective functional is constructed. A numerical test illustrates the performance of conjugate gradient algorithm with the formal gradient.
Csiba, Dominik
2017-09-09
In this paper we introduce two novel generalizations of the theory for gradient descent type methods in the proximal setting. First, we introduce the proportion function, which we further use to analyze all known (and many new) block-selection rules for block coordinate descent methods under a single framework. This framework includes randomized methods with uniform, non-uniform or even adaptive sampling strategies, as well as deterministic methods with batch, greedy or cyclic selection rules. Second, the theory of strongly-convex optimization was recently generalized to a specific class of non-convex functions satisfying the so-called Polyak-{\\\\L}ojasiewicz condition. To mirror this generalization in the weakly convex case, we introduce the Weak Polyak-{\\\\L}ojasiewicz condition, using which we give global convergence guarantees for a class of non-convex functions previously not considered in theory. Additionally, we establish (necessarily somewhat weaker) convergence guarantees for an even larger class of non-convex functions satisfying a certain smoothness assumption only. By combining the two abovementioned generalizations we recover the state-of-the-art convergence guarantees for a large class of previously known methods and setups as special cases of our general framework. Moreover, our frameworks allows for the derivation of new guarantees for many new combinations of methods and setups, as well as a large class of novel non-convex objectives. The flexibility of our approach offers a lot of potential for future research, as a new block selection procedure will have a convergence guarantee for all objectives considered in our framework, while a new objective analyzed under our approach will have a whole fleet of block selection rules with convergence guarantees readily available.
Csiba, Dominik; Richtarik, Peter
2017-01-01
In this paper we introduce two novel generalizations of the theory for gradient descent type methods in the proximal setting. First, we introduce the proportion function, which we further use to analyze all known (and many new) block-selection rules for block coordinate descent methods under a single framework. This framework includes randomized methods with uniform, non-uniform or even adaptive sampling strategies, as well as deterministic methods with batch, greedy or cyclic selection rules. Second, the theory of strongly-convex optimization was recently generalized to a specific class of non-convex functions satisfying the so-called Polyak-{\\L}ojasiewicz condition. To mirror this generalization in the weakly convex case, we introduce the Weak Polyak-{\\L}ojasiewicz condition, using which we give global convergence guarantees for a class of non-convex functions previously not considered in theory. Additionally, we establish (necessarily somewhat weaker) convergence guarantees for an even larger class of non-convex functions satisfying a certain smoothness assumption only. By combining the two abovementioned generalizations we recover the state-of-the-art convergence guarantees for a large class of previously known methods and setups as special cases of our general framework. Moreover, our frameworks allows for the derivation of new guarantees for many new combinations of methods and setups, as well as a large class of novel non-convex objectives. The flexibility of our approach offers a lot of potential for future research, as a new block selection procedure will have a convergence guarantee for all objectives considered in our framework, while a new objective analyzed under our approach will have a whole fleet of block selection rules with convergence guarantees readily available.
Stochastic Spectral Descent for Discrete Graphical Models
International Nuclear Information System (INIS)
Carlson, David; Hsieh, Ya-Ping; Collins, Edo; Carin, Lawrence; Cevher, Volkan
2015-01-01
Interest in deep probabilistic graphical models has in-creased in recent years, due to their state-of-the-art performance on many machine learning applications. Such models are typically trained with the stochastic gradient method, which can take a significant number of iterations to converge. Since the computational cost of gradient estimation is prohibitive even for modestly sized models, training becomes slow and practically usable models are kept small. In this paper we propose a new, largely tuning-free algorithm to address this problem. Our approach derives novel majorization bounds based on the Schatten- norm. Intriguingly, the minimizers of these bounds can be interpreted as gradient methods in a non-Euclidean space. We thus propose using a stochastic gradient method in non-Euclidean space. We both provide simple conditions under which our algorithm is guaranteed to converge, and demonstrate empirically that our algorithm leads to dramatically faster training and improved predictive ability compared to stochastic gradient descent for both directed and undirected graphical models.
Variational method for integrating radial gradient field
Legarda-Saenz, Ricardo; Brito-Loeza, Carlos; Rivera, Mariano; Espinosa-Romero, Arturo
2014-12-01
We propose a variational method for integrating information obtained from circular fringe pattern. The proposed method is a suitable choice for objects with radial symmetry. First, we analyze the information contained in the fringe pattern captured by the experimental setup and then move to formulate the problem of recovering the wavefront using techniques from calculus of variations. The performance of the method is demonstrated by numerical experiments with both synthetic and real data.
A Spectral Conjugate Gradient Method for Unconstrained Optimization
International Nuclear Information System (INIS)
Birgin, E. G.; Martinez, J. M.
2001-01-01
A family of scaled conjugate gradient algorithms for large-scale unconstrained minimization is defined. The Perry, the Polak-Ribiere and the Fletcher-Reeves formulae are compared using a spectral scaling derived from Raydan's spectral gradient optimization method. The best combination of formula, scaling and initial choice of step-length is compared against well known algorithms using a classical set of problems. An additional comparison involving an ill-conditioned estimation problem in Optics is presented
A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method
Directory of Open Access Journals (Sweden)
Shengwei Yao
2014-01-01
Full Text Available The conjugate gradient (CG method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. In this paper, we propose a new conjugacy condition which is similar to Dai-Liao (2001. Based on this condition, the related nonlinear conjugate gradient method is given. With some mild conditions, the given method is globally convergent under the strong Wolfe-Powell line search for general functions. The numerical experiments show that the proposed method is very robust and efficient.
A density gradient theory based method for surface tension calculations
DEFF Research Database (Denmark)
Liang, Xiaodong; Michelsen, Michael Locht; Kontogeorgis, Georgios
2016-01-01
The density gradient theory has been becoming a widely used framework for calculating surface tension, within which the same equation of state is used for the interface and bulk phases, because it is a theoretically sound, consistent and computationally affordable approach. Based on the observation...... that the optimal density path from the geometric mean density gradient theory passes the saddle point of the tangent plane distance to the bulk phases, we propose to estimate surface tension with an approximate density path profile that goes through this saddle point. The linear density gradient theory, which...... assumes linearly distributed densities between the two bulk phases, has also been investigated. Numerical problems do not occur with these density path profiles. These two approximation methods together with the full density gradient theory have been used to calculate the surface tension of various...
2016-05-11
REPORT NUMBER 9. SPONSORING/ MONITORING AGENCY NAME(S) AND ADDRESS(ES) AOARD UNIT 45002 APO AP 96338-5002 10. SPONSOR/MONITOR’S ACRONYM(S) AFRL/AFOSR IOA...orders of magnitude less memory than our competitors . We implemented our methods on MAPREDUCE with two widely-applicable optimization techniques...local disk caching and greedy row assignment. They speeded up our methods up to 98.2x and also the competitors up to 5.9x. 15. SUBJECT TERMS 16
A hybrid optimization method for biplanar transverse gradient coil design
International Nuclear Information System (INIS)
Qi Feng; Tang Xin; Jin Zhe; Jiang Zhongde; Shen Yifei; Meng Bin; Zu Donglin; Wang Weimin
2007-01-01
The optimization of transverse gradient coils is one of the fundamental problems in designing magnetic resonance imaging gradient systems. A new approach is presented in this paper to optimize the transverse gradient coils' performance. First, in the traditional spherical harmonic target field method, high order coefficients, which are commonly ignored, are used in the first stage of the optimization process to give better homogeneity. Then, some cosine terms are introduced into the series expansion of stream function. These new terms provide simulated annealing optimization with new freedoms. Comparison between the traditional method and the optimized method shows that the inhomogeneity in the region of interest can be reduced from 5.03% to 1.39%, the coil efficiency increased from 3.83 to 6.31 mT m -1 A -1 and the minimum distance of these discrete coils raised from 1.54 to 3.16 mm
Gradient-based methods for production optimization of oil reservoirs
Energy Technology Data Exchange (ETDEWEB)
Suwartadi, Eka
2012-07-01
Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM
Deflation in preconditioned conjugate gradient methods for Finite Element Problems
Vermolen, F.J.; Vuik, C.; Segal, A.
2002-01-01
We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods applied to a Finite Element discretization for an elliptic equation. Our set-up is a Poisson problem in two dimensions with continuous or discontinuous
Accurate conjugate gradient methods for families of shifted systems
Eshof, J. van den; Sleijpen, G.L.G.
We present an efficient and accurate variant of the conjugate gradient method for solving families of shifted systems. In particular we are interested in shifted systems that occur in Tikhonov regularization for inverse problems since these problems can be sensitive to roundoff errors. The
Method to stimulate dose gradient in liquid media
International Nuclear Information System (INIS)
Scarlat, F.
1993-01-01
The depth absorbed dose from electrons with energy higher than 10 MeV shows a distribution with a big-percentage absorbed dose at the entrance surface and a small dose gradient. This is due to the big distance between the virtual focus and irradiated liquid medium. In order to stimulate dose gradient and decrease the surface dose, this paper presents a method for obtaining the second focus by means of a magnetostatic planar wiggler. Preliminary calculations indicated that the absorbed dose rate increases two-three times at the reference plane in the irradiated liquid medium. (Author)
Optimization algorithm based on densification and dynamic canonical descent
Bousson, K.; Correia, S. D.
2006-07-01
Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable. They have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method, which reduces the search space by means of densification curves, coupled with the dynamic canonical descent algorithm. The performances of the new method are shown on several known problems classically used for testing optimization algorithms, and proved to outperform competitive algorithms such as simulated annealing and genetic algorithms.
Antoine, Xavier; Levitt, Antoine; Tang, Qinglin
2017-08-01
We propose a preconditioned nonlinear conjugate gradient method coupled with a spectral spatial discretization scheme for computing the ground states (GS) of rotating Bose-Einstein condensates (BEC), modeled by the Gross-Pitaevskii Equation (GPE). We first start by reviewing the classical gradient flow (also known as imaginary time (IMT)) method which considers the problem from the PDE standpoint, leading to numerically solve a dissipative equation. Based on this IMT equation, we analyze the forward Euler (FE), Crank-Nicolson (CN) and the classical backward Euler (BE) schemes for linear problems and recognize classical power iterations, allowing us to derive convergence rates. By considering the alternative point of view of minimization problems, we propose the preconditioned steepest descent (PSD) and conjugate gradient (PCG) methods for the GS computation of the GPE. We investigate the choice of the preconditioner, which plays a key role in the acceleration of the convergence process. The performance of the new algorithms is tested in 1D, 2D and 3D. We conclude that the PCG method outperforms all the previous methods, most particularly for 2D and 3D fast rotating BECs, while being simple to implement.
A gradient activation method for direct methanol fuel cells
International Nuclear Information System (INIS)
Liu, Guicheng; Yang, Zhaoyi; Halim, Martin; Li, Xinyang; Wang, Manxiang; Kim, Ji Young; Mei, Qiwen; Wang, Xindong; Lee, Joong Kee
2017-01-01
Highlights: • A gradient activation method was reported firstly for direct methanol fuel cells. • The activity recovery of Pt-based catalyst was introduced into the novel activation process. • The new activation method led to prominent enhancement of DMFC performance. • DMFC performance was improved with the novel activation step by step within 7.5 h. - Abstract: To realize gradient activation effect and recover catalytic activity of catalyst in a short time, a gradient activation method has firstly been proposed for enhancing discharge performance and perfecting activation mechanism of the direct methanol fuel cell (DMFC). This method includes four steps, i.e. proton activation, activity recovery activation, H_2-O_2 mode activation and forced discharging activation. The results prove that the proposed method has gradually realized replenishment of water and protons, recovery of catalytic activity of catalyst, establishment of transfer channels for electrons, protons, and oxygen, and optimization of anode catalyst layer for methanol transfer in turn. Along with the novel activation process going on, the DMFC discharge performance has been improved, step by step, to more than 1.9 times higher than that of the original one within 7.5 h. This method provides a practicable activation way for the real application of single DMFCs and stacks.
Application of Conjugate Gradient methods to tidal simulation
Barragy, E.; Carey, G.F.; Walters, R.A.
1993-01-01
A harmonic decomposition technique is applied to the shallow water equations to yield a complex, nonsymmetric, nonlinear, Helmholtz type problem for the sea surface and an accompanying complex, nonlinear diagonal problem for the velocities. The equation for the sea surface is linearized using successive approximation and then discretized with linear, triangular finite elements. The study focuses on applying iterative methods to solve the resulting complex linear systems. The comparative evaluation includes both standard iterative methods for the real subsystems and complex versions of the well known Bi-Conjugate Gradient and Bi-Conjugate Gradient Squared methods. Several Incomplete LU type preconditioners are discussed, and the effects of node ordering, rejection strategy, domain geometry and Coriolis parameter (affecting asymmetry) are investigated. Implementation details for the complex case are discussed. Performance studies are presented and comparisons made with a frontal solver. ?? 1993.
Moving force identification based on modified preconditioned conjugate gradient method
Chen, Zhen; Chan, Tommy H. T.; Nguyen, Andy
2018-06-01
This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.
Sobolev gradients and differential equations
Neuberger, J W
2010-01-01
A Sobolev gradient of a real-valued functional on a Hilbert space is a gradient of that functional taken relative to an underlying Sobolev norm. This book shows how descent methods using such gradients allow a unified treatment of a wide variety of problems in differential equations. For discrete versions of partial differential equations, corresponding Sobolev gradients are seen to be vastly more efficient than ordinary gradients. In fact, descent methods with these gradients generally scale linearly with the number of grid points, in sharp contrast with the use of ordinary gradients. Aside from the first edition of this work, this is the only known account of Sobolev gradients in book form. Most of the applications in this book have emerged since the first edition was published some twelve years ago. What remains of the first edition has been extensively revised. There are a number of plots of results from calculations and a sample MatLab code is included for a simple problem. Those working through a fair p...
Gadolinium burnable absorber optimization by the method of conjugate gradients
International Nuclear Information System (INIS)
Drumm, C.R.; Lee, J.C.
1987-01-01
The optimal axial distribution of gadolinium burnable poison in a pressurized water reactor is determined to yield an improved power distribution. The optimization scheme is based on Pontryagin's maximum principle, with the objective function accounting for a target power distribution. The conjugate gradients optimization method is used to solve the resulting Euler-Lagrange equations iteratively, efficiently handling the high degree of nonlinearity of the problem
Conjugate descent formulation of backpropagation error in ...
African Journals Online (AJOL)
The feedforward neural network architecture uses backpropagation learning to determine optimal weights between dierent interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to ...
Using nuclear methods for analyzing materials and determining concentration gradients
International Nuclear Information System (INIS)
Darras, R.
After reviewing the various type of nuclear chemical analysis methods, the possibilities of analysis by activation and direct observation of nuclear reactions are specifically described. These methods make it possible to effect analyses of trace-elements or impurities, even as traces, in materials, with selectivity, accuracy and great sensitivity. This latter property makes them advantageous too for determining major elements in small quantities of available matter. Furthermore, they lend themselves to carrying out superficial analyses and the determination of concentration gradients, given the careful choice of the nature and energy of the incident particles. The paper is illustrated with typical examples of analyses on steels, pure iron, refractory metals, etc [fr
Conjugate descent formulation of backpropagation error in feedforward neural networks
Directory of Open Access Journals (Sweden)
NK Sharma
2009-06-01
Full Text Available The feedforward neural network architecture uses backpropagation learning to determine optimal weights between different interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to minimise the error function for a given set of patterns, by adjusting the weights of the network. The first derivates of the error with respect to the weights identify the local error surface in the descent direction. Hence the network exhibits a different local error surface for every different pattern presented to it, and weights are iteratively modified in order to minimise the current local error. The determination of an optimal weight vector is possible only when the total minimum error (mean of the minimum local errors for all patterns from the training set may be minimised. In this paper, we present a general mathematical formulation for the second derivative of the error function with respect to the weights (which represents a conjugate descent for arbitrary feedforward neural network topologies, and we use this derivative information to obtain the optimal weight vector. The local error is backpropagated among the units of hidden layers via the second order derivative of the error with respect to the weights of the hidden and output layers independently and also in combination. The new total minimum error point may be evaluated with the help of the current total minimum error and the current minimised local error. The weight modification processes is performed twice: once with respect to the present local error and once more with respect to the current total or mean error. We present some numerical evidence that our proposed method yields better network weights than those determined via a conventional gradient descent approach.
Random versus Deterministic Descent in RNA Energy Landscape Analysis
Directory of Open Access Journals (Sweden)
Luke Day
2016-01-01
Full Text Available Identifying sets of metastable conformations is a major research topic in RNA energy landscape analysis, and recently several methods have been proposed for finding local minima in landscapes spawned by RNA secondary structures. An important and time-critical component of such methods is steepest, or gradient, descent in attraction basins of local minima. We analyse the speed-up achievable by randomised descent in attraction basins in the context of large sample sets where the size has an order of magnitude in the region of ~106. While the gain for each individual sample might be marginal, the overall run-time improvement can be significant. Moreover, for the two nongradient methods we analysed for partial energy landscapes induced by ten different RNA sequences, we obtained that the number of observed local minima is on average larger by 7.3% and 3.5%, respectively. The run-time improvement is approximately 16.6% and 6.8% on average over the ten partial energy landscapes. For the large sample size we selected for descent procedures, the coverage of local minima is very high up to energy values of the region where the samples were randomly selected from the partial energy landscapes; that is, the difference to the total set of local minima is mainly due to the upper area of the energy landscapes.
Gradient augmented level set method for phase change simulations
Anumolu, Lakshman; Trujillo, Mario F.
2018-01-01
A numerical method for the simulation of two-phase flow with phase change based on the Gradient-Augmented-Level-set (GALS) strategy is presented. Sharp capturing of the vaporization process is enabled by: i) identification of the vapor-liquid interface, Γ (t), at the subgrid level, ii) discontinuous treatment of thermal physical properties (except for μ), and iii) enforcement of mass, momentum, and energy jump conditions, where the gradients of the dependent variables are obtained at Γ (t) and are consistent with their analytical expression, i.e. no local averaging is applied. Treatment of the jump in velocity and pressure at Γ (t) is achieved using the Ghost Fluid Method. The solution of the energy equation employs the sub-grid knowledge of Γ (t) to discretize the temperature Laplacian using second-order one-sided differences, i.e. the numerical stencil completely resides within each respective phase. To carefully evaluate the benefits or disadvantages of the GALS approach, the standard level set method is implemented and compared against the GALS predictions. The results show the expected trend that interface identification and transport are predicted noticeably better with GALS over the standard level set. This benefit carries over to the prediction of the Laplacian and temperature gradients in the neighborhood of the interface, which are directly linked to the calculation of the vaporization rate. However, when combining the calculation of interface transport and reinitialization with two-phase momentum and energy, the benefits of GALS are to some extent neutralized, and the causes for this behavior are identified and analyzed. Overall the additional computational costs associated with GALS are almost the same as those using the standard level set technique.
Program generator for the Incomplete Cholesky Conjugate Gradient (ICCG) method
International Nuclear Information System (INIS)
Kuo-Petravic, G.; Petravic, M.
1978-04-01
The Incomplete Cholesky Conjugate Gradient (ICCG) method has been found very effective for the solution of sparse systems of linear equations. Its implementation on a computer, however, requires a considerable amount of careful coding to achieve good machine efficiency. Furthermore, the resulting code is necessarily inflexible and cannot be easily adapted to different problems. We present in this paper a code generator GENIC which, given a small amount of information concerning the sparsity pattern and size of the system of equations, generates a solver package. This package, called SOLIC, is tailor made for a particular problem and can be easily incorporated into any user program
Total variation superiorized conjugate gradient method for image reconstruction
Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.
2018-03-01
The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise; due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Non-linear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG); one of its input parameters is a positive number ɛ. It is proved that, for any given ɛ that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ɛ. Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value ɛ of the half-squared residual.
Acceleration of monte Carlo solution by conjugate gradient method
International Nuclear Information System (INIS)
Toshihisa, Yamamoto
2005-01-01
The conjugate gradient method (CG) was applied to accelerate Monte Carlo solutions in fixed source problems. The equilibrium model based formulation enables to use CG scheme as well as initial guess to maximize computational performance. This method is available to arbitrary geometry provided that the neutron source distribution in each subregion can be regarded as flat. Even if it is not the case, the method can still be used as a powerful tool to provide an initial guess very close to the converged solution. The major difference of Monte Carlo CG to deterministic CG is that residual error is estimated using Monte Carlo sampling, thus statistical error exists in the residual. This leads to a flow diagram specific to Monte Carlo-CG. Three pre-conditioners were proposed for CG scheme and the performance was compared with a simple 1-D slab heterogeneous test problem. One of them, Sparse-M option, showed an excellent performance in convergence. The performance per unit cost was improved by four times in the test problem. Although direct estimation of efficiency of the method is impossible mainly because of the strong problem-dependence of the optimized pre-conditioner in CG, the method seems to have efficient potential as a fast solution algorithm for Monte Carlo calculations. (author)
Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method
Directory of Open Access Journals (Sweden)
Wei Xue
2016-08-01
Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.
Aerodynamic shape optimization using preconditioned conjugate gradient methods
Burgreen, Greg W.; Baysal, Oktay
1993-01-01
In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.
Santos Basin Geological Structures Mapped by Cross-gradient Method
Jilinski, P.; Fontes, S. L.
2011-12-01
Introduction We mapped regional-scale geological structures localized in offshore zone Santos Basin, South-East Brazilian Coast. The region is dominated by transition zone from oceanic to continental crust. Our objective was to determine the imprint of deeper crustal structures from correlation between bathymetric, gravity and magnetic anomaly maps. The region is extensively studied for oil and gas deposits including large tectonic sub-salt traps. Our method is based on gradient directions and their magnitudes product. We calculate angular differences and cross-product and access correlation between properties and map structures. Theory and Method We used angular differences and cross-product to determine correlated region between bathymetric, free-air gravity and magnetic anomaly maps. This gradient based method focuses on borders of anomalies and uses its morphological properties to access correlation between their sources. We generated maps of angles and cross-product distribution to locate correlated regions. Regional scale potential fields maps of FA and MA are a reflection of the overlaying and overlapping effects of the adjacent structures. Our interest was in quantifying and characterizing the relation between shapes of magnetic anomalies and gravity anomalies. Results Resulting maps show strong correlation between bathymetry and gravity anomaly and bathymetry and magnetic anomaly for large strictures including Serra do Mar, shelf, continental slope and rise. All maps display the regional dominance of NE-SW geological structures alignment parallel to the shore. Special interest is presented by structures transgressing this tendency. Magnetic, gravity anomaly and bathymetry angles map show large correlated region over the shelf zone and smaller scale NE-SW banded structures over abyssal plane. From our interpretation the large band of inverse correlation adjacent to the shore is generated by the gravity effect of Serra do Mar. Disrupting structures including
The 15th and last section of the CMS detector was lowered on Tuesday 22 January. The YE-1 endcap (1430 tonnes) began its 100-metre descent at 7 am and arrived gently on the floor of the experiment hall at 5.30 pm.
Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn
2007-01-01
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.
Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael
2018-06-01
To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric
Directory of Open Access Journals (Sweden)
Andreea Koreanschi
2017-02-01
Full Text Available In this paper, an ‘in-house’ genetic algorithm is described and applied to an optimization problem for improving the aerodynamic performances of an aircraft wing tip through upper surface morphing. The algorithm’s performances were studied from the convergence point of view, in accordance with design conditions. The algorithm was compared to two other optimization methods, namely the artificial bee colony and a gradient method, for two optimization objectives, and the results of the optimizations with each of the three methods were plotted on response surfaces obtained with the Monte Carlo method, to show that they were situated in the global optimum region. The optimization results for 16 wind tunnel test cases and 2 objective functions were presented. The 16 cases used for the optimizations were included in the experimental test plan for the morphing wing-tip demonstrator, and the results obtained using the displacements given by the optimizations were evaluated.
Preconditioned Conjugate Gradient methods for low speed flow calculations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1993-01-01
An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations are integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and the convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the lower-upper (L-U)-successive symmetric over-relaxation iterative scheme is more efficient than a preconditioner based on incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional line Gauss-Seidel relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.
The ﬁrst endcap disc of CMS being lowered slowly and carefully 100 m underground into the experimental cavern. The disc is one of 15 large pieces to make the grand descent. The uniquely shaped slice, 16 m high, about 50 cm thick weighs 400 tonnes. The two HF that were lowered earlier in November can also be seen in the foreground and background.
Dictionary descent in optimization
Temlyakov, Vladimir
2015-01-01
The problem of convex optimization is studied. Usually in convex optimization the minimization is over a d-dimensional domain. Very often the convergence rate of an optimization algorithm depends on the dimension d. The algorithms studied in this paper utilize dictionaries instead of a canonical basis used in the coordinate descent algorithms. We show how this approach allows us to reduce dimensionality of the problem. Also, we investigate which properties of a dictionary are beneficial for t...
With precise coordination YE+1 was lowered into the cavern (9-Jan), soon joined by the ?rst barrel wheel YB+2 (19-Jan), then YB+1(4-Feb) and HB+ (13-Feb). The 1920 ton central barrel wheel YB0 rests brie?y on the pit-head cover in anticipation of a monumental descent (28-Feb) that will also trigger an intense campaign of installation of services and detectors underground.
Accurate reanalysis of structures by a preconditioned conjugate gradient method
Czech Academy of Sciences Publication Activity Database
Kirsch, U.; Kočvara, Michal; Zowe, J.
2002-01-01
Roč. 55, č. 2 (2002), s. 233-251 ISSN 0029-5981 R&D Projects: GA AV ČR IAA1075005 Grant - others:BMBF(DE) 03ZOM3ER Institutional research plan: CEZ:AV0Z1075907 Keywords : preconditioned conjugate gradient s * structural reanalysis Subject RIV: BA - General Mathematics Impact factor: 1.468, year: 2002
International Nuclear Information System (INIS)
Chen, G.S.
1997-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used. TFQMR (transpose free quasi-minimal residual algorithm), CGS (conjuage gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These sub-routines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. (author)
Ledoux, L.A.F.; Berkhoff, Arthur P.; Thijssen, J.M.
The Conjugate Gradient Rayleigh method for the calculation of acoustic reflection and transmission at a rough interface between two media was experimentally verified. The method is based on a continuous version of the conjugate gradient technique and plane-wave expansions. We measured the beam
Weighted graph based ordering techniques for preconditioned conjugate gradient methods
Clift, Simon S.; Tang, Wei-Pai
1994-01-01
We describe the basis of a matrix ordering heuristic for improving the incomplete factorization used in preconditioned conjugate gradient techniques applied to anisotropic PDE's. Several new matrix ordering techniques, derived from well-known algorithms in combinatorial graph theory, which attempt to implement this heuristic, are described. These ordering techniques are tested against a number of matrices arising from linear anisotropic PDE's, and compared with other matrix ordering techniques. A variation of RCM is shown to generally improve the quality of incomplete factorization preconditioners.
Application of the conjugate-gradient method to ground-water models
Manteuffel, T.A.; Grove, D.B.; Konikow, Leonard F.
1984-01-01
The conjugate-gradient method can solve efficiently and accurately finite-difference approximations to the ground-water flow equation. An aquifer-simulation model using the conjugate-gradient method was applied to a problem of ground-water flow in an alluvial aquifer at the Rocky Mountain Arsenal, Denver, Colorado. For this application, the accuracy and efficiency of the conjugate-gradient method compared favorably with other available methods for steady-state flow. However, its efficiency relative to other available methods depends on the nature of the specific problem. The main advantage of the conjugate-gradient method is that it does not require the use of iteration parameters, thereby eliminating this partly subjective procedure. (USGS)
Terrain reconstruction based on descent images for the Chang’e III landing area
Directory of Open Access Journals (Sweden)
Xu Xinchao
2015-10-01
Full Text Available A new method that combined image matching and shape from shading for terrain reconstruction was proposed to solve the lack of terrain in the landing area of Chang'e III. First, the reflection equation was established based on the Lommel– Seeliger reflection model. After edge extraction, the gradients of points on the edge were solved. The normal vectors of adjacent points were obtained using the smoothness constraint. Furthermore, the gradients of residual points in the image were determined through evolution. The inadequacy of the reflection equation was eliminated by considering the gradient as the constraint of the reflection equation. The normal vector of each point could be obtained by solving the reflection equation. The terrain without coordinate information was reconstructed by iterating the vector field. After using scaleinvariant feature transform to extract matching points in the descent images, the terrain was converted to a lander centroid coordinate system. Experiments were carried out with MATLAB-simulated images, laboratory images, and descent images of Chang'e III. Results show that the proposed method performs better than the classical SFS algorithm. The new method can provide reference for other deep space exploration activities.
A Gauss-Newton method for the integration of spatial normal fields in shape Space
Balzer, Jonathan
2011-01-01
to solving a nonlinear least-squares problem in shape space. Previously, the corresponding minimization has been performed by gradient descent, which suffers from slow convergence and susceptibility to local minima. Newton-type methods, although significantly
International Nuclear Information System (INIS)
Kowsary, F.; Pooladvand, K.; Pourshaghaghy, A.
2007-01-01
In this paper, an appropriate distribution of the heating elements' strengths in a radiation furnace is estimated using inverse methods so that a pre-specified temperature and heat flux distribution is attained on the design surface. Minimization of the sum of the squares of the error function is performed using the variable metric method (VMM), and the results are compared with those obtained by the conjugate gradient method (CGM) established previously in the literature. It is shown via test cases and a well-founded validation procedure that the VMM, when using a 'regularized' estimator, is more accurate and is able to reach at a higher quality final solution as compared to the CGM. The test cases used in this study were two-dimensional furnaces filled with an absorbing, emitting, and scattering gas
On the solution of the Hartree-Fock-Bogoliubov equations by the conjugate gradient method
International Nuclear Information System (INIS)
Egido, J.L.; Robledo, L.M.
1995-01-01
The conjugate gradient method is formulated in the Hilbert space for density and non-density dependent Hamiltonians. We apply it to the solution of the Hartree-Fock-Bogoliubov equations with constraints. As a numerical application we show calculations with the finite range density dependent Gogny force. The number of iterations required to reach convergence is reduced by a factor of three to four as compared with the standard gradient method. (orig.)
PHASE GRADIENT METHOD OF MAGNETIC FIELD MEASUREMENTS IN ELECTRIC VEHICLES
Directory of Open Access Journals (Sweden)
N. G. Ptitsyna
2013-01-01
Full Text Available Operation of electric and hybrid vehicles demands real time magnetic field control, for instance, for fire and electromagnetic safety. The article deals with a method of magnetic field measurements onboard electric cars taking into account peculiar features of these fields. The method is based on differential methods of measurements, and minimizes the quantity of magnetic sensors.
Blockwise conjugate gradient methods for image reconstruction in volumetric CT.
Qiu, W; Titley-Peloquin, D; Soleimani, M
2012-11-01
Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
PRECONDITIONED BI-CONJUGATE GRADIENT METHOD FOR RADIATIVE TRANSFER IN SPHERICAL MEDIA
International Nuclear Information System (INIS)
Anusha, L. S.; Nagendra, K. N.; Paletou, F.; Leger, L.
2009-01-01
A robust numerical method called the Preconditioned Bi-Conjugate Gradient (Pre-BiCG) method is proposed for the solution of the radiative transfer equation in spherical geometry. A variant of this method called Stabilized Preconditioned Bi-Conjugate Gradient (Pre-BiCG-STAB) is also presented. These are iterative methods based on the construction of a set of bi-orthogonal vectors. The application of the Pre-BiCG method in some benchmark tests shows that the method is quite versatile, and can handle difficult problems that may arise in astrophysical radiative transfer theory.
International Nuclear Information System (INIS)
Chen, G.S.; Yang, D.Y.
1998-01-01
We apply and compare the preconditioned generalized conjugate gradient methods to solve the linear system equation that arises in the two-dimensional neutron and photon transport equation in this paper. Several subroutines are developed on the basis of preconditioned generalized conjugate gradient methods for time-independent, two-dimensional neutron and photon transport equation in the transport theory. These generalized conjugate gradient methods are used: TFQMR (transpose free quasi-minimal residual algorithm) CGS (conjugate gradient square algorithm), Bi-CGSTAB (bi-conjugate gradient stabilized algorithm) and QMRCGSTAB (quasi-minimal residual variant of bi-conjugate gradient stabilized algorithm). These subroutines are connected to computer program DORT. Several problems are tested on a personal computer with Intel Pentium CPU. The reasons to choose the generalized conjugate gradient methods are that the methods have better residual (equivalent to error) control procedures in the computation and have better convergent rate. The pointwise incomplete LU factorization ILU, modified pointwise incomplete LU factorization MILU, block incomplete factorization BILU and modified blockwise incomplete LU factorization MBILU are the preconditioning techniques used in the several testing problems. In Bi-CGSTAB, CGS, TFQMR and QMRCGSTAB method, we find that either CGS or Bi-CGSTAB method combined with preconditioner MBILU is the most efficient algorithm in these methods in the several testing problems. The numerical solution of flux by preconditioned CGS and Bi-CGSTAB methods has the same result as those from Cray computer, obtained by either the point successive relaxation method or the line successive relaxation method combined with Gaussian elimination
A Projected Conjugate Gradient Method for Sparse Minimax Problems
DEFF Research Database (Denmark)
Madsen, Kaj; Jonasson, Kristjan
1993-01-01
A new method for nonlinear minimax problems is presented. The method is of the trust region type and based on sequential linear programming. It is a first order method that only uses first derivatives and does not approximate Hessians. The new method is well suited for large sparse problems...... as it only requires that software for sparse linear programming and a sparse symmetric positive definite equation solver are available. On each iteration a special linear/quadratic model of the function is minimized, but contrary to the usual practice in trust region methods the quadratic model is only...... with the method are presented. In fact, we find that the number of iterations required is comparable to that of state-of-the-art quasi-Newton codes....
Hybridization of the probability perturbation method with gradient information
DEFF Research Database (Denmark)
Johansen, Kent; Caers, J.; Suzuki, S.
2007-01-01
Geostatistically based history-matching methods make it possible to devise history-matching strategies that will honor geologic knowledge about the reservoir. However, the performance of these methods is known to be impeded by slow convergence rates resulting from the stochastic nature of the alg...
A conjugate gradient method for the spectral partitioning of graphs
Kruyt, Nicolaas P.
1997-01-01
The partitioning of graphs is a frequently occurring problem in science and engineering. The spectral graph partitioning method is a promising heuristic method for this class of problems. Its main disadvantage is the large computing time required to solve a special eigenproblem. Here a simple and
Conjugate Gradient like methods and their application to fixed source neutron diffusion problems
International Nuclear Information System (INIS)
Suetomi, Eiichi; Sekimoto, Hiroshi
1989-01-01
This paper presents a number of fast iterative methods for solving systems of linear equations appearing in fixed source problems for neutron diffusion. We employed the conjugate gradient and conjugate residual methods. In order to accelerate the conjugate residual method, we proposed the conjugate residual squared method by transforming the residual polynomial of the conjugate residual method. Since the convergence of these methods depends on the spectrum of coefficient matrix, we employed the incomplete Choleski (IC) factorization and the modified IC (MIC) factorization as preconditioners. These methods were applied to some neutron diffusion problems and compared with the successive overrelaxation (SOR) method. The results of these numerical experiments showed superior convergence characteristics of the conjugate gradient like method with MIC factorization to the SOR method, especially for a problem involving void region. The CPU time of the MICCG, MICCR and MICCRS methods showed no great difference. In order to vectorize the conjugate gradient like methods based on (M)IC factorization, the hyperplane method was used and implemented on the vector computers, the HITAC S-820/80 and ETA10-E (one processor mode). Significant decrease of the CPU times was observed on the S-820/80. Since the scaled conjugate gradient (SCG) method can be vectorized with no manipulation, it was also compared with the above methods. It turned out the SCG method was the fastest with respect to the CPU times on the ETA10-E. These results suggest that one should implement suitable algorithm for different vector computers. (author)
A gradient-based method for segmenting FDG-PET images: methodology and validation
International Nuclear Information System (INIS)
Geets, Xavier; Lee, John A.; Gregoire, Vincent; Bol, Anne; Lonneux, Max
2007-01-01
A new gradient-based method for segmenting FDG-PET images is described and validated. The proposed method relies on the watershed transform and hierarchical cluster analysis. To allow a better estimation of the gradient intensity, iteratively reconstructed images were first denoised and deblurred with an edge-preserving filter and a constrained iterative deconvolution algorithm. Validation was first performed on computer-generated 3D phantoms containing spheres, then on a real cylindrical Lucite phantom containing spheres of different volumes ranging from 2.1 to 92.9 ml. Moreover, laryngeal tumours from seven patients were segmented on PET images acquired before laryngectomy by the gradient-based method and the thresholding method based on the source-to-background ratio developed by Daisne (Radiother Oncol 2003;69:247-50). For the spheres, the calculated volumes and radii were compared with the known values; for laryngeal tumours, the volumes were compared with the macroscopic specimens. Volume mismatches were also analysed. On computer-generated phantoms, the deconvolution algorithm decreased the mis-estimate of volumes and radii. For the Lucite phantom, the gradient-based method led to a slight underestimation of sphere volumes (by 10-20%), corresponding to negligible radius differences (0.5-1.1 mm); for laryngeal tumours, the segmented volumes by the gradient-based method agreed with those delineated on the macroscopic specimens, whereas the threshold-based method overestimated the true volume by 68% (p = 0.014). Lastly, macroscopic laryngeal specimens were totally encompassed by neither the threshold-based nor the gradient-based volumes. The gradient-based segmentation method applied on denoised and deblurred images proved to be more accurate than the source-to-background ratio method. (orig.)
Methods for Fabricating Gradient Alloy Articles with Multi-Functional Properties
Hofmann, Douglas C. (Inventor); Borgonia, John Paul C. (Inventor); Dillon, Robert P. (Inventor); Suh, Eric J. (Inventor); Mulder, Jerry L. (Inventor); Gardner, Paul B. (Inventor)
2015-01-01
Systems and methods for fabricating multi-functional articles comprised of additively formed gradient materials are provided. The fabrication of multi-functional articles using the additive deposition of gradient alloys represents a paradigm shift from the traditional way that metal alloys and metal/metal alloy parts are fabricated. Since a gradient alloy that transitions from one metal to a different metal cannot be fabricated through any conventional metallurgy techniques, the technique presents many applications. Moreover, the embodiments described identify a broad range of properties and applications.
Application of conjugate gradient method to Commix-1B three-dimensional momentum equation
International Nuclear Information System (INIS)
King, J.B.; Domanus, H.
1987-01-01
Conjugate gradient method which is a special case of the variational method was implemented in the momentum section of the COMMIX-1B thermal hydraulics code. The comparisons between this method and the conventional iterative method of Successive Over Relation (S.O.R.) were made. Using COMMIX-1B, three steady state problems were analyzed. These problems were flow distribution in a scaled model of the Clinch River Fast Breeder Reactor outlet plenum, flow of coolant in the cold leg and downcomer of a PWR and isothermal air flow through a partially blocked pipe. It was found that if the conjugate gradient method is used, the execution time required to solve the resulting COMMIX-1B system of equations can be reduced by a factor of about 2 for the first two problems. For the isothermal air flow problem, the conjugate gradient method did not improve the execution time
Two-level preconditioned conjugate gradient methods with applications to bubbly flow problems
Tang, J.M.
2008-01-01
The Preconditioned Conjugate Gradient (PCG) method is one of the most popular iterative methods for solving large linear systems with a symmetric and positive semi-definite coefficient matrix. However, if the preconditioned coefficient matrix is ill-conditioned, the convergence of the PCG method
Analysis and performance estimation of the Conjugate Gradient method on multiple GPUs
Verschoor, M.; Jalba, A.C.
2012-01-01
The Conjugate Gradient (CG) method is a widely-used iterative method for solving linear systems described by a (sparse) matrix. The method requires a large amount of Sparse-Matrix Vector (SpMV) multiplications, vector reductions and other vector operations to be performed. We present a number of
International Nuclear Information System (INIS)
Roidl, B.; Meinke, M.; Schröder, W.
2014-01-01
Highlights: • Reformulated synthetic turbulence generation method (RSTGM) is applied. • Zonal RANS-LES method is applied to boundary layers at pressure gradients. • Good agreement with the pure LES and other reference data is obtained. • The RSTGM is applicable to pressure gradient flows without modification. • RANS-to-LES boundary should be located where -1·10 6 6 is satisfied. -- Abstract: The reformulated synthetic turbulence generation (RSTG) method is used to compute by a fully coupled zonal RANS-LES approach turbulent non-zero-pressure gradient boundary layers. The quality of the RSTG method, which is based on the same shape functions and length scale distributions as in zero-pressure gradient flow, is discussed by comparing the zonal RANS-LES findings with pure LES, pure RANS, direct numerical simulation (DNS), and experimental data. For the favorable pressure gradient (FPG) simulation the RANS-to-LES transition occurs in the accelerated flow region and for the adverse pressure gradient (APG) case it is located in the decelerated flow region. The results of the time and spanwise averaged skin-friction distributions, velocity profiles, and Reynolds stress distributions of the zonal RANS-LES simulation show a satisfactory to good agreement with the pure LES, reference DNS, and experimental data. The quality of the findings shows that the rigorous formulation of the synthetic turbulence generation makes the RSTG method applicable without a priori knowledge of the flow properties but those determined by the RANS solution and without using additional control planes to regulate the shear stress budget to a wide range of Reynolds numbers and pressure gradients. The method is a promising approach to formulate embedded RANS-to-LES boundaries in flow regions where the Pohlhausen or acceleration parameter satisfies -1·10 -6 ⩽K⩽2·10 -6
A finite element conjugate gradient FFT method for scattering
Collins, Jeffery D.; Ross, Dan; Jin, J.-M.; Chatterjee, A.; Volakis, John L.
1991-01-01
Validated results are presented for the new 3D body of revolution finite element boundary integral code. A Fourier series expansion of the vector electric and mangnetic fields is employed to reduce the dimensionality of the system, and the exact boundary condition is employed to terminate the finite element mesh. The mesh termination boundary is chosen such that is leads to convolutional boundary operatores of low O(n) memory demand. Improvements of this code are discussed along with the proposed formulation for a full 3D implementation of the finite element boundary integral method in conjunction with a conjugate gradiant fast Fourier transformation (CGFFT) solution.
A nonsmooth nonlinear conjugate gradient method for interactive contact force problems
DEFF Research Database (Denmark)
Silcowitz, Morten; Abel, Sarah Maria Niebe; Erleben, Kenny
2010-01-01
of a nonlinear complementarity problem (NCP), which can be solved using an iterative splitting method, such as the projected Gauss–Seidel (PGS) method. We present a novel method for solving the NCP problem by applying a Fletcher–Reeves type nonlinear nonsmooth conjugate gradient (NNCG) type method. We analyze...... and present experimental convergence behavior and properties of the new method. Our results show that the NNCG method has at least the same convergence rate as PGS, and in many cases better....
Zhou, J.; Danilov, D.; Notten, P.H.L.
2006-01-01
An electrochemical method has been developed for the in situ determination of concentration gradients in the electrolyte of sealed Li-ion batteries by measuring the potential difference between microreference electrodes. Formulas relating the concentration gradient and the potential difference
Comparison of gradient methods for gain tuning of a PD controller applied on a quadrotor system
Kim, Jinho; Wilkerson, Stephen A.; Gadsden, S. Andrew
2016-05-01
Many mechanical and electrical systems have utilized the proportional-integral-derivative (PID) control strategy. The concept of PID control is a classical approach but it is easy to implement and yields a very good tracking performance. Unmanned aerial vehicles (UAVs) are currently experiencing a significant growth in popularity. Due to the advantages of PID controllers, UAVs are implementing PID controllers for improved stability and performance. An important consideration for the system is the selection of PID gain values in order to achieve a safe flight and successful mission. There are a number of different algorithms that can be used for real-time tuning of gains. This paper presents two algorithms for gain tuning, and are based on the method of steepest descent and Newton's minimization of an objective function. This paper compares the results of applying these two gain tuning algorithms in conjunction with a PD controller on a quadrotor system.
HNO3 fluxes to a deciduous forest derived using gradient and REA methods
DEFF Research Database (Denmark)
Pryor, S.C.; Barthelmie, R.J.; Jensen, B.
2002-01-01
Summertime nitric acid concentrations over a deciduous forest in the midwestern United States are reported, which range between 0.36 and 3.3 mug m(-3). Fluxes to the forest are computed using the relaxed eddy accumulation technique and gradient methods. In accord with previous studies, the results...... indicate substantial uncertainties in the gradient-based calculations. The relaxed eddy accumulation (REA) derived fluxes are physically reasonable and are shown to be of similar magnitude to dry deposition estimates from gradient sampling. The REA derived mean deposition velocity is approximately 3 cm s......(-1), which is also comparable to growing season estimates derived by Meyers et al. for a similar deciduous forest. Occasional inverted concentration gradients and fluxes are observed but most are not statistically significant. Data are also presented that indicate substantial through canopy...
Preconditioned conjugate gradient methods for the Navier-Stokes equations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1994-01-01
A preconditioned Krylov subspace method (GMRES) is used to solve the linear systems of equations formed at each time-integration step of the unsteady, two-dimensional, compressible Navier-Stokes equations of fluid flow. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux-split formulation. Several preconditioning techniques are investigated to enhance the efficiency and convergence rate of the implicit solver based on the GMRES algorithm. The superiority of the new solver is established by comparisons with a conventional implicit solver, namely line Gauss-Seidel relaxation (LGSR). Computational test results for low-speed (incompressible flow over a backward-facing step at Mach 0.1), transonic flow (trailing edge flow in a transonic turbine cascade), and hypersonic flow (shock-on-shock interactions on a cylindrical leading edge at Mach 6.0) are presented. For the Mach 0.1 case, overall speedup factors of up to 17 (in terms of time-steps) and 15 (in terms of CPU time on a CRAY-YMP/8) are found in favor of the preconditioned GMRES solver, when compared with the LGSR solver. The corresponding speedup factors for the transonic flow case are 17 and 23, respectively. The hypersonic flow case shows slightly lower speedup factors of 9 and 13, respectively. The study of preconditioners conducted in this research reveals that a new LUSGS-type preconditioner is much more efficient than a conventional incomplete LU-type preconditioner.
Boundedness and convergence of online gradient method with penalty for feedforward neural networks.
Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen
2009-06-01
In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.
Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization
International Nuclear Information System (INIS)
Xiao Yunhai; Hu Qingjie
2008-01-01
An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection
Vasil'ev, V. I.; Kardashevsky, A. M.; Popov, V. V.; Prokopev, G. A.
2017-10-01
This article presents results of computational experiment carried out using a finite-difference method for solving the inverse Cauchy problem for a two-dimensional elliptic equation. The computational algorithm involves an iterative determination of the missing boundary condition from the override condition using the conjugate gradient method. The results of calculations are carried out on the examples with exact solutions as well as at specifying an additional condition with random errors are presented. Results showed a high efficiency of the iterative method of conjugate gradients for numerical solution
Syrakos, Alexandros; Varchanis, Stylianos; Dimakopoulos, Yannis; Goulas, Apostolos; Tsamopoulos, John
2017-12-01
Finite volume methods (FVMs) constitute a popular class of methods for the numerical simulation of fluid flows. Among the various components of these methods, the discretisation of the gradient operator has received less attention despite its fundamental importance with regards to the accuracy of the FVM. The most popular gradient schemes are the divergence theorem (DT) (or Green-Gauss) scheme and the least-squares (LS) scheme. Both are widely believed to be second-order accurate, but the present study shows that in fact the common variant of the DT gradient is second-order accurate only on structured meshes whereas it is zeroth-order accurate on general unstructured meshes, and the LS gradient is second-order and first-order accurate, respectively. This is explained through a theoretical analysis and is confirmed by numerical tests. The schemes are then used within a FVM to solve a simple diffusion equation on unstructured grids generated by several methods; the results reveal that the zeroth-order accuracy of the DT gradient is inherited by the FVM as a whole, and the discretisation error does not decrease with grid refinement. On the other hand, use of the LS gradient leads to second-order accurate results, as does the use of alternative, consistent, DT gradient schemes, including a new iterative scheme that makes the common DT gradient consistent at almost no extra cost. The numerical tests are performed using both an in-house code and the popular public domain partial differential equation solver OpenFOAM.
Accelerated gradient methods for total-variation-based CT image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Joergensen, Jakob H.; Hansen, Per Christian [Technical Univ. of Denmark, Lyngby (Denmark). Dept. of Informatics and Mathematical Modeling; Jensen, Tobias L.; Jensen, Soeren H. [Aalborg Univ. (Denmark). Dept. of Electronic Systems; Sidky, Emil Y.; Pan, Xiaochuan [Chicago Univ., Chicago, IL (United States). Dept. of Radiology
2011-07-01
Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-intensive methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits prohibitively slow convergence. In the present work we address the question of how to reduce the number of gradient method iterations needed to achieve a high-accuracy TV reconstruction. We consider the use of two accelerated gradient-based methods, GPBB and UPN, to solve the 3D-TV minimization problem in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the standard gradient method. (orig.)
A Gradient Weighted Moving Finite-Element Method with Polynomial Approximation of Any Degree
Directory of Open Access Journals (Sweden)
Ali R. Soheili
2009-01-01
Full Text Available A gradient weighted moving finite element method (GWMFE based on piecewise polynomial of any degree is developed to solve time-dependent problems in two space dimensions. Numerical experiments are employed to test the accuracy and effciency of the proposed method with nonlinear Burger equation.
An M-step preconditioned conjugate gradient method for parallel computation
Adams, L.
1983-01-01
This paper describes a preconditioned conjugate gradient method that can be effectively implemented on both vector machines and parallel arrays to solve sparse symmetric and positive definite systems of linear equations. The implementation on the CYBER 203/205 and on the Finite Element Machine is discussed and results obtained using the method on these machines are given.
An Improved Local Gradient Method for Sea Surface Wind Direction Retrieval from SAR Imagery
Directory of Open Access Journals (Sweden)
Lizhang Zhou
2017-06-01
Full Text Available Sea surface wind affects the fluxes of energy, mass and momentum between the atmosphere and ocean, and therefore regional and global weather and climate. With various satellite microwave sensors, sea surface wind can be measured with large spatial coverage in almost all-weather conditions, day or night. Like any other remote sensing measurements, sea surface wind measurement is also indirect. Therefore, it is important to develop appropriate wind speed and direction retrieval models for different types of microwave instruments. In this paper, a new sea surface wind direction retrieval method from synthetic aperture radar (SAR imagery is developed. In the method, local gradients are computed in frequency domain by combining the operation of smoothing and computing local gradients in one step to simplify the process and avoid the difference approximation. This improved local gradients (ILG method is compared with the traditional two-dimensional fast Fourier transform (2D FFT method and local gradients (LG method, using interpolating wind directions from the European Centre for Medium-Range Weather Forecast (ECMWF reanalysis data and the Cross-Calibrated Multi-Platform (CCMP wind vector product. The sensitivities to the salt-and-pepper noise, the additive noise and the multiplicative noise are analyzed. The ILG method shows a better performance of retrieval wind directions than the other two methods.
Necessary and sufficient conditions for the existence of a conjugate gradient method
International Nuclear Information System (INIS)
Faber, V.; Manteuffel, T.
1984-01-01
The authors characterize the class CG(s) of matrices A for which the linear system Ax = b can be solved by an s-term conjugate gradient method. The authors show that, except for a few anomalies, the class CG(s) consists of matrices A for which conjugate gradient methods are already known. These matrices are the Hermitian matrices, A* = A, and the matrices of the form A = e/sup i theta/(dI + B), with B* = -B. 7 references
Application of preconditioned conjugate gradient-like methods to reactor kinetics
International Nuclear Information System (INIS)
Yang, D.Y.; Chen, G.S.; Chou, H.P.
1993-01-01
Several conjugate gradient-like (CG-like) methods are applied to solve the nonsymmetric linear systems of equations derived from the time-dependent two-dimensional two-energy-group neutron diffusion equations by a finite difference approximation. The methods are: the generalized conjugate residual method; the generalized conjugate gradient least-square method; the generalized minimal residual method (GMRES); the conjugate gradient square method; and a variant of bi-conjugate gradient method (Bi-CGSTAB). In order to accelerate these methods, six preconditioning techniques are investigated. Two are based on pointwise incomplete factorization: the incomplete LU (ILU) and the modified incomplete LU (MILU) decompositions; two, based on the block tridiagonal structure of the coefficient matrix, are blockwise and modified blockwise incomplete factorizations, BILU and MBILU; two are the alternating-direction implicit and symmetric successive overrelaxation (SSOR) preconditioners, derived from the basic iterative schemes. Comparisons are made by using CG-like methods combined with different preconditioners to solve a sequence of time-step reactor transient problems. Numerical tests indicate that preconditioned BI-CGSTAB with the preconditioner MBILU requires less CPU time and fewer iterations than other methods. The preconditioned CG-like methods are less sensitive to the time-step size used than the Chebyshev semi-iteration method and line SOR method. The indication is that the CGS, Bi-CGSTAB and GMRES methods are, on average, better than the other methods in reactor kinetics computation and that a good preconditioner is more important than the choice of CG-like methods. The MILU decomposition based on the conventional row-sum criterion has difficulty yielding a convergent solution and an improved version is introduced. (author)
Duijnhoven, van F.G.H.; Bastiaansen, C.W.M.
1999-01-01
A new method is presented to generate and to fixate compositional gradients in blends of two miscible and amorphous polymers. A compositional gradient is introduced into a solution of a polymer in a monomer by use of a centrifugal field, and this gradient is subsequently fixated by polymerization of
Sozer, Emre; Brehm, Christoph; Kiris, Cetin C.
2014-01-01
A survey of gradient reconstruction methods for cell-centered data on unstructured meshes is conducted within the scope of accuracy assessment. Formal order of accuracy, as well as error magnitudes for each of the studied methods, are evaluated on a complex mesh of various cell types through consecutive local scaling of an analytical test function. The tests highlighted several gradient operator choices that can consistently achieve 1st order accuracy regardless of cell type and shape. The tests further offered error comparisons for given cell types, leading to the observation that the "ideal" gradient operator choice is not universal. Practical implications of the results are explored via CFD solutions of a 2D inviscid standing vortex, portraying the discretization error properties. A relatively naive, yet largely unexplored, approach of local curvilinear stencil transformation exhibited surprisingly favorable properties
Conjugate gradient type methods for linear systems with complex symmetric coefficient matrices
Freund, Roland
1989-01-01
We consider conjugate gradient type methods for the solution of large sparse linear system Ax equals b with complex symmetric coefficient matrices A equals A(T). Such linear systems arise in important applications, such as the numerical solution of the complex Helmholtz equation. Furthermore, most complex non-Hermitian linear systems which occur in practice are actually complex symmetric. We investigate conjugate gradient type iterations which are based on a variant of the nonsymmetric Lanczos algorithm for complex symmetric matrices. We propose a new approach with iterates defined by a quasi-minimal residual property. The resulting algorithm presents several advantages over the standard biconjugate gradient method. We also include some remarks on the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.
An optimized target-field method for MRI transverse biplanar gradient coil design
International Nuclear Information System (INIS)
Zhang, Rui; Xu, Jing; Huang, Kefu; Zhang, Jue; Fang, Jing; Fu, Youyi; Li, Yangjing
2011-01-01
Gradient coils are essential components of magnetic resonance imaging (MRI) systems. In this paper, we present an optimized target-field method for designing a transverse biplanar gradient coil with high linearity, low inductance and small resistance, which can well satisfy the requirements of permanent-magnet MRI systems. In this new method, the current density is expressed by trigonometric basis functions with unknown coefficients in polar coordinates. Following the standard procedures, we construct an objective function with respect to the total square errors of the magnetic field at all target-field points with the penalty items associated with the stored magnetic energy and the dissipated power. By adjusting the two penalty factors and minimizing the objective function, the appropriate coefficients of the current density are determined. Applying the stream function method to the current density, the specific winding patterns on the planes can be obtained. A novel biplanar gradient coil has been designed using this method to operate in a permanent-magnet MRI system. In order to verify the validity of the proposed approach, the gradient magnetic field generated by the resulted current density has been calculated via the Biot–Savart law. The results have demonstrated the effectiveness and advantage of this proposed method
Strong source heat transfer simulations based on a GalerKin/Gradient - least - squares method
International Nuclear Information System (INIS)
Franca, L.P.; Carmo, E.G.D. do.
1989-05-01
Heat conduction problems with temperature-dependent strong sources are modeled by an equation with a laplacian term, a linear term and a given source distribution term. When the linear-temperature-dependent source term is much larger than the laplacian term, we have a singular perturbation problem. In this case, boundary layers are formed to satisfy the Dirichlet boundary conditions. Although this is an elliptic equation, the standard Galerkin method solution is contaminated by spurious oscillations in the neighborhood of the boundary layers. Herein we employ a Galerkin/Gradient-least-squares method which eliminates all pathological phenomena of the Galerkin method. The method is constructed by adding to the Galerkin method a mesh-dependent term obtained by the least-squares form of the gradient of the Euler-Lagrange equation. Error estimates, numerical simulations in one-and multi-dimensions are given that attest the good stability and accuracy properties of the method [pt
Luteinizing hormone in testicular descent
DEFF Research Database (Denmark)
Toppari, Jorma; Kaleva, Marko M; Virtanen, Helena E
2007-01-01
alone is not sufficient for normal testicular descent. The regulation of androgen production is influenced both by placental human chorionic gonadotropin (hCG) and pituitary luteinizing hormone (LH). There is evidence that the longer pregnancy continues, the more important role pituitary LH may have....... Insulin-like hormone-3 (INSL3) is suggested to be the main regulator of gubernacular development and therefore an apparent regulator of testicular descent. INSL3 production is also related to LH, and reduced INSL3 action is a possible cause for cryptorchidism. Cryptorchid boys have normal testosterone...
A family of conjugate gradient methods for large-scale nonlinear equations
Directory of Open Access Journals (Sweden)
Dexiang Feng
2017-09-01
Full Text Available Abstract In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.
A family of conjugate gradient methods for large-scale nonlinear equations.
Feng, Dexiang; Sun, Min; Wang, Xueyong
2017-01-01
In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.
The influence of deflation vectors at interfaces on the deflated conjugate gradient method
Vermolen, F.J.; Vuik, C.
2001-01-01
We investigate the influence of the value of deflation vectors at interfaces on the rate of convergence of preconditioned conjugate gradient methods. Our set-up is a Laplace problem in two dimensions with continuous or discontinuous coeffcients that vary in several orders of magnitude. In the
Pilling evaluation of patterned fabrics based on a gradient field method
Czech Academy of Sciences Publication Activity Database
Techniková, L.; Tunák, M.; Janáček, Jiří
2016-01-01
Roč. 41, č. 1 (2016), s. 97-101 ISSN 0971-0426 Institutional support: RVO:67985823 Keywords : 3D surface reconstruction * fabric pilling * gradient field method * patterned fabric * pills detection Subject RIV: JS - Reliability ; Quality Management, Testing Impact factor: 0.430, year: 2016
A blind deconvolution method based on L1/L2 regularization prior in the gradient space
Cai, Ying; Shi, Yu; Hua, Xia
2018-02-01
In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.
A fast nonlinear conjugate gradient based method for 3D frictional contact problems
Zhao, J.; Vollebregt, E.A.H.; Oosterlee, C.W.
2014-01-01
This paper presents a fast numerical solver for a nonlinear constrained optimization problem, arising from a 3D frictional contact problem. It incorporates an active set strategy with a nonlinear conjugate gradient method. One novelty is to consider the tractions of each slip element in a polar
A fast nonlinear conjugate gradient based method for 3D concentrated frictional contact problems
J. Zhao (Jing); E.A.H. Vollebregt (Edwin); C.W. Oosterlee (Cornelis)
2015-01-01
htmlabstractThis paper presents a fast numerical solver for a nonlinear constrained optimization problem, arising from 3D concentrated frictional shift and rolling contact problems with dry Coulomb friction. The solver combines an active set strategy with a nonlinear conjugate gradient method. One
Efficient two-level preconditionined conjugate gradient method on the GPU
Gupta, R.; Van Gijzen, M.B.; Vuik, K.
2011-01-01
We present an implementation of Two-Level Preconditioned Conjugate Gradient Method for the GPU. We investigate a Truncated Neumann Series based preconditioner in combination with deflation and compare it with Block Incomplete Cholesky schemes. This combination exhibits fine-grain parallelism and
Applicability of Stokes method for measuring viscosity of mixtures with concentration gradient
Directory of Open Access Journals (Sweden)
César Medina
2017-12-01
Full Text Available After measuring density and viscosity of a mixture of glycerin and water contained in a vertical pipe, a variation of these properties according to depth is observed. These gradients are typical of non-equilibrium states related to the lower density of water and the fact that relatively long times are necessary to achieve homogeneity. In the same pipe, the falling velocity of five little spheres is measured as a function of depth, and then a numerical fit is performed which agrees very well with experimental data. Based on the generalization of these results, the applicability of Stokes method is discussed for measuring viscosity of mixtures with a concentration gradient.
Development of the CARS method for measurement of pressure and temperature gradients in centrifuges
International Nuclear Information System (INIS)
Zeltmann, A.H.; Valentini, J.J.
1983-12-01
These experiments evaluated the feasibility of applying the CARS technique to the measurement of UF 6 concentrations and pressure gradients in a gas centrifuge. The resultant CARS signals were properly related to system parameters as suggested by theory. The results have been used to guide design of an apparatus for making CARS measurements in a UF 6 gas centrifuge. Ease of measurement is expected for pressures as low as 0.1 torr. Temperature gradients can be measured by this technique with changes in the data acquisition method. 16 references, 8 figures, 2 tables
Analytical free energy gradient for the molecular Ornstein-Zernike self-consistent-field method
Directory of Open Access Journals (Sweden)
N.Yoshida
2007-09-01
Full Text Available An analytical free energy gradient for the molecular Ornstein-Zernike self-consistent-field (MOZ-SCF method is presented. MOZ-SCF theory is one of the theories to considering the solvent effects on the solute electronic structure in solution. [Yoshida N. et al., J. Chem. Phys., 2000, 113, 4974] Molecular geometries of water, formaldehyde, acetonitrile and acetone in water are optimized by analytical energy gradient formula. The results are compared with those from the polarizable continuum model (PCM, the reference interaction site model (RISM-SCF and the three dimensional (3D RISM-SCF.
Bernal, Javier; Torres-Jimenez, Jose
2015-01-01
SAGRAD (Simulated Annealing GRADient), a Fortran 77 program for computing neural networks for classification using batch learning, is discussed. Neural network training in SAGRAD is based on a combination of simulated annealing and Møller's scaled conjugate gradient algorithm, the latter a variation of the traditional conjugate gradient method, better suited for the nonquadratic nature of neural networks. Different aspects of the implementation of the training process in SAGRAD are discussed, such as the efficient computation of gradients and multiplication of vectors by Hessian matrices that are required by Møller's algorithm; the (re)initialization of weights with simulated annealing required to (re)start Møller's algorithm the first time and each time thereafter that it shows insufficient progress in reaching a possibly local minimum; and the use of simulated annealing when Møller's algorithm, after possibly making considerable progress, becomes stuck at a local minimum or flat area of weight space. Outlines of the scaled conjugate gradient algorithm, the simulated annealing procedure and the training process used in SAGRAD are presented together with results from running SAGRAD on two examples of training data.
Feng, Shuo; Ji, Jim
2014-04-01
Parallel excitation (pTx) techniques with multiple transmit channels have been widely used in high field MRI imaging to shorten the RF pulse duration and/or reduce the specific absorption rate (SAR). However, the efficiency of pulse design still needs substantial improvement for practical real-time applications. In this paper, we present a detailed description of a fast pulse design method with Fourier domain gridding and a conjugate gradient method. Simulation results of the proposed method show that the proposed method can design pTx pulses at an efficiency 10 times higher than that of the conventional conjugate-gradient based method, without reducing the accuracy of the desirable excitation patterns.
Monte Carlo method for polarized radiative transfer in gradient-index media
International Nuclear Information System (INIS)
Zhao, J.M.; Tan, J.Y.; Liu, L.H.
2015-01-01
Light transfer in gradient-index media generally follows curved ray trajectories, which will cause light beam to converge or diverge during transfer and induce the rotation of polarization ellipse even when the medium is transparent. Furthermore, the combined process of scattering and transfer along curved ray path makes the problem more complex. In this paper, a Monte Carlo method is presented to simulate polarized radiative transfer in gradient-index media that only support planar ray trajectories. The ray equation is solved to the second order to address the effect induced by curved ray trajectories. Three types of test cases are presented to verify the performance of the method, which include transparent medium, Mie scattering medium with assumed gradient index distribution, and Rayleigh scattering with realistic atmosphere refractive index profile. It is demonstrated that the atmospheric refraction has significant effect for long distance polarized light transfer. - Highlights: • A Monte Carlo method for polarized radiative transfer in gradient index media. • Effect of curved ray paths on polarized radiative transfer is considered. • Importance of atmospheric refraction for polarized light transfer is demonstrated
A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates
Energy Technology Data Exchange (ETDEWEB)
Wang, Hanquan, E-mail: hanquan.wang@gmail.com [School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, Yunnan Province, 650221 (China); Yunnan Tongchang Scientific Computing and Data Mining Research Center, Kunming, Yunnan Province, 650221 (China)
2014-10-01
In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can be computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method.
A projection gradient method for computing ground state of spin-2 Bose–Einstein condensates
International Nuclear Information System (INIS)
Wang, Hanquan
2014-01-01
In this paper, a projection gradient method is presented for computing ground state of spin-2 Bose–Einstein condensates (BEC). We first propose the general projection gradient method for solving energy functional minimization problem under multiple constraints, in which the energy functional takes real functions as independent variables. We next extend the method to solve a similar problem, where the energy functional now takes complex functions as independent variables. We finally employ the method into finding the ground state of spin-2 BEC. The key of our method is: by constructing continuous gradient flows (CGFs), the ground state of spin-2 BEC can be computed as the steady state solution of such CGFs. We discretized the CGFs by a conservative finite difference method along with a proper way to deal with the nonlinear terms. We show that the numerical discretization is normalization and magnetization conservative and energy diminishing. Numerical results of the ground state and their energy of spin-2 BEC are reported to demonstrate the effectiveness of the numerical method
Research on n-γ discrimination method based on spectrum gradient analysis of signals
International Nuclear Information System (INIS)
Luo Xiaoliang; Liu Guofu; Yang Jun; Wang Yueke
2013-01-01
Having discovered that there are distinct differences between the spectrum gradient of the output neutron and γ-ray signal from liquid scintillator detectors, this paper presented a n-γ discrimination method called spectrum gradient analysis (SGA) based on frequency-domain features of the pulse signals. The basic principle and feasibility of SGA method were discussed and the validity of n-γ discrimination results of SGA was verified by the associated particle neutron flight experiment. The discrimination performance of SGA was evaluated under different conditions of sampling rates ranging from 5 G/s to 250 M/s. The results show that SGA method exhibits insensitivity to noise, strong anti-interference ability, stable discrimination performance and lower amount of calculation in contrast with time-domain n-γ discrimination methods. (authors)
Ananiev, Sergey
2006-01-01
The paper demonstrates the equivalence between the optimality criteria (OC) method, initially proposed by Bendsoe & Kikuchi for topology optimization problem, and the projected gradient method. The equivalence is shown using Hestenes definition of Lagrange multipliers. Based on this development, an alternative formulation of the Karush-Kuhn-Tucker (KKT) condition is suggested. Such reformulation has some advantages, which will be also discussed in the paper. For verification purposes the modi...
Conjugate gradient method for phase retrieval based on the Wirtinger derivative.
Wei, Zhun; Chen, Wen; Qiu, Cheng-Wei; Chen, Xudong
2017-05-01
A conjugate gradient Wirtinger flow (CG-WF) algorithm for phase retrieval is proposed in this paper. It is shown that, compared with recently reported Wirtinger flow and its modified methods, the proposed CG-WF algorithm is able to dramatically accelerate the convergence rate while keeping the dominant computational cost of each iteration unchanged. We numerically illustrate the effectiveness of our method in recovering 1D Gaussian signals and 2D natural color images under both Gaussian and coded diffraction pattern models.
Improvement of GaN epilayer by gradient layer method with molecular-beam epitaxy
International Nuclear Information System (INIS)
Chen, Yen-Liang; Lo, Ikai; Gau, Ming-Hong; Hsieh, Chia-Ho; Sham, Meng-Wei; Pang, Wen-Yuan; Hsu, Yu-Chi; Tsai, Jenn-Kai; Schuber, Ralf; Schaadt, Daniel
2012-01-01
We demonstrated a molecular beam epitaxy method to resolve the dilemma between structural and morphological quality in growth of the GaN epilayer. A gradient buffer layer was grown in such a way that the N/Ga ratio was gradually changed from nitrogen-rich to gallium-rich. The GaN epitaxial layer was then grown on the gradient buffer layer. In the X-ray diffraction analysis of GaN(002) rocking curves, we found that the full width at half-maximum was improved from 531.69″ to 59.43″ for the sample with a gradient buffer layer as compared to a purely gallium-rich grown sample. Atomic force microscopy analysis showed that the root-mean-square roughness of the surface was improved from 18.28 nm to 1.62 nm over an area of 5 × 5 μm 2 with respect to a purely nitrogen-rich grown sample. Raman scattering showed the presence of a slightly tilted plane in the gradient layer. Furthermore we showed that the gradient layer can also slash the strain force caused by either Ga-rich GaN epitaxial layer or AlN buffer layer. - Highlights: ► The samples were grown by plasma-assisted molecular beam epitaxy. ► The GaN epilayer was grown on sapphire substrate. ► The samples were characterized by X-ray diffraction and atomic force microscopy. ► The sample quality was improved by gradient buffer layer.
Improvement of GaN epilayer by gradient layer method with molecular-beam epitaxy
Energy Technology Data Exchange (ETDEWEB)
Chen, Yen-Liang [Department of Physics, Institute of Material Science and Engineering, Center for Nanoscience and Nanotechnology, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC (China); Lo, Ikai, E-mail: ikailo@mail.phys.nsysu.edu.tw [Department of Physics, Institute of Material Science and Engineering, Center for Nanoscience and Nanotechnology, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC (China); Gau, Ming-Hong; Hsieh, Chia-Ho; Sham, Meng-Wei; Pang, Wen-Yuan; Hsu, Yu-Chi [Department of Physics, Institute of Material Science and Engineering, Center for Nanoscience and Nanotechnology, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan, ROC (China); Tsai, Jenn-Kai [Department of Electronics Engineering, National Formosa University, Hu-Wei, Yun-Lin County 63208, Taiwan, ROC (China); Schuber, Ralf; Schaadt, Daniel [Institute of Applied Physics/DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany)
2012-07-31
We demonstrated a molecular beam epitaxy method to resolve the dilemma between structural and morphological quality in growth of the GaN epilayer. A gradient buffer layer was grown in such a way that the N/Ga ratio was gradually changed from nitrogen-rich to gallium-rich. The GaN epitaxial layer was then grown on the gradient buffer layer. In the X-ray diffraction analysis of GaN(002) rocking curves, we found that the full width at half-maximum was improved from 531.69 Double-Prime to 59.43 Double-Prime for the sample with a gradient buffer layer as compared to a purely gallium-rich grown sample. Atomic force microscopy analysis showed that the root-mean-square roughness of the surface was improved from 18.28 nm to 1.62 nm over an area of 5 Multiplication-Sign 5 {mu}m{sup 2} with respect to a purely nitrogen-rich grown sample. Raman scattering showed the presence of a slightly tilted plane in the gradient layer. Furthermore we showed that the gradient layer can also slash the strain force caused by either Ga-rich GaN epitaxial layer or AlN buffer layer. - Highlights: Black-Right-Pointing-Pointer The samples were grown by plasma-assisted molecular beam epitaxy. Black-Right-Pointing-Pointer The GaN epilayer was grown on sapphire substrate. Black-Right-Pointing-Pointer The samples were characterized by X-ray diffraction and atomic force microscopy. Black-Right-Pointing-Pointer The sample quality was improved by gradient buffer layer.
Accelerated gradient methods for total-variation-based CT image reconstruction
DEFF Research Database (Denmark)
Jørgensen, Jakob Heide; Jensen, Tobias Lindstrøm; Hansen, Per Christian
2011-01-01
incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping...... reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton’s method. The simple gradient method has much lower memory requirements, but exhibits slow convergence...
And still, a new beginning: the Galerkin least-squares gradient method
International Nuclear Information System (INIS)
Franca, L.P.; Carmo, E.G.D. do
1988-08-01
A finite element method is proposed to solve a scalar singular diffusion problem. The method is constructed by adding to the standard Galerkin a mesh-dependent term obtained by taking the gradient of the Euler-lagrange equation and multiplying it by its least-squares. For the one-dimensional homogeneous problem the method is designed to develop nodal exact solution. An error estimate shows that the method converges optimaly for any value of the singular parameter. Numerical results demonstrate the good stability and accuracy properties of the method. (author) [pt
Application of the gradient method to Hartree-Fock-Bogoliubov theory
International Nuclear Information System (INIS)
Robledo, L. M.; Bertsch, G. F.
2011-01-01
A computer code is presented for solving the equations of the Hartree-Fock-Bogoliubov (HFB) theory by the gradient method, motivated by the need for efficient and robust codes to calculate the configurations required by extensions of the HFB theory, such as the generator coordinate method. The code is organized with a separation between the parts that are specific to the details of the Hamiltonian and the parts that are generic to the gradient method. This permits total flexibility in choosing the symmetries to be imposed on the HFB solutions. The code solves for both even and odd particle-number ground states, with the choice determined by the input data stream. Application is made to the nuclei in the sd shell using the universal sd-shell interaction B (USDB) shell-model Hamiltonian.
International Nuclear Information System (INIS)
Miyazaki, T.; Koyama, T.; Kobayashi, S.
1996-01-01
A new experimental method to determine the phase boundary and phase equilibrium is accomplished by - means of analytical transmission electron microscopy for alloys with a macroscopic composition gradient. The various phase boundaries, i.e. the coherent binodal and spinodal lines, incoherent binodal line and order/disorder transformation line are distinctly determined for the Cu-Ti alloy and the other alloy systems. Furthermore, the equilibrium compositions at the interface of precipitate/matrix can experimentally be obtained for various particle sizes, and thus the Gibbs-Thomson's relation is verified. It is expected that the composition gradient method proposed in the present will become an important experimental method of the microstructural characterization
New generalized conjugate gradient methods for the non-quadratic model in unconstrained optimization
International Nuclear Information System (INIS)
Al-Bayati, A.
2001-01-01
This paper present two new conjugate gradient algorithms which use the non-quadratic model in unconstrained optimization. The first is a new generalized self-scaling variable metric algorithm based on the sloboda generalized conjugate gradient method which is invariant to a nonlinear scaling of a stricity convex quadratic function; the second is an interleaving between the generalized sloboda method and the first algorithm; all these algorithm use exact line searches. Numerical comparisons over twenty test functions show that the interleaving algorithm is best overall and requires only about half the function evaluations of the Sloboda method: interleaving algorithms are likely to be preferred when the dimensionality of the problem is increased. (author). 29 refs., 1 tab
Use of a preconditioned Bi-conjugate gradient method for hybrid plasma stability analysis
International Nuclear Information System (INIS)
Mikic, Z.; Morse, E.C.
1985-01-01
The numerical stability analysis of compact toroidal plasmas using implicit time differencing requires the solution of a set of coupled, 2-dimensional, elliptic partial differential equations for the field quantities at every timestep. When the equations are spatially finite-differenced and written in matrix form, the resulting matrix is large, sparse, complex, non-Hermitian, and indefinite. The use of the preconditioned bi-conjugate gradient method for solving these equations is discussed. The effect of block-diagonal preconditioning and incomplete block-LU preconditionig on the convergence of the method is investigated. For typical matrices arising in our studies, the eigenvalue spectra of the original and preconditioned matrices are calculated as an illustration of the effectiveness of the preconditioning. We show that the preconditioned bi-conjugate gradient method coverages more rapidly than the conjugate gradient method applied to the normal equations, and that it is an effective iterative method for the class of non-Hermitian, indefinite problems of interest
Theseus' arid Peirithoos' descent into the underworld
Bremmer, Jan N.
2015-01-01
In my contribution I will first briefly discuss the earliest known literary descent, that by Enkidu, which almost certainly influenced the poet of the Odyssey in his depiction of Odysseus' descent. Then I will take a brief look at some descents in the Archaic Age, in particular the earliest
Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.
Traneus, Erik; Bizzocchi, Nicola; Fellin, Francesco; Rombi, Barbara; Farace, Paolo
2018-01-01
The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
Energy Technology Data Exchange (ETDEWEB)
Knox, C.E.; Vicroy, D.D.; Simmon, D.A.
1985-05-01
A simple, airborne, flight-management descent algorithm was developed and programmed into a small programmable calculator. The algorithm may be operated in either a time mode or speed mode. The time mode was designed to aid the pilot in planning and executing a fuel-conservative descent to arrive at a metering fix at a time designated by the air traffic control system. The speed model was designed for planning fuel-conservative descents when time is not a consideration. The descent path for both modes was calculated for a constant with considerations given for the descent Mach/airspeed schedule, gross weight, wind, wind gradient, and nonstandard temperature effects. Flight tests, using the algorithm on the programmable calculator, showed that the open-loop guidance could be useful to airline flight crews for planning and executing fuel-conservative descents.
International Nuclear Information System (INIS)
Caffrey, M.; Hing, F.S.
1987-01-01
A method that enables temperature-composition phase diagram construction at unprecedented rates is described and evaluated. The method involves establishing a known temperature gradient along the length of a metal rod. Samples of different compositions contained in long, thin-walled capillaries are positioned lengthwise on the rod and equilibrated such that the temperature gradient is communicated into the sample. The sample is then moved through a focused, monochromatic synchrotron-derived x-ray beam and the image-intensified diffraction pattern from the sample is recorded on videotape continuously in live-time as a function of position and, thus, temperature. The temperature at which the diffraction pattern changes corresponds to a phase boundary, and the phase(s) existing (coexisting) on either side of the boundary can be identified on the basis of the diffraction pattern. Repeating the measurement on samples covering the entire composition range completes the phase diagram. These additional samples can be conveniently placed at different locations around the perimeter of the cylindrical rod and rotated into position for diffraction measurement. Temperature-composition phase diagrams for the fully hydrated binary mixtures, dimyristoylphosphatidylcholine (DMPC)/dipalmitoylphosphatidylcholine (DPPC) and dipalmitoylphosphatidylethanolamine (DPPE)/DPPC, have been constructed using the new temperature gradient method. They agree well with and extend the results obtained by other techniques. In the DPPE/DPPC system structural parameters as a function of temperature in the various phases including the subgel phase are reported. The potential limitations of this steady-state method are discussed
Leone, Frank A., Jr.
2015-01-01
A method is presented to represent the large-deformation kinematics of intraply matrix cracks and delaminations in continuum damage mechanics (CDM) constitutive material models. The method involves the additive decomposition of the deformation gradient tensor into 'crack' and 'bulk material' components. The response of the intact bulk material is represented by a reduced deformation gradient tensor, and the opening of an embedded cohesive interface is represented by a normalized cohesive displacement-jump vector. The rotation of the embedded interface is tracked as the material deforms and as the crack opens. The distribution of the total local deformation between the bulk material and the cohesive interface components is determined by minimizing the difference between the cohesive stress and the bulk material stress projected onto the cohesive interface. The improvements to the accuracy of CDM models that incorporate the presented method over existing approaches are demonstrated for a single element subjected to simple shear deformation and for a finite element model of a unidirectional open-hole tension specimen. The material model is implemented as a VUMAT user subroutine for the Abaqus/Explicit finite element software. The presented deformation gradient decomposition method reduces the artificial load transfer across matrix cracks subjected to large shearing deformations, and avoids the spurious secondary failure modes that often occur in analyses based on conventional progressive damage models.
HIRFL-SSC trim coil currents calculation by conjugate gradients method
International Nuclear Information System (INIS)
Liu, W.
2005-01-01
For accelerating different kinds of ions to various energies, the HIRFL-SSC should form the corresponding isochronous magnetic field by its main coil and trim coils. Previously, there were errors in fitting the theoretical isochronous magnetic field in the small radius region, which led to some operation difficulties for ion acceleration in the inject region. After further investigation of the restrictive condition of the maximum current limitation, the trim coil currents for fitting the theoretical isochronous magnetic field were recalculated by the conjugate gradients method. Better results were obtained in the operation of HIRFL-SSC. This article introduces the procedure to calculate the trim coil currents. The calculation method of conjugate gradients is introduced and the fitting error is analysed. (author)
International Nuclear Information System (INIS)
Kari, R.E.; Mezey, P.G.; Csizmadia, I.G.
1975-01-01
Expressions are given for calculating the energy gradient vector in the exponent space of Gaussian basis sets and a technique to optimize orbital exponents using the method of conjugate gradients is described. The method is tested on the (9/sups/5/supp/) Gaussian basis space and optimum exponents are determined for the carbon atom. The analysis of the results shows that the calculated one-electron properties converge more slowly to their optimum values than the total energy converges to its optimum value. In addition, basis sets approximating the optimum total energy very well can still be markedly improved for the prediction of one-electron properties. For smaller basis sets, this improvement does not warrant the necessary expense
Research on a wavefront aberration calculation method for a laser energy gradient attenuator
International Nuclear Information System (INIS)
Dong, Tingting; Han, Xu; Chen, Chi; Fu, Yuegang; Li, Ming
2013-01-01
When a laser energy gradient attenuator is working, there is an inhomogeneous temperature distribution in the whole of the glass because of the non-uniform light energy absorption. This will lead to optical performance reduction. An integrated opto-thermal–mechanical method is proposed to calculate the wavefront aberration for analysis of the thermal effect of the system. Non-sequential optical analysis is used for computing the absorbed energy distribution. The finite element analysis program solves the temperature distribution and the deformations of nodes on the surfaces. An interface routine is created to fit the surface shape and the index field, and extended Zernike polynomials are introduced to get a higher fitting precision. Finally, the parameters are imported to the CodeV optical design program automatically, and the user defined gradient index material is ray traced to obtain the wavefront aberration. The method can also be used in other optical systems for thermal effect analysis. (letter)
Optimization of offshore wind turbine support structures using analytical gradient-based method
Chew, Kok Hon; Tai, Kang; Ng, E.Y.K.; Muskulus, Michael
2015-01-01
Design optimization of the offshore wind turbine support structure is an expensive task; due to the highly-constrained, non-convex and non-linear nature of the design problem. This report presents an analytical gradient-based method to solve this problem in an efficient and effective way. The design sensitivities of the objective and constraint functions are evaluated analytically while the optimization of the structure is performed, subject to sizing, eigenfrequency, extreme load an...
Asynchronous Gossip-Based Gradient-Free Method for Multiagent Optimization
Deming Yuan
2014-01-01
This paper considers the constrained multiagent optimization problem. The objective function of the problem is a sum of convex functions, each of which is known by a specific agent only. For solving this problem, we propose an asynchronous distributed method that is based on gradient-free oracles and gossip algorithm. In contrast to the existing work, we do not require that agents be capable of computing the subgradients of their objective functions and coordinating their...
Problem of unstable pivots in the incomplete LU-conjugate gradient method
International Nuclear Information System (INIS)
Kershaw, D.S.
1978-01-01
Incomplete LU and incomplete-Cholesky conjugate gradient methods are becoming widely used in both laser and magnetic fusion research. In my original presentation of these methods, the problem of what to do if a pivot [L/sub ii/U/sub ii/) becomes very small or zero was raised and only partially answered by the suggestion that it be arbitrarily set to some non-zero value. In what follows it will be shown precisely how small the pivot can become before it must be fixed and precisely what value it should be set to in order to minimize the error in LU. Numerical examples will be given to show that not only does this prescription improve incomplete LU-conjugate gradient methods , but exact LU decomposition carried out with this prescription for handling small pivots and followed by a few linear or conjugate gradient iterations can be much faster than the permutations of rows and columns usually employed to circumvent small pivot problems
A Projected Non-linear Conjugate Gradient Method for Interactive Inverse Kinematics
DEFF Research Database (Denmark)
Engell-Nørregård, Morten; Erleben, Kenny
2009-01-01
Inverse kinematics is the problem of posing an articulated figure to obtain a wanted goal, without regarding inertia and forces. Joint limits are modeled as bounds on individual degrees of freedom, leading to a box-constrained optimization problem. We present A projected Non-linear Conjugate...... Gradient optimization method suitable for box-constrained optimization problems for inverse kinematics. We show application on inverse kinematics positioning of a human figure. Performance is measured and compared to a traditional Jacobian Transpose method. Visual quality of the developed method...
Kou, Jisheng; Sun, Shuyu
2014-01-01
The gradient theory for the surface tension of simple fluids and mixtures is rigorously analyzed based on mathematical theory. The finite element approximation of surface tension is developed and analyzed, and moreover, an adaptive finite element method based on a physical-based estimator is proposed and it can be coupled efficiently with Newton's method as well. The numerical tests are carried out both to verify the proposed theory and to demonstrate the efficiency of the proposed method. © 2013 Elsevier B.V. All rights reserved.
Frequency domain optical tomography using a conjugate gradient method without line search
International Nuclear Information System (INIS)
Kim, Hyun Keol; Charette, Andre
2007-01-01
A conjugate gradient method without line search (CGMWLS) is presented. This method is used to retrieve the local maps of absorption and scattering coefficients inside the tissue-like test medium, with the synthetic data. The forward problem is solved with a discrete-ordinates finite-difference method based on the frequency domain formulation of radiative transfer equation. The inversion results demonstrate that the CGMWLS can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by reducing cross-talk between absorption and scattering coefficients
Microwave imaging of dielectric cylinder using level set method and conjugate gradient algorithm
International Nuclear Information System (INIS)
Grayaa, K.; Bouzidi, A.; Aguili, T.
2011-01-01
In this paper, we propose a computational method for microwave imaging cylinder and dielectric object, based on combining level set technique and the conjugate gradient algorithm. By measuring the scattered field, we tried to retrieve the shape, localisation and the permittivity of the object. The forward problem is solved by the moment method, while the inverse problem is reformulate in an optimization one and is solved by the proposed scheme. It found that the proposed method is able to give good reconstruction quality in terms of the reconstructed shape and permittivity.
Kou, Jisheng
2014-01-01
The gradient theory for the surface tension of simple fluids and mixtures is rigorously analyzed based on mathematical theory. The finite element approximation of surface tension is developed and analyzed, and moreover, an adaptive finite element method based on a physical-based estimator is proposed and it can be coupled efficiently with Newton\\'s method as well. The numerical tests are carried out both to verify the proposed theory and to demonstrate the efficiency of the proposed method. © 2013 Elsevier B.V. All rights reserved.
Hakiki, Farizal
2017-07-25
A study performed by Marbun et al. [1] claimed that “A new methodology to predict fracture pressure from former calculations, Matthew–Kelly and Eaton are proposed.” Also, Marbun et al.\\'s paper stated that “A new value of Poisson\\'s and a stress ratio of the formation were generated and the accuracy of fracture gradient was improved.” We found those all statements are incorrect and some misleading concepts are revealed. An attempt to expose the method of fracture gradient determination from industry practice also appears to solidify that our arguments are acceptable to against improper Marbun et al.\\'s claims.
Descent construction for GSpin groups
Hundley, Joseph
2016-01-01
In this paper the authors provide an extension of the theory of descent of Ginzburg-Rallis-Soudry to the context of essentially self-dual representations, that is, representations which are isomorphic to the twist of their own contragredient by some Hecke character. The authors' theory supplements the recent work of Asgari-Shahidi on the functorial lift from (split and quasisplit forms of) GSpin_{2n} to GL_{2n}.
Analytical Energy Gradients for Excited-State Coupled-Cluster Methods
Wladyslawski, Mark; Nooijen, Marcel
The equation-of-motion coupled-cluster (EOM-CC) and similarity transformed equation-of-motion coupled-cluster (STEOM-CC) methods have been firmly established as accurate and routinely applicable extensions of single-reference coupled-cluster theory to describe electronically excited states. An overview of these methods is provided, with emphasis on the many-body similarity transform concept that is the key to a rationalization of their accuracy. The main topic of the paper is the derivation of analytical energy gradients for such non-variational electronic structure approaches, with an ultimate focus on obtaining their detailed algebraic working equations. A general theoretical framework using Lagrange's method of undetermined multipliers is presented, and the method is applied to formulate the EOM-CC and STEOM-CC gradients in abstract operator terms, following the previous work in [P.G. Szalay, Int. J. Quantum Chem. 55 (1995) 151] and [S.R. Gwaltney, R.J. Bartlett, M. Nooijen, J. Chem. Phys. 111 (1999) 58]. Moreover, the systematics of the Lagrange multiplier approach is suitable for automation by computer, enabling the derivation of the detailed derivative equations through a standardized and direct procedure. To this end, we have developed the SMART (Symbolic Manipulation and Regrouping of Tensors) package of automated symbolic algebra routines, written in the Mathematica programming language. The SMART toolkit provides the means to expand, differentiate, and simplify equations by manipulation of the detailed algebraic tensor expressions directly. The Lagrangian multiplier formulation establishes a uniform strategy to perform the automated derivation in a standardized manner: A Lagrange multiplier functional is constructed from the explicit algebraic equations that define the energy in the electronic method; the energy functional is then made fully variational with respect to all of its parameters, and the symbolic differentiations directly yield the explicit
Multi-color incomplete Cholesky conjugate gradient methods for vector computers. Ph.D. Thesis
Poole, E. L.
1986-01-01
In this research, we are concerned with the solution on vector computers of linear systems of equations, Ax = b, where A is a larger, sparse symmetric positive definite matrix. We solve the system using an iterative method, the incomplete Cholesky conjugate gradient method (ICCG). We apply a multi-color strategy to obtain p-color matrices for which a block-oriented ICCG method is implemented on the CYBER 205. (A p-colored matrix is a matrix which can be partitioned into a pXp block matrix where the diagonal blocks are diagonal matrices). This algorithm, which is based on a no-fill strategy, achieves O(N/p) length vector operations in both the decomposition of A and in the forward and back solves necessary at each iteration of the method. We discuss the natural ordering of the unknowns as an ordering that minimizes the number of diagonals in the matrix and define multi-color orderings in terms of disjoint sets of the unknowns. We give necessary and sufficient conditions to determine which multi-color orderings of the unknowns correpond to p-color matrices. A performance model is given which is used both to predict execution time for ICCG methods and also to compare an ICCG method to conjugate gradient without preconditioning or another ICCG method. Results are given from runs on the CYBER 205 at NASA's Langley Research Center for four model problems.
Ozcan, Aydin; Perego, Claudio; Salvalaglio, Matteo; Parrinello, Michele; Yazaydin, Ozgur
2017-05-01
In this study, we introduce a new non-equilibrium molecular dynamics simulation method to perform simulations of concentration driven membrane permeation processes. The methodology is based on the application of a non-conservative bias force controlling the concentration of species at the inlet and outlet of a membrane. We demonstrate our method for pure methane, ethane and ethylene permeation and for ethane/ethylene separation through a flexible ZIF-8 membrane. Results show that a stationary concentration gradient is maintained across the membrane, realistically simulating an out-of-equilibrium diffusive process, and the computed permeabilities and selectivity are in good agreement with experimental results.
A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency.
Wang, Bo; Su, Yumin; Wan, Lei
2016-04-15
Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs) to detect the sea-sky line (SSL) accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF). In the end, the proposed method is tested on a benchmark dataset from the "XL" USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.
Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.
Fessler, J A; Booth, S D
1999-01-01
Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.
A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency
Directory of Open Access Journals (Sweden)
Bo Wang
2016-04-01
Full Text Available Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs to detect the sea-sky line (SSL accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF. In the end, the proposed method is tested on a benchmark dataset from the “XL” USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.
A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery
Directory of Open Access Journals (Sweden)
Fasahat Ullah Siddiqui
2016-07-01
Full Text Available Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality. Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state
Directory of Open Access Journals (Sweden)
Kang Ma
2017-01-01
Full Text Available Coherent gradient sensing (CGS method can be used to measure the slope of a reflective surface, and has the merits of full-field, non-contact, and real-time measurement. In this study, the thermal stress field of thermal barrier coating (TBC structures is measured by CGS method. Two kinds of powders were sprayed onto Ni-based alloy using a plasma spraying method to obtain two groups of film–substrate specimens. The specimens were then heated with an oxy-acetylene flame. The resulting thermal mismatch between the film and substrate led to out-of-plane deformation of the specimen. The deformation was measured by the reflective CGS method and the thermal stress field of the structure was obtained through calibration with the help of finite element analysis. Both the experiment and numerical results showed that the thermal stress field of TBC structures can be successfully measured by CGS method.
Method of T2 spectrum inversion with conjugate gradient algorithm from NMR data
International Nuclear Information System (INIS)
Li Pengju; Shi Shangming; Song Yanjie
2010-01-01
Based on the optimization techniques, the T 2 spectrum inversion method of conjugate gradient that is easy to realize non-negativity constraint of T2 spectrum is proposed. The method transforms the linear mixed-determined problem of T2 spectrum inversion into the typical optimization problem of searching the minimum of objective function by building up the objective function according to the basic idea of geophysics modeling. The optimization problem above is solved with the conjugate gradient algorithm that has quick convergence rate and quadratic termination. The method has been applied to the inversion of noise free echo train generated from artificial spectrum, artificial echo train with signal-to-noise ratio (SNR)=25 and NMR experimental data of drilling core. The comparison between the inversion results of this paper and artificial spectrum or the result of software imported in NMR laboratory shows that the method can correctly invert T 2 spectrum from artificial NMR relaxation data even though SNR=25 and that inversion T 2 spectrum with good continuity and smoothness from core NMR experimental data accords perfectly with that of laboratory software imported, and moreover,the absolute error between the NMR porosity computed from T 2 spectrum and helium (He) porosity in laboratory is 0.65%. (authors)
Mühlherr, Bernhard; Weiss, Richard M
2015-01-01
Descent in Buildings begins with the resolution of a major open question about the local structure of Bruhat-Tits buildings. The authors then put their algebraic solution into a geometric context by developing a general fixed point theory for groups acting on buildings of arbitrary type, giving necessary and sufficient conditions for the residues fixed by a group to form a kind of subbuilding or "form" of the original building. At the center of this theory is the notion of a Tits index, a combinatorial version of the notion of an index in the relative theory of algebraic groups. These results
Astawa, INGA; Gusti Ngurah Bagus Caturbawa, I.; Made Sajayasa, I.; Dwi Suta Atmaja, I. Made Ari
2018-01-01
The license plate recognition usually used as part of system such as parking system. License plate detection considered as the most important step in the license plate recognition system. We propose methods that can be used to detect the vehicle plate on mobile phone. In this paper, we used Sliding Window, Histogram of Oriented Gradient (HOG), and Support Vector Machines (SVM) method to license plate detection so it will increase the detection level even though the image is not in a good quality. The image proceed by Sliding Window method in order to find plate position. Feature extraction in every window movement had been done by HOG and SVM method. Good result had shown in this research, which is 96% of accuracy.
International Nuclear Information System (INIS)
Kaschner, R.; Graefenstein, J.; Ziesche, P.
1988-12-01
From the local momentum balance using density functional theory an expression for the local quantum-mechanical stress tensor (or stress field) σ(r) of non-relativistic Coulomb systems is found out within the Thomas-Fermi approximation and its generalizations including gradient expansion method. As an illustration the stress field σ(r) is calculated for the jellium model of the interface K-Cs, containing especially the adhesive force between the two half-space jellia. (author). 23 refs, 1 fig
Penalty Algorithm Based on Conjugate Gradient Method for Solving Portfolio Management Problem
Directory of Open Access Journals (Sweden)
Wang YaLin
2009-01-01
Full Text Available A new approach was proposed to reformulate the biobjectives optimization model of portfolio management into an unconstrained minimization problem, where the objective function is a piecewise quadratic polynomial. We presented some properties of such an objective function. Then, a class of penalty algorithms based on the well-known conjugate gradient methods was developed to find the solution of portfolio management problem. By implementing the proposed algorithm to solve the real problems from the stock market in China, it was shown that this algorithm is promising.
Czech Academy of Sciences Publication Activity Database
Strakoš, Zdeněk; Tichý, Petr
2002-01-01
Roč. 13, - (2002), s. 56-80 ISSN 1068-9613 R&D Projects: GA ČR GA201/02/0595 Institutional research plan: AV0Z1030915 Keywords : conjugate gradient method * Gauss kvadrature * evaluation of convergence * error bounds * finite precision arithmetic * rounding errors * loss of orthogonality Subject RIV: BA - General Mathematics Impact factor: 0.565, year: 2002 http://etna.mcs.kent.edu/volumes/2001-2010/vol13/abstract.php?vol=13&pages=56-80
Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.
Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L
2002-09-01
We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.
International Nuclear Information System (INIS)
Andrei, Petru; Oniciuc, Liviu; Stancu, Alexandru; Stoleriu, Laurentiu
2007-01-01
An identification technique for the parameters of phenomenological models of hysteresis is presented. The basic idea of our technique is to set up a system of equations for the parameters of the model as a function of known quantities on the major or minor hysteresis loops (e.g. coercive force, susceptibilities at various points, remanence), or other magnetization curves. This system of equations can be either over or underspecified and is solved by using the conjugate gradient method. Numerical results related to the identification of parameters in the Energetic, Jiles-Atherton, and Preisach models are presented
Method of formation of a high gradient magnetic field and the device for division of substances
International Nuclear Information System (INIS)
Il'yashenko, E. I.; Glebov, V. A.; Skeltorp, A. T.
2005-01-01
Full text: The method and the device [1] are intended for use as a high-sensitivity magnetic separator for different types of paramagnetic substances and materials from diamagnetic ones, for division of paramagnetic substances and materials on the magnitudes of their paramagnetic susceptibility, for division of diamagnetic substances and materials on magnitudes of their diamagnetic susceptibility. Scopes: to produce pure and super pure substances and materials in electronics, metallurgy and chemistry, separation of biological objects (red blood cells, magnetic bacteria, etc.) in biology and medicine, water treatment removing heavy metals and organic impurities, etc. The main condition for magnetic separation is the magnetic force which acts on a particle of the substance and which is proportional to the magnetic susceptibility of the substance, magnetic induction B and gradient ∇B of the applied magnetic field. Therefore, to increase the sensitivity and selectivity of magnetic separation it will be required to use the largest possible values of the magnetic induction and the gradient of a magnetic field, or their product - B∇B. The device declared in the present work includes the magnetic system such as the open domain structure, consisting of permanent magnets with magnetic anisotropy much greater than the induction of a material of magnets. However, the declared device differs from the open domain structure in that [1]: *the surface of the neighbor poles of magnets is covered with a mask made from sheets of adjustable thickness of a soft magnetic material; *the soft magnetic material of the mask is selected on the basis of the magnitudes of the induction of saturation and magnetic permeability for achievement of the required magnitude of the induction and gradient of the magnetic field; *between the sheets of the mask there is an adjustable gap located symmetrically relative to the junction line of the magnets; *the size and the form of the gap between the
Piret, Cécile
2012-05-01
Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper, we investigate methods to solve PDEs on arbitrary stationary surfaces embedded in . R3 using the RBF method. We present three RBF-based methods that easily discretize surface differential operators. We take advantage of the meshfree character of RBFs, which give us a high accuracy and the flexibility to represent the most complex geometries in any dimension. Two out of the three methods, which we call the orthogonal gradients (OGr) methods are the result of our work and are hereby presented for the first time. © 2012 Elsevier Inc.
Yong, Peng; Liao, Wenyuan; Huang, Jianping; Li, Zhenchuan
2018-04-01
Full waveform inversion is an effective tool for recovering the properties of the Earth from seismograms. However, it suffers from local minima caused mainly by the limited accuracy of the starting model and the lack of a low-frequency component in the seismic data. Because of the high velocity contrast between salt and sediment, the relation between the waveform and velocity perturbation is strongly nonlinear. Therefore, salt inversion can easily get trapped in the local minima. Since the velocity of salt is nearly constant, we can make the most of this characteristic with total variation regularization to mitigate the local minima. In this paper, we develop an adaptive primal dual hybrid gradient method to implement total variation regularization by projecting the solution onto a total variation norm constrained convex set, through which the total variation norm constraint is satisfied at every model iteration. The smooth background velocities are first inverted and the perturbations are gradually obtained by successively relaxing the total variation norm constraints. Numerical experiment of the projection of the BP model onto the intersection of the total variation norm and box constraints has demonstrated the accuracy and efficiency of our adaptive primal dual hybrid gradient method. A workflow is designed to recover complex salt structures in the BP 2004 model and the 2D SEG/EAGE salt model, starting from a linear gradient model without using low-frequency data below 3 Hz. The salt inversion processes demonstrate that wavefield reconstruction inversion with a total variation norm and box constraints is able to overcome local minima and inverts the complex salt velocity layer by layer.
International Nuclear Information System (INIS)
Bakosi, Jozsef; Ristorcelli, Raymond J.
2010-01-01
Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.
A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary
Gillis, Nicolas; Luce, Robert
2018-01-01
A nonnegative matrix factorization (NMF) can be computed efficiently under the separability assumption, which asserts that all the columns of the given input data matrix belong to the cone generated by a (small) subset of them. The provably most robust methods to identify these conic basis columns are based on nonnegative sparse regression and self dictionaries, and require the solution of large-scale convex optimization problems. In this paper we study a particular nonnegative sparse regression model with self dictionary. As opposed to previously proposed models, this model yields a smooth optimization problem where the sparsity is enforced through linear constraints. We show that the Euclidean projection on the polyhedron defined by these constraints can be computed efficiently, and propose a fast gradient method to solve our model. We compare our algorithm with several state-of-the-art methods on synthetic data sets and real-world hyperspectral images.
A conjugate gradient method for solving the non-LTE line radiation transfer problem
Paletou, F.; Anterrieu, E.
2009-12-01
This study concerns the fast and accurate solution of the line radiation transfer problem, under non-LTE conditions. We propose and evaluate an alternative iterative scheme to the classical ALI-Jacobi method, and to the more recently proposed Gauss-Seidel and successive over-relaxation (GS/SOR) schemes. Our study is indeed based on applying a preconditioned bi-conjugate gradient method (BiCG-P). Standard tests, in 1D plane parallel geometry and in the frame of the two-level atom model with monochromatic scattering are discussed. Rates of convergence between the previously mentioned iterative schemes are compared, as are their respective timing properties. The smoothing capability of the BiCG-P method is also demonstrated.
Conjugate-gradient optimization method for orbital-free density functional calculations.
Jiang, Hong; Yang, Weitao
2004-08-01
Orbital-free density functional theory as an extension of traditional Thomas-Fermi theory has attracted a lot of interest in the past decade because of developments in both more accurate kinetic energy functionals and highly efficient numerical methodology. In this paper, we developed a conjugate-gradient method for the numerical solution of spin-dependent extended Thomas-Fermi equation by incorporating techniques previously used in Kohn-Sham calculations. The key ingredient of the method is an approximate line-search scheme and a collective treatment of two spin densities in the case of spin-dependent extended Thomas-Fermi problem. Test calculations for a quartic two-dimensional quantum dot system and a three-dimensional sodium cluster Na216 with a local pseudopotential demonstrate that the method is accurate and efficient. (c) 2004 American Institute of Physics.
Three-Dimensional Induced Polarization Parallel Inversion Using Nonlinear Conjugate Gradients Method
Directory of Open Access Journals (Sweden)
Huan Ma
2015-01-01
Full Text Available Four kinds of array of induced polarization (IP methods (surface, borehole-surface, surface-borehole, and borehole-borehole are widely used in resource exploration. However, due to the presence of large amounts of the sources, it will take much time to complete the inversion. In the paper, a new parallel algorithm is described which uses message passing interface (MPI and graphics processing unit (GPU to accelerate 3D inversion of these four methods. The forward finite differential equation is solved by ILU0 preconditioner and the conjugate gradient (CG solver. The inverse problem is solved by nonlinear conjugate gradients (NLCG iteration which is used to calculate one forward and two “pseudo-forward” modelings and update the direction, space, and model in turn. Because each source is independent in forward and “pseudo-forward” modelings, multiprocess modes are opened by calling MPI library. The iterative matrix solver within CULA is called in each process. Some tables and synthetic data examples illustrate that this parallel inversion algorithm is effective. Furthermore, we demonstrate that the joint inversion of surface and borehole data produces resistivity and chargeability results are superior to those obtained from inversions of individual surface data.
Use of the preconditioned conjugate gradient method to accelerate S/sub n/ iterations
International Nuclear Information System (INIS)
Derstine, K.L.; Gelbard, E.M.
1985-01-01
It is well known that specially tailored diffusion difference equations are required in the synthetic method. The tailoring process is not trivial, and for some S/sub n/ schemes (e.g., in hexagonal geometry) tailored diffusion operators are not available. The need for alternative acceleration methods has been noted by Larsen who has, in fact, proposed two alternatives. The proposed methods, however, do not converge to the S/sub n/ solution, and their accuracy is still largely unknown. Los Alamos acceleration methods are required to converge for any mesh, no matter how coarse. Since negative flux-fix ups (normally involved when mesh widths are large) may impede convergence, it is not clear that such a strict condition is really practical. Here a lesser objective is chosen. The authors wish to develop an acceleration method useful for a wide (though finite) range of mesh widths, but to avoid the use of special diffusion difference equations. It is shown that the conjugate gradient (CG) method, with the standard box-centered (BC) diffusion equation as a preconditioner, yields an algorithm that, for fixed-source problems with isotropic scattering, is mechanically very similar to the synthetic method; but, in two-dimensional test problems in various geometries, the CG method is substantially more stable
Projection and nested force-gradient methods for quantum field theories
Energy Technology Data Exchange (ETDEWEB)
Shcherbakov, Dmitry
2017-07-26
For the Hybrid Monte Carlo algorithm (HMC), often used to study the fundamental quantum field theory of quarks and gluons, quantum chromodynamics (QCD), on the lattice, one is interested in efficient numerical time integration schemes which preserve geometric properties of the flow and are optimal in terms of computational costs per trajectory for a given acceptance rate. High order numerical methods allow the use of larger step sizes, but demand a larger computational effort per step; low order schemes do not require such large computational costs per step, but need more steps per trajectory. So there is a need to balance these opposing effects. In this work we introduce novel geometric numerical time integrators, namely, projection and nested force-gradient methods in order to improve the efficiency of the HMC algorithm in application to the problems of quantum field theories.
He, Xiaowei; Liang, Jimin; Wang, Xiaorui; Yu, Jingjing; Qu, Xiaochao; Wang, Xiaodong; Hou, Yanbin; Chen, Duofang; Liu, Fang; Tian, Jie
2010-11-22
In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.
Energy Technology Data Exchange (ETDEWEB)
Shu, Yu-Chen, E-mail: ycshu@mail.ncku.edu.tw [Department of Mathematics, National Cheng Kung University, Tainan 701, Taiwan (China); Mathematics Division, National Center for Theoretical Sciences (South), Tainan 701, Taiwan (China); Chern, I-Liang, E-mail: chern@math.ntu.edu.tw [Department of Applied Mathematics, National Chiao Tung University, Hsin Chu 300, Taiwan (China); Department of Mathematics, National Taiwan University, Taipei 106, Taiwan (China); Mathematics Division, National Center for Theoretical Sciences (Taipei Office), Taipei 106, Taiwan (China); Chang, Chien C., E-mail: mechang@iam.ntu.edu.tw [Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan (China); Department of Mathematics, National Taiwan University, Taipei 106, Taiwan (China)
2014-10-15
Most elliptic interface solvers become complicated for complex interface problems at those “exceptional points” where there are not enough neighboring interior points for high order interpolation. Such complication increases especially in three dimensions. Usually, the solvers are thus reduced to low order accuracy. In this paper, we classify these exceptional points and propose two recipes to maintain order of accuracy there, aiming at improving the previous coupling interface method [26]. Yet the idea is also applicable to other interface solvers. The main idea is to have at least first order approximations for second order derivatives at those exceptional points. Recipe 1 is to use the finite difference approximation for the second order derivatives at a nearby interior grid point, whenever this is possible. Recipe 2 is to flip domain signatures and introduce a ghost state so that a second-order method can be applied. This ghost state is a smooth extension of the solution at the exceptional point from the other side of the interface. The original state is recovered by a post-processing using nearby states and jump conditions. The choice of recipes is determined by a classification scheme of the exceptional points. The method renders the solution and its gradient uniformly second-order accurate in the entire computed domain. Numerical examples are provided to illustrate the second order accuracy of the presently proposed method in approximating the gradients of the original states for some complex interfaces which we had tested previous in two and three dimensions, and a real molecule ( (1D63)) which is double-helix shape and composed of hundreds of atoms.
A self-reference PRF-shift MR thermometry method utilizing the phase gradient
International Nuclear Information System (INIS)
Langley, Jason; Potter, William; Phipps, Corey; Zhao Qun; Huang Feng
2011-01-01
In magnetic resonance (MR) imaging, the most widely used and accurate method for measuring temperature is based on the shift in proton resonance frequency (PRF). However, inter-scan motion and bulk magnetic field shifts can lead to inaccurate temperature measurements in the PRF-shift MR thermometry method. The self-reference PRF-shift MR thermometry method was introduced to overcome such problems by deriving a reference image from the heated or treated image, and approximates the reference phase map with low-order polynomial functions. In this note, a new approach is presented to calculate the baseline phase map in self-reference PRF-shift MR thermometry. The proposed method utilizes the phase gradient to remove the phase unwrapping step inherent to other self-reference PRF-shift MR thermometry methods. The performance of the proposed method was evaluated using numerical simulations with temperature distributions following a two-dimensional Gaussian function as well as phantom and in vivo experimental data sets. The results from both the numerical simulations and experimental data show that the proposed method is a promising technique for measuring temperature. (note)
Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis
Li, Y.
2013-05-01
The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.
Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients
Directory of Open Access Journals (Sweden)
Zemin Ren
2014-01-01
Full Text Available We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results.
International Nuclear Information System (INIS)
Maciejewski, W. J.
1985-01-01
A method and apparatus for measuring the differential or gradient of an earth variable within a well bore (e.g., the spontaneous earth potential) and producing improved logs of this gradient or differential and its integral variable essentially free of any accumulated instrument and base line drift or error. The differential spontaneous potential of an earth formation traversed by a well bore is measured at repeated multiple depths by moving a pair of closely spaced electrodes through the well bore wherein each electrode is electrically insulated externally from the other and from a third downhole local ground (such as the well tool cable) to which each is internally resistively referenced. The measured electrical potential across the closely spaced electrodes is amplified and digitized before being transmitted to the earth's surface, whereupon an averaged value of such differential measurements within a traveling data window of predetermined length and adjacent to each successive measurement is used to adjust for base line drift, noise and instrument induced error. The resulting compensated differential logs are integrated, resulting in spontaneous potential logs of improved character
Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images
International Nuclear Information System (INIS)
Mumcuglu, E.U.; Leahy, R.; Zhou, Z.; Cherry, S.R.
1994-01-01
The authors describe conjugate gradient algorithms for reconstruction of transmission and emission PET images. The reconstructions are based on a Bayesian formulation, where the data are modeled as a collection of independent Poisson random variables and the image is modeled using a Markov random field. A conjugate gradient algorithm is used to compute a maximum a posteriori (MAP) estimate of the image by maximizing over the posterior density. To ensure nonnegativity of the solution, a penalty function is used to convert the problem to one of unconstrained optimization. Preconditioners are used to enhance convergence rates. These methods generally achieve effective convergence in 15--25 iterations. Reconstructions are presented of an 18 FDG whole body scan from data collected using a Siemens/CTI ECAT931 whole body system. These results indicate significant improvements in emission image quality using the Bayesian approach, in comparison to filtered backprojection, particularly when reprojections of the MAP transmission image are used in place of the standard attenuation correction factors
Continuous Descent Operations using Energy Principles
De Jong, P.M.A.
2014-01-01
During today’s aircraft descents, Air Traf?c Control (ATC) commands aircraft to descend to specific altitudes and directions to maintain separation and spacing from other aircraft. When the aircraft is instructed to maintain an intermediate descent altitude, it requires engine thrust to maintain
International Nuclear Information System (INIS)
Fathizadeh, M.; Aroujalian, A.
2012-01-01
The boundary layer convective heat transfer equations with low pressure gradient over a flat plate are solved using Homotopy Perturbation Method, which is one of the semi-exact methods. The nonlinear equations of momentum and energy solved simultaneously via Homotopy Perturbation Method are in good agreement with results obtained from numerical methods. Using this method, a general equation in terms of Pr number and pressure gradient (λ) is derived which can be used to investigate velocity and temperature profiles in the boundary layer.
International Nuclear Information System (INIS)
Ohtakara, Kazuhiro; Hayashi, Shinya; Hoshi, Hiroaki
2011-01-01
The objective of our study was to describe the dose gradient characteristics of Linac-based stereotactic radiosurgery using Paddick's gradient index (GI) and to elucidate the factors influencing the GI value. Seventy-three plans for brain metastases using the dynamic conformal arcs were reviewed. The GI values were calculated at the 80% and 90% isodose surfaces (IDSs) and at the different target coverage IDSs (D99, D95, D90, and D85). The GI values significantly decreased as the target coverage of the reference IDS increased (the percentage of the IDS decreased). There was a significant inverse correlation between the GI values and target volume. The plans generated with the addition of a 1-mm leaf margin had worse GI values both at the D99 and D95 relative to those without leaf margin. The number and arrangement of arcs also affected the GI value. The GI values are highly sensitive to the IDS selection variability for dose prescription or evaluation, the target volume, and the planning method. To objectively compare the quality of dose gradient between rival plans, it would be preferable to employ the GI defined at the reference IDS indicating the specific target coverage (exempli gratia (e.g.), D95), irrespective of the intended marginal dose. The modified GI (mGI), defined in this study, substituting the denominator of the original GI with the target volume, would be useful to compensate for the false superior GI value in cases of target over-coverage with the reference IDS and to objectively evaluate the dose gradient outside the target boundary. (author)
Directory of Open Access Journals (Sweden)
Uttam Singh Baghel
2012-10-01
Full Text Available Objective: The aim of present work was to develop a gradient RP-HPLC method for simultaneous analysis of rosiglitazone and gliclazide, in a tablet dosage form. Method: Chromatographic system was optimized using a hypersil C18 (250mm x 4.6mm, 5毺 m column with potassium dihydrogen phosphate (pH-7.0 and acetonitrile in the ratio of 60:40, as mobile phase, at a flow rate of 1.0 ml/min. Detection was carried out at 225 nm by a SPD-20A prominence UV/Vis detector. Result: Rosiglitazone and gliclazide were eluted with retention times of 17.36 and 7.06 min, respectively. Beer’s Lambert ’s Law was obeyed over the concentration ranges of 5 to 70 毺 g/ml and 2 to 12 毺 g/ml for rosiglitazone and gliclazide, respectively. Conclusion: The high recovery and low coefficients of variation confirm the suitability of the method for simultaneous analysis of both drugs in a tablets dosage form. Statistical analysis proves that the method is sensitive and significant for the analysis of rosiglitazone and gliclazide in pure and in pharmaceutical dosage form without any interference from the excipients. The method was validated in accordance with ICH guidelines. Validation revealed the method is specific, rapid, accurate, precise, reliable, and reproducible.
International Nuclear Information System (INIS)
Biffle, J.H.
1991-01-01
1 - Description of program or function: JAC is a two-dimensional finite element program for solving large deformation, temperature dependent, quasi-static mechanics problems with the nonlinear conjugate gradient (CG) technique. Either plane strain or axisymmetric geometry may be used with material descriptions which include temperature dependent elastic-plastic, temperature dependent secondary creep, and isothermal soil models. The nonlinear effects examined include material and geometric nonlinearities due to large rotations, large strains, and surface which slide relative to one another. JAC is vectorized to perform efficiently on the Cray1 computer. A restart capability is included. 2 - Method of solution: The nonlinear conjugate gradient method is employed in a two-dimensional plane strain or axisymmetric setting with various techniques for accelerating convergence. Sliding interface conditions are also implemented. A four-node Lagrangian uniform strain element is used with orthogonal hourglass viscosity to control the zero energy modes. Three sets of continuum equations are needed - kinematic statements, constitutive equations, and equations of equilibrium - to describe the deformed configuration of the body. 3 - Restrictions on the complexity of the problem - Maxima of: 10 load and solution control functions, 4 materials. The strain rate is assumed constant over a time interval. Current large rotation theory is applicable to a maximum shear strain of 1.0. JAC should be used with caution for large shear strains. Problem size is limited only by available memory
Yeung, E.S.; Chen, G.
1990-05-01
A method and means are disclosed for a spatial and temporal probe for laser generated plumes based on density gradients includes generation of a plume of vaporized material from a surface by an energy source. The probe laser beam is positioned so that the plume passes through the probe laser beam. Movement of the probe laser beam caused by refraction from the density gradient of the plume is monitored. Spatial and temporal information, correlated to one another, is then derived. 15 figs.
A modified conjugate gradient method based on the Tikhonov system for computerized tomography (CT).
Wang, Qi; Wang, Huaxiang
2011-04-01
During the past few decades, computerized tomography (CT) was widely used for non-destructive testing (NDT) and non-destructive examination (NDE) in the industrial area because of its characteristics of non-invasiveness and visibility. Recently, CT technology has been applied to multi-phase flow measurement. Using the principle of radiation attenuation measurements along different directions through the investigated object with a special reconstruction algorithm, cross-sectional information of the scanned object can be worked out. It is a typical inverse problem and has always been a challenge for its nonlinearity and ill-conditions. The Tikhonov regulation method is widely used for similar ill-posed problems. However, the conventional Tikhonov method does not provide reconstructions with qualities good enough, the relative errors between the reconstructed images and the real distribution should be further reduced. In this paper, a modified conjugate gradient (CG) method is applied to a Tikhonov system (MCGT method) for reconstructing CT images. The computational load is dominated by the number of independent measurements m, and a preconditioner is imported to lower the condition number of the Tikhonov system. Both simulation and experiment results indicate that the proposed method can reduce the computational time and improve the quality of image reconstruction. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Kaporin, I. E.
2012-02-01
In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.
A primal sub-gradient method for structured classification with the averaged sum loss
Directory of Open Access Journals (Sweden)
Mančev Dejan
2014-12-01
Full Text Available We present a primal sub-gradient method for structured SVM optimization defined with the averaged sum of hinge losses inside each example. Compared with the mini-batch version of the Pegasos algorithm for the structured case, which deals with a single structure from each of multiple examples, our algorithm considers multiple structures from a single example in one update. This approach should increase the amount of information learned from the example. We show that the proposed version with the averaged sum loss has at least the same guarantees in terms of the prediction loss as the stochastic version. Experiments are conducted on two sequence labeling problems, shallow parsing and part-of-speech tagging, and also include a comparison with other popular sequential structured learning algorithms.
Accelerated gradient methods for the x-ray imaging of solar flares
Bonettini, S.; Prato, M.
2014-05-01
In this paper we present new optimization strategies for the reconstruction of x-ray images of solar flares by means of the data collected by the Reuven Ramaty high energy solar spectroscopic imager. The imaging concept of the satellite is based on rotating modulation collimator instruments, which allow the use of both Fourier imaging approaches and reconstruction techniques based on the straightforward inversion of the modulated count profiles. Although in the last decade, greater attention has been devoted to the former strategies due to their very limited computational cost, here we consider the latter model and investigate the effectiveness of different accelerated gradient methods for the solution of the corresponding constrained minimization problem. Moreover, regularization is introduced through either an early stopping of the iterative procedure, or a Tikhonov term added to the discrepancy function by means of a discrepancy principle accounting for the Poisson nature of the noise affecting the data.
International Nuclear Information System (INIS)
Huang, C.-H.; Wu, H.-H.
2006-01-01
In the present study an inverse hyperbolic heat conduction problem is solved by the conjugate gradient method (CGM) in estimating the unknown boundary heat flux based on the boundary temperature measurements. Results obtained in this inverse problem will be justified based on the numerical experiments where three different heat flux distributions are to be determined. Results show that the inverse solutions can always be obtained with any arbitrary initial guesses of the boundary heat flux. Moreover, the drawbacks of the previous study for this similar inverse problem, such as (1) the inverse solution has phase error and (2) the inverse solution is sensitive to measurement error, can be avoided in the present algorithm. Finally, it is concluded that accurate boundary heat flux can be estimated in this study
Mixed gradient-Tikhonov methods for solving nonlinear ill-posed problems in Banach spaces
International Nuclear Information System (INIS)
Margotti, Fábio
2016-01-01
Tikhonov regularization is a very useful and widely used method for finding stable solutions of ill-posed problems. A good choice of the penalization functional as well as a careful selection of the topologies of the involved spaces is fundamental to the quality of the reconstructions. These choices can be combined with some a priori information about the solution in order to preserve desired characteristics like sparsity constraints for example. To prove convergence and stability properties of this method, one usually has to assume that a minimizer of the Tikhonov functional is known. In practical situations however, the exact computation of a minimizer is very difficult and even finding an approximation can be a very challenging and expensive task if the involved spaces have poor convexity or smoothness properties. In this paper we propose a method to attenuate this gap between theory and practice, applying a gradient-like method to a Tikhonov functional in order to approximate a minimizer. Using only available information, we explicitly calculate a maximal step-size which ensures a monotonically decreasing error. The resulting algorithm performs only finitely many steps and terminates using the discrepancy principle. In particular the knowledge of a minimizer or even its existence does not need to be assumed. Under standard assumptions, we prove convergence and stability results in relatively general Banach spaces, and subsequently, test its performance numerically, reconstructing conductivities with sparsely located inclusions and different kinds of noise in the 2D electrical impedance tomography. (paper)
Missing value imputation in DNA microarrays based on conjugate gradient method.
Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh
2012-02-01
Analysis of gene expression profiles needs a complete matrix of gene array values; consequently, imputation methods have been suggested. In this paper, an algorithm that is based on conjugate gradient (CG) method is proposed to estimate missing values. k-nearest neighbors of the missed entry are first selected based on absolute values of their Pearson correlation coefficient. Then a subset of genes among the k-nearest neighbors is labeled as the best similar ones. CG algorithm with this subset as its input is then used to estimate the missing values. Our proposed CG based algorithm (CGimpute) is evaluated on different data sets. The results are compared with sequential local least squares (SLLSimpute), Bayesian principle component analysis (BPCAimpute), local least squares imputation (LLSimpute), iterated local least squares imputation (ILLSimpute) and adaptive k-nearest neighbors imputation (KNNKimpute) methods. The average of normalized root mean squares error (NRMSE) and relative NRMSE in different data sets with various missing rates shows CGimpute outperforms other methods. Copyright © 2011 Elsevier Ltd. All rights reserved.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Directory of Open Access Journals (Sweden)
Gonglin Yuan
Full Text Available Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1 βk ≥ 0 2 the search direction has the trust region property without the use of any line search method 3 the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.
Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou
2015-01-01
Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.
Standard Test Method for Measuring Heat Flux Using Flush-Mounted Insert Temperature-Gradient Gages
American Society for Testing and Materials. Philadelphia
2009-01-01
1.1 This test method describes the measurement of the net heat flux normal to a surface using gages inserted flush with the surface. The geometry is the same as heat-flux gages covered by Test Method E 511, but the measurement principle is different. The gages covered by this standard all use a measurement of the temperature gradient normal to the surface to determine the heat that is exchanged to or from the surface. Although in a majority of cases the net heat flux is to the surface, the gages operate by the same principles for heat transfer in either direction. 1.2 This general test method is quite broad in its field of application, size and construction. Two different gage types that are commercially available are described in detail in later sections as examples. A summary of common heat-flux gages is given by Diller (1). Applications include both radiation and convection heat transfer. The gages used for aerospace applications are generally small (0.155 to 1.27 cm diameter), have a fast time response ...
A primal–dual hybrid gradient method for nonlinear operators with applications to MRI
Valkonen, Tuomo
2014-05-01
We study the solution of minimax problems min xmax yG(x) + K(x), y - F*(y) in finite-dimensional Hilbert spaces. The functionals G and F* we assume to be convex, but the operator K we allow to be nonlinear. We formulate a natural extension of the modified primal-dual hybrid gradient method, originally for linear K, due to Chambolle and Pock. We prove the local convergence of the method, provided various technical conditions are satisfied. These include in particular the Aubin property of the inverse of a monotone operator at the solution. Of particular interest to us is the case arising from Tikhonov type regularization of inverse problems with nonlinear forward operators. Mainly we are interested in total variation and second-order total generalized variation priors. For such problems, we show that our general local convergence result holds when the noise level of the data f is low, and the regularization parameter α is correspondingly small. We verify the numerical performance of the method by applying it to problems from magnetic resonance imaging (MRI) in chemical engineering and medicine. The specific applications are in diffusion tensor imaging and MR velocity imaging. These numerical studies show very promising performance. © 2014 IOP Publishing Ltd.
International Nuclear Information System (INIS)
King, J.B.; Anghaie, S.; Domanus, H.M.
1987-01-01
Finite difference approximations to the continuity, momentum, and energy equations in thermal hydraulics codes result in a system of N by N equations for a problem having N field points. In a three dimensional problem, N increases as the problem becomes larger or more complex, and more rapidly as the computational mesh size is reduced. As a consequence, the execution time required to solve the problem increases, which may lead to placing limits on the problem resolution or accuracy. A conventinal method of solution of these systems of equations is the Successive Over Relaxation (SOR) technique. However, for a wide range of problems the execution time may be reduced by using a more efficient linear equation solver. One such method is the conjugate gradient method which was implemented in COMMIX-1B thermal hydraulics code. It was found that the execution time required to solve the resulting system of equations was reduced by a factor of about 2 for some problems. This paper summarizes the characteristics of these iterative solution procedures and compares their performance in modeling of a variety of reactor thermal hydraulic problems, using the COMMIX-1B computer code
Adjustment technique without explicit formation of normal equations /conjugate gradient method/
Saxena, N. K.
1974-01-01
For a simultaneous adjustment of a large geodetic triangulation system, a semiiterative technique is modified and used successfully. In this semiiterative technique, known as the conjugate gradient (CG) method, original observation equations are used, and thus the explicit formation of normal equations is avoided, 'huge' computer storage space being saved in the case of triangulation systems. This method is suitable even for very poorly conditioned systems where solution is obtained only after more iterations. A detailed study of the CG method for its application to large geodetic triangulation systems was done that also considered constraint equations with observation equations. It was programmed and tested on systems as small as two unknowns and three equations up to those as large as 804 unknowns and 1397 equations. When real data (573 unknowns, 965 equations) from a 1858-km-long triangulation system were used, a solution vector accurate to four decimal places was obtained in 2.96 min after 1171 iterations (i.e., 2.0 times the number of unknowns).
A numerical method for solving singular De`s
Energy Technology Data Exchange (ETDEWEB)
Mahaver, W.T.
1996-12-31
A numerical method is developed for solving singular differential equations using steepest descent based on weighted Sobolev gradients. The method is demonstrated on a variety of first and second order problems, including linear constrained, unconstrained, and partially constrained first order problems, a nonlinear first order problem with irregular singularity, and two second order variational problems.
Adamski,Tadeusz; Krystkowiak,Karolina; Kuczynska,Anetta; Mikolajczak,Krzysztof; Ogrodowicz,Piotr; Ponitka,Aleksandra; Surma,Maria; Slusarkiewicz-Jarzina,Aurelia
2014-01-01
Background: The quality of wheat grain depends on several characteristics, among which the composition of high molecular weight glutenin subunits, encoded by Glu-1 loci, are the most important. Application of biotechnological tools to accelerate the attainment of homozygous lines may influence the proportion of segregated genotypes. The objective was to determine, whether the selection pressure generated by the methods based on in vitro cultures, may cause a loss of genotypes with desirable G...
Calibration of groundwater vulnerability mapping using the generalized reduced gradient method.
Elçi, Alper
2017-12-01
Groundwater vulnerability assessment studies are essential in water resources management. Overlay-and-index methods such as DRASTIC are widely used for mapping of groundwater vulnerability, however, these methods mainly suffer from a subjective selection of model parameters. The objective of this study is to introduce a calibration procedure that results in a more accurate assessment of groundwater vulnerability. The improvement of the assessment is formulated as a parameter optimization problem using an objective function that is based on the correlation between actual groundwater contamination and vulnerability index values. The non-linear optimization problem is solved with the generalized-reduced-gradient (GRG) method, which is numerical algorithm based optimization method. To demonstrate the applicability of the procedure, a vulnerability map for the Tahtali stream basin is calibrated using nitrate concentration data. The calibration procedure is easy to implement and aims the maximization of correlation between observed pollutant concentrations and groundwater vulnerability index values. The influence of each vulnerability parameter in the calculation of the vulnerability index is assessed by performing a single-parameter sensitivity analysis. Results of the sensitivity analysis show that all factors are effective on the final vulnerability index. Calibration of the vulnerability map improves the correlation between index values and measured nitrate concentrations by 19%. The regression coefficient increases from 0.280 to 0.485. It is evident that the spatial distribution and the proportions of vulnerability class areas are significantly altered with the calibration process. Although the applicability of the calibration method is demonstrated on the DRASTIC model, the applicability of the approach is not specific to a certain model and can also be easily applied to other overlay-and-index methods. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Bozkaya, Uğur; Sherrill, C. David
2016-01-01
An efficient implementation is presented for analytic gradients of the coupled-cluster singles and doubles (CCSD) method with the density-fitting approximation, denoted DF-CCSD. Frozen core terms are also included. When applied to a set of alkanes, the DF-CCSD analytic gradients are significantly accelerated compared to conventional CCSD for larger molecules. The efficiency of our DF-CCSD algorithm arises from the acceleration of several different terms, which are designated as the “gradient terms”: computation of particle density matrices (PDMs), generalized Fock-matrix (GFM), solution of the Z-vector equation, formation of the relaxed PDMs and GFM, back-transformation of PDMs and GFM to the atomic orbital (AO) basis, and evaluation of gradients in the AO basis. For the largest member of the alkane set (C 10 H 22 ), the computational times for the gradient terms (with the cc-pVTZ basis set) are 2582.6 (CCSD) and 310.7 (DF-CCSD) min, respectively, a speed up of more than 8-folds. For gradient related terms, the DF approach avoids the usage of four-index electron repulsion integrals. Based on our previous study [U. Bozkaya, J. Chem. Phys. 141, 124108 (2014)], our formalism completely avoids construction or storage of the 4-index two-particle density matrix (TPDM), using instead 2- and 3-index TPDMs. The DF approach introduces negligible errors for equilibrium bond lengths and harmonic vibrational frequencies.
Energy Technology Data Exchange (ETDEWEB)
Zou, Wenli; Filatov, Michael; Cremer, Dieter, E-mail: dcremer@smu.edu [Computational and Theoretical Chemistry Group (CATCO), Department of Chemistry, Southern Methodist University, 3215 Daniel Ave, Dallas, Texas 75275-0314 (United States)
2015-06-07
The analytical gradient for the two-component Normalized Elimination of the Small Component (2c-NESC) method is presented. The 2c-NESC is a Dirac-exact method that employs the exact two-component one-electron Hamiltonian and thus leads to exact Dirac spin-orbit (SO) splittings for one-electron atoms. For many-electron atoms and molecules, the effect of the two-electron SO interaction is modeled by a screened nucleus potential using effective nuclear charges as proposed by Boettger [Phys. Rev. B 62, 7809 (2000)]. The effect of spin-orbit coupling (SOC) on molecular geometries is analyzed utilizing the properties of the frontier orbitals and calculated SO couplings. It is shown that bond lengths can either be lengthened or shortened under the impact of SOC where in the first case the influence of low lying excited states with occupied antibonding orbitals plays a role and in the second case the jj-coupling between occupied antibonding and unoccupied bonding orbitals dominates. In general, the effect of SOC on bond lengths is relatively small (≤5% of the scalar relativistic changes in the bond length). However, large effects are found for van der Waals complexes Hg{sub 2} and Cn{sub 2}, which are due to the admixture of more bonding character to the highest occupied spinors.
Zou, Wenli; Filatov, Michael; Cremer, Dieter
2015-06-01
The analytical gradient for the two-component Normalized Elimination of the Small Component (2c-NESC) method is presented. The 2c-NESC is a Dirac-exact method that employs the exact two-component one-electron Hamiltonian and thus leads to exact Dirac spin-orbit (SO) splittings for one-electron atoms. For many-electron atoms and molecules, the effect of the two-electron SO interaction is modeled by a screened nucleus potential using effective nuclear charges as proposed by Boettger [Phys. Rev. B 62, 7809 (2000)]. The effect of spin-orbit coupling (SOC) on molecular geometries is analyzed utilizing the properties of the frontier orbitals and calculated SO couplings. It is shown that bond lengths can either be lengthened or shortened under the impact of SOC where in the first case the influence of low lying excited states with occupied antibonding orbitals plays a role and in the second case the jj-coupling between occupied antibonding and unoccupied bonding orbitals dominates. In general, the effect of SOC on bond lengths is relatively small (≤5% of the scalar relativistic changes in the bond length). However, large effects are found for van der Waals complexes Hg2 and Cn2, which are due to the admixture of more bonding character to the highest occupied spinors.
Applying the Weighted Horizontal Magnetic Gradient Method to a Simulated Flaring Active Region
Korsós, M. B.; Chatterjee, P.; Erdélyi, R.
2018-04-01
Here, we test the weighted horizontal magnetic gradient (WG M ) as a flare precursor, introduced by Korsós et al., by applying it to a magnetohydrodynamic (MHD) simulation of solar-like flares. The preflare evolution of the WG M and the behavior of the distance parameter between the area-weighted barycenters of opposite-polarity sunspots at various heights is investigated in the simulated δ-type sunspot. Four flares emanated from this sunspot. We found the optimum heights above the photosphere where the flare precursors of the WG M method are identifiable prior to each flare. These optimum heights agree reasonably well with the heights of the occurrence of flares identified from the analysis of their thermal and ohmic heating signatures in the simulation. We also estimated the expected time of the flare onsets from the duration of the approaching–receding motion of the barycenters of opposite polarities before each single flare. The estimated onset time and the actual time of occurrence of each flare are in good agreement at the corresponding optimum heights. This numerical experiment further supports the use of flare precursors based on the WG M method.
Generalized conjugate-gradient methods for the Navier-Stokes equations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1991-01-01
A generalized conjugate-gradient method is used to solve the two-dimensional, compressible Navier-Stokes equations of fluid flow. The equations are discretized with an implicit, upwind finite-volume formulation. Preconditioning techniques are incorporated into the new solver to accelerate convergence of the overall iterative method. The superiority of the new solver is demonstrated by comparisons with a conventional line Gauss-Siedel Relaxation solver. Computational test results for transonic flow (trailing edge flow in a transonic turbine cascade) and hypersonic flow (M = 6.0 shock-on-shock phenoena on a cylindrical leading edge) are presented. When applied to the transonic cascade case, the new solver is 4.4 times faster in terms of number of iterations and 3.1 times faster in terms of CPU time than the Relaxation solver. For the hypersonic shock case, the new solver is 3.0 times faster in terms of number of iterations and 2.2 times faster in terms of CPU time than the Relaxation solver.
Directory of Open Access Journals (Sweden)
Faming Zhang
2016-11-01
Full Text Available The prediction of travel times is challenging because of the sparseness of real-time traffic data and the intrinsic uncertainty of travel on congested urban road networks. We propose a new gradient–boosted regression tree method to accurately predict travel times. This model accounts for spatiotemporal correlations extracted from historical and real-time traffic data for adjacent and target links. This method can deliver high prediction accuracy by combining simple regression trees with poor performance. It corrects the error found in existing models for improved prediction accuracy. Our spatiotemporal gradient–boosted regression tree model was verified in experiments. The training data were obtained from big data reflecting historic traffic conditions collected by probe vehicles in Wuhan from January to May 2014. Real-time data were extracted from 11 weeks of GPS records collected in Wuhan from 5 May 2014 to 20 July 2014. Based on these data, we predicted link travel time for the period from 21 July 2014 to 25 July 2014. Experiments showed that our proposed spatiotemporal gradient–boosted regression tree model obtained better results than gradient boosting, random forest, or autoregressive integrated moving average approaches. Furthermore, these results indicate the advantages of our model for urban link travel time prediction.
Chowdhary, J; Keyes, T
2002-02-01
Instantaneous normal modes (INM's) are calculated during a conjugate-gradient (CG) descent of the potential energy landscape, starting from an equilibrium configuration of a liquid or crystal. A small number (approximately equal to 4) of CG steps removes all the Im-omega modes in the crystal and leaves the liquid with diffusive Im-omega which accurately represent the self-diffusion constant D. Conjugate gradient filtering appears to be a promising method, applicable to any system, of obtaining diffusive modes and facilitating INM theory of D. The relation of the CG-step dependent INM quantities to the landscape and its saddles is discussed.
Propulsive Descent Technologies (PDT): Original Content Project
National Aeronautics and Space Administration — Future missions to Mars require landed mass that exceeds the capability of current entry, descent, and landing technology. New technology and techniques are...
Steepest descent approximations for accretive operator equations
International Nuclear Information System (INIS)
Chidume, C.E.
1993-03-01
A necessary and sufficient condition is established for the strong convergence of the steepest descent approximation to a solution of equations involving quasi-accretive operators defined on a uniformly smooth Banach space. (author). 49 refs
Directory of Open Access Journals (Sweden)
Lu Yang
2018-01-01
Full Text Available Downward shortwave radiation (DSR is an essential parameter in the terrestrial radiation budget and a necessary input for models of land-surface processes. Although several radiation products using satellite observations have been released, coarse spatial resolution and low accuracy limited their application. It is important to develop robust and accurate retrieval methods with higher spatial resolution. Machine learning methods may be powerful candidates for estimating the DSR from remotely sensed data because of their ability to perform adaptive, nonlinear data fitting. In this study, the gradient boosting regression tree (GBRT was employed to retrieve DSR measurements with the ground observation data in China collected from the China Meteorological Administration (CMA Meteorological Information Center and the satellite observations from the Advanced Very High Resolution Radiometer (AVHRR at a spatial resolution of 5 km. The validation results of the DSR estimates based on the GBRT method in China at a daily time scale for clear sky conditions show an R2 value of 0.82 and a root mean square error (RMSE value of 27.71 W·m−2 (38.38%. These values are 0.64 and 42.97 W·m−2 (34.57%, respectively, for cloudy sky conditions. The monthly DSR estimates were also evaluated using ground measurements. The monthly DSR estimates have an overall R2 value of 0.92 and an RMSE of 15.40 W·m−2 (12.93%. Comparison of the DSR estimates with the reanalyzed and retrieved DSR measurements from satellite observations showed that the estimated DSR is reasonably accurate but has a higher spatial resolution. Moreover, the proposed GBRT method has good scalability and is easy to apply to other parameter inversion problems by changing the parameters and training data.
Czech Academy of Sciences Publication Activity Database
Gutknecht, M. H.; Rozložník, Miroslav
2002-01-01
Roč. 41, - (2002), s. 7-22 ISSN 0168-9274 R&D Projects: GA AV ČR IAA1030103; GA ČR GA101/00/1035 Institutional research plan: AV0Z1030915 Keywords : sparse linear systems * Krylov space method * orthogonal residual method * minimal residual method * conjugate gradient method * residual smoothing * CG * CGNE * CGNR * CR * FOM * GMRES * PRES Subject RIV: BA - General Mathematics Impact factor: 0.504, year: 2002
Sun, Qi; Fu, Shujun
2017-09-20
Fringe orientation is an important feature of fringe patterns and has a wide range of applications such as guiding fringe pattern filtering, phase unwrapping, and abstraction. Estimating fringe orientation is a basic task for subsequent processing of fringe patterns. However, various noise, singular and obscure points, and orientation data degeneration lead to inaccurate calculations of fringe orientation. Thus, to deepen the understanding of orientation estimation and to better guide orientation estimation in fringe pattern processing, some advanced gradient-field-based orientation estimation methods are compared and analyzed. At the same time, following the ideas of smoothing regularization and computing of bigger gradient fields, a regularized singular-value decomposition (RSVD) technique is proposed for fringe orientation estimation. To compare the performance of these gradient-field-based methods, quantitative results and visual effect maps of orientation estimation are given on simulated and real fringe patterns that demonstrate that the RSVD produces the best estimation results at a cost of relatively less time.
Energy Technology Data Exchange (ETDEWEB)
Ledermüller, Katrin; Schütz, Martin, E-mail: martin.schuetz@chemie.uni-regensburg.de [Institute of Physical and Theoretical Chemistry, University of Regensburg, Universitätsstraße 31, D-93040 Regensburg (Germany)
2014-04-28
A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest.
Ledermüller, Katrin; Schütz, Martin
2014-04-28
A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest.
International Nuclear Information System (INIS)
Ledermüller, Katrin; Schütz, Martin
2014-01-01
A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest
Experience with the Incomplete Cholesky Conjugate Gradient method in a diffusion code
International Nuclear Information System (INIS)
Hoebel, W.
1985-01-01
For the numerical solution of sparse systems of linear equations arising from finite difference approximation of the multidimensional neutron diffusion equation fast methods are needed. Effective algorithms for scalar computers may not be likewise suitable on vector computers. In the improved version DIXY2 of the Karlsruhe two-dimensional neutron diffusion code for rectangular geometries an Incomplete Cholesky Conjugate Gradient (ICCG) algorithm has been combined with the originally implemented Cyclically Reduced 4-Lines SOR (CR4LSOR) inner iteration method. The combined procedure is automatically activated for slowly converging applications, thus leading to a drastic reduction of iterations as well as CPU-times on a scalar computer. In a follow-up benchmark study necessary modifications to ICCG and CR4LSOR for their use on a vector computer were investigated. It was found that a modified preconditioning for the ICCG algorithm restricted to the block diagonal matrix is an effective method both on scalar and vector computers. With a splitting of the 9-band-matrix in two triangular Cholesky matrices necessary inversions are performed on a scalar machine by recursive forward and backward substitutions. On vector computers an additional factorization of the triangular matrices into four bidiagonal matrices enables Buneman reduction and the recursive inversion is restricted to a small system. A similar strategy can be realized with CR4LSOR if the unvectorizable Gauss-Seidel iteration is replaced by Double Jacobi and Buneman technique for a vector computer. Compared to single line blocking over the original mesh the cyclical 4-lines reduction of the DIXY inner iteration scheme reduces numbers of iterations and CPU-times considerably
Experience with the incomplete Cholesky conjugate gradient method in a diffusion code
International Nuclear Information System (INIS)
Hoebel, W.
1986-01-01
For the numerical solution of sparse systems of linear equations arising from the finite difference approximation of the multidimensional neutron diffusion equation, fast methods are needed. Effective algorithms for scalar computers may not be likewise suitable on vector computers. In the improved version (DIXY2) of the Karlsruhe two-dimensional neutron diffusion code for rectangular geometries, an incomplete Cholesky conjugate gradient (ICCG) algorithm has been combined with the originally implemented cyclically reduced four-line successive overrelaxation (CR4LSOR) inner iteration method. The combined procedure is automatically activated for slowly converging applications, thus leading to a drastic reduction of iterations as well as CPU times on a scalar computer. In a follow-up benchmark study, necessary modifications to ICCG and CR4LSOR for use on a vector computer were investigated. It was found that a modified preconditioning for the ICCG algorithm restricted to the block diagonal matrix is an effective method both on scalar and vector computers. With a splitting of the nine-band matrix in two triangular Cholesky matrices, necessary inversions are performed on a scalar machine by recursive forward and backward substitutions. On vector computers an additional factorization of the triangular matrices into four bidiagonal matrices enables Buneman reduction, and the recursive inversion is restricted to a small system. A similar strategy can be realized with CR4LSOR if the unvectorizable Gauss-eidel iteration is replaced by Double Jacobi and Buneman techniques for a vector computer. Compared to single-line blocking over the original mesh, the cyclical four-line reduction of the DIXY inner iteration scheme reduces numbers of iterations and CPU times considerably
Solving groundwater flow problems by conjugate-gradient methods and the strongly implicit procedure
Hill, Mary C.
1990-01-01
The performance of the preconditioned conjugate-gradient method with three preconditioners is compared with the strongly implicit procedure (SIP) using a scalar computer. The preconditioners considered are the incomplete Cholesky (ICCG) and the modified incomplete Cholesky (MICCG), which require the same computer storage as SIP as programmed for a problem with a symmetric matrix, and a polynomial preconditioner (POLCG), which requires less computer storage than SIP. Although POLCG is usually used on vector computers, it is included here because of its small storage requirements. In this paper, published comparisons of the solvers are evaluated, all four solvers are compared for the first time, and new test cases are presented to provide a more complete basis by which the solvers can be judged for typical groundwater flow problems. Based on nine test cases, the following conclusions are reached: (1) SIP is actually as efficient as ICCG for some of the published, linear, two-dimensional test cases that were reportedly solved much more efficiently by ICCG; (2) SIP is more efficient than other published comparisons would indicate when common convergence criteria are used; and (3) for problems that are three-dimensional, nonlinear, or both, and for which common convergence criteria are used, SIP is often more efficient than ICCG, and is sometimes more efficient than MICCG.
3D DC Resistivity Inversion with Topography Based on Regularized Conjugate Gradient Method
Directory of Open Access Journals (Sweden)
Jian-ke Qiang
2013-01-01
Full Text Available During the past decades, we observed a strong interest in 3D DC resistivity inversion and imaging with complex topography. In this paper, we implemented 3D DC resistivity inversion based on regularized conjugate gradient method with FEM. The Fréchet derivative is assembled with the electric potential in order to speed up the inversion process based on the reciprocity theorem. In this study, we also analyzed the sensitivity of the electric potential on the earth’s surface to the conductivity in each cell underground and introduced an optimized weighting function to produce new sensitivity matrix. The synthetic model study shows that this optimized weighting function is helpful to improve the resolution of deep anomaly. By incorporating topography into inversion, the artificial anomaly which is actually caused by topography can be eliminated. As a result, this algorithm potentially can be applied to process the DC resistivity data collected in mountain area. Our synthetic model study also shows that the convergence and computation speed are very stable and fast.
Optimization of gadolinium burnable poison loading by the conjugate gradients method
International Nuclear Information System (INIS)
Drumm, C.R.
1984-01-01
Improved use of burnable poison is suggested for pressurized water reactors (PWR's) to insure a sufficiently negative moderator temperature coefficient of reactivity for extended burnup cycles and low leakage refueling patterns. The use of gadolinium as a burnable poison can lead to large axial fluctuations in the power distribution through the cycle. The goal of this work is to determine the optimal axial distribution of gadolinium burnable poison in a PWR to overcome the axial fluctuations, yielding an improved power distribution. The conjugate gradients optimization method is used in this work because of the high degree of nonlinearity of the problem. The neutron diffusion and depletion equations are solved for a one-dimensional one-group core model. The state variables are the flux, the critical soluble boron concentration, and the burnup. The control variables are the number of gadolinium pins per assembly and the beginning-of-cycle gadolinium concentration, which determine the gadolinium cross section. Two separate objectives are considered: 1) to minimize the power peaking factor, which will minimize the capital cost of the plant; and 2) to maximize the cycle length, which will minimize the fuel cost for the plant. It is shown in this work that optimizing the gadolinium distribution can yield an improved power distribution
Zou, Wenli; Filatov, Michael; Cremer, Dieter
2011-01-01
The analytical energy gradient of the normalized elimination of the small component (NESC) method is derived for the first time and implemented for the routine calculation of NESC geometries and other first order molecular properties. Essential for the derivation is the correct calculation of the
DEFF Research Database (Denmark)
Paidarová, Ivana; Sauer, Stephan P. A.
2012-01-01
We have compared the performance of density functional theory (DFT) using five different exchange-correlation functionals with four coupled cluster theory based wave function methods in the calculation of geometrical derivatives of the polarizability tensor of methane. The polarizability gradient...
International Nuclear Information System (INIS)
Oh, C.H.; Cho, Z.H.; California Univ., Irvine
1986-01-01
A new phase coding method using a selection gradient for high speed NMR flow velocity measurements is introduced and discussed. To establish a phase-velocity relationship of flow under the slice selection gradient and spin-echo RF pulse, the Bloch equation was numerically solved under the assumption that only one directional flow exists, i.e. in the direction of slice selection. Details of the numerical solution of the Bloch equation and techniques related to the numerical computations are also given. Finally, using the numerical calculation, high speed flow velocity measurement was attempted and found to be in good agreement with other complementary controlled measurements. (author)
Directory of Open Access Journals (Sweden)
Shoubin Wang
2017-01-01
Full Text Available The compound variable inverse problem which comprises boundary temperature distribution and surface convective heat conduction coefficient of two-dimensional steady heat transfer system with inner heat source is studied in this paper applying the conjugate gradient method. The introduction of complex variable to solve the gradient matrix of the objective function obtains more precise inversion results. This paper applies boundary element method to solve the temperature calculation of discrete points in forward problems. The factors of measuring error and the number of measuring points zero error which impact the measurement result are discussed and compared with L-MM method in inverse problems. Instance calculation and analysis prove that the method applied in this paper still has good effectiveness and accuracy even if measurement error exists and the boundary measurement points’ number is reduced. The comparison indicates that the influence of error on the inversion solution can be minimized effectively using this method.
International Nuclear Information System (INIS)
Bjorgaard, J. A.; Velizhanin, K. A.; Tretiak, S.
2015-01-01
This study describes variational energy expressions and analytical excited state energy gradients for time-dependent self-consistent field methods with polarizable solvent effects. Linear response, vertical excitation, and state-specific solventmodels are examined. Enforcing a variational ground stateenergy expression in the state-specific model is found to reduce it to the vertical excitation model. Variational excited state energy expressions are then provided for the linear response and vertical excitation models and analytical gradients are formulated. Using semiempiricalmodel chemistry, the variational expressions are verified by numerical and analytical differentiation with respect to a static external electric field. Lastly, analytical gradients are further tested by performing microcanonical excited state molecular dynamics with p-nitroaniline
International Nuclear Information System (INIS)
Kobayashi, Fujio; Yamaguchi, Shoichiro
1982-01-01
A method of the reconstruction of computed tomographic images was proposed to reduce the exposure dose to X-ray. The method is the small number of X-ray projection method by accelerative gradient method. The procedures of computation are described. The algorithm of these procedures is simple, the convergence of the computation is fast, and the required memory capacity is small. Numerical simulation was carried out to conform the validity of this method. A sample of simple shape was considered, projection data were given, and the images were reconstructed from 6 views. Good results were obtained, and the method is considered to be useful. (Kato, T.)
Preconditioned conjugate-gradient methods for low-speed flow calculations
Ajmani, Kumud; Ng, Wing-Fai; Liou, Meng-Sing
1993-01-01
An investigation is conducted into the viability of using a generalized Conjugate Gradient-like method as an iterative solver to obtain steady-state solutions of very low-speed fluid flow problems. Low-speed flow at Mach 0.1 over a backward-facing step is chosen as a representative test problem. The unsteady form of the two dimensional, compressible Navier-Stokes equations is integrated in time using discrete time-steps. The Navier-Stokes equations are cast in an implicit, upwind finite-volume, flux split formulation. The new iterative solver is used to solve a linear system of equations at each step of the time-integration. Preconditioning techniques are used with the new solver to enhance the stability and convergence rate of the solver and are found to be critical to the overall success of the solver. A study of various preconditioners reveals that a preconditioner based on the Lower-Upper Successive Symmetric Over-Relaxation iterative scheme is more efficient than a preconditioner based on Incomplete L-U factorizations of the iteration matrix. The performance of the new preconditioned solver is compared with a conventional Line Gauss-Seidel Relaxation (LGSR) solver. Overall speed-up factors of 28 (in terms of global time-steps required to converge to a steady-state solution) and 20 (in terms of total CPU time on one processor of a CRAY-YMP) are found in favor of the new preconditioned solver, when compared with the LGSR solver.
A temporal subtraction method for thoracic CT images based on generalized gradient vector flow
International Nuclear Information System (INIS)
Miyake, Noriaki; Kim, H.; Maeda, Shinya; Itai, Yoshinori; Tan, J.K.; Ishikawa, Seiji; Katsuragawa, Shigehiko
2010-01-01
A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes (such as formation of new lesions and changes in existing abnormalities) on medical images by removing most of the normal structures. If image registration is incorrect, not only the interval changes but also the normal structures would be appeared as some artifacts on the temporal subtraction image. In a temporal subtraction technique for 2-D X-ray image, the effectiveness is shown through a lot of clinical evaluation experiments, and practical use is advancing. Moreover, the MDCT (Multi-Detector row Computed Tomography) can easily introduced on medical field, the development of a temporal subtraction for thoracic CT Images is expected. In our study, a temporal subtraction technique for thoracic CT Images is developed. As the technique, the vector fields are described by use of GGVF (Generalized Gradient Vector Flow) from the previous and current CT images. Afterwards, VOI (Volume of Interest) are set up on the previous and current CT image pairs. The shift vectors are calculated by using nearest neighbor matching of the vector fields in these VOIs. The search kernel on previous CT image is set up from the obtained shift vector. The previous CT voxel which resemble standard the current voxel is detected by voxel value and vector of the GGVF in the kernel. And, the previous CT image is transformed to the same coordinate of standard voxel. Finally, temporal subtraction image is made by subtraction of a warping image from a current one. To verify the proposal method, the result of application to 7 cases and the effectiveness are described. (author)
Porous materials with gradient and biporous structure, methods of their production
International Nuclear Information System (INIS)
Ilyuschenko, A.; Savich, V.; Pilinevich, L.; Rak, A.
2001-01-01
We have worked out the technology of production porous powder materials (PPMs) of bronze, nickel, corrosion resistant steel and titanium powders with gradient and (or) biporous structure: vibrating forming of metal powders (including in electromagnetic field); layer-by-layer forming of metal powders with pore-maker while different proportion of the latter in the layer; forming of powder polymer layer on the preliminary sintered metal PPM surface. We have worked out the technology of production biporous structure by the following methods: metal granules forming and sintering; forming and sintering of metal powder with granules (2-3 mm) and pores-forming powder (size of particles is 0,4-0,63 mm). The novelty is in creation of technological bases of pores sizes regulation from 5 mkm on one PPM surface to 120 mkm on the opposite PPM surface which thickness can be 2-6 mm. PPM porosity can be constant within 0,3-0,6 relative units. More effective are those PPM which pores sizes are changeable and also porosity (from 0,35 to 0,60) from one surface o the opposite one. Two-layer metal-polymer PPM have pores sizes of 20-40 mkm in polymer layer and porosity 0,4-0,5 and, correspondingly, in metal layer 80-100 mkm and 0,45-0,55. In biporous structures made of 2-3 mm metal granules the distance between granules is 300-600 mkm and in granules - 14-30 mkm. The integral porosity of such PPM is 0,55-0,70. The technology of forming and sintering metal powder with granules and pores-making powder (carbamide) enables to regulate the integral porosity within 0,7-0,8 and average pores sizes within 100-1000 mkm with average size of metal powder particles of 0,63-1,0 mm. (author)
Directory of Open Access Journals (Sweden)
Hao Shi
2018-02-01
Full Text Available With the rapid development of remote sensing technologies, SAR satellites like China’s Gaofen-3 satellite have more imaging modes and higher resolution. With the availability of high-resolution SAR images, automatic ship target detection has become an important topic in maritime research. In this paper, a novel ship detection method based on gradient and integral features is proposed. This method is mainly composed of three steps. First, in the preprocessing step, a filter is employed to smooth the clutters and the smoothing effect can be adaptive adjusted according to the statistics information of the sub-window. Thus, it can retain details while achieving noise suppression. Second, in the candidate area extraction, a sea-land segmentation method based on gradient enhancement is presented. The integral image method is employed to accelerate computation. Finally, in the ship target identification step, a feature extraction strategy based on Haar-like gradient information and a Radon transform is proposed. This strategy decreases the number of templates found in traditional Haar-like methods. Experiments were performed using Gaofen-3 single-polarization SAR images, and the results showed that the proposed method has high detection accuracy and rapid computational efficiency. In addition, this method has the potential for on-board processing.
International Nuclear Information System (INIS)
Dinh Nho Hao; Nguyen Trung Thanh; Sahli, Hichem
2008-01-01
In this paper we consider a multi-dimensional inverse heat conduction problem with time-dependent coefficients in a box, which is well-known to be severely ill-posed, by a variational method. The gradient of the functional to be minimized is obtained by aids of an adjoint problem and the conjugate gradient method with a stopping rule is then applied to this ill-posed optimization problem. To enhance the stability and the accuracy of the numerical solution to the problem we apply this scheme to the discretized inverse problem rather than to the continuous one. The difficulties with large dimensions of discretized problems are overcome by a splitting method which only requires the solution of easy-to-solve one-dimensional problems. The numerical results provided by our method are very good and the techniques seem to be very promising.
Gradient heat flux measurement as monitoring method for the diesel engine
Sapozhnikov, S. Z.; Mityakov, V. Yu; Mityakov, A. V.; Vintsarevich, A. V.; Pavlov, A. V.; Nalyotov, I. D.
2017-11-01
The usage of gradient heat flux measurement for monitoring of heat flux on combustion chamber surface and optimization of diesel work process is proposed. Heterogeneous gradient heat flux sensors can be used at various regimes for an appreciable length of time. Fuel injection timing is set by the position of the maximum point on the angular heat flux diagram however, the value itself of the heat flux may not be considered. The development of such an approach can be productive for remote monitoring of work process in the cylinders of high-power marine engines.
Bell, Robert T; Jacobs, Alan G; Sorg, Victoria C; Jung, Byungki; Hill, Megan O; Treml, Benjamin E; Thompson, Michael O
2016-09-12
A high-throughput method for characterizing the temperature dependence of material properties following microsecond to millisecond thermal annealing, exploiting the temperature gradients created by a lateral gradient laser spike anneal (lgLSA), is presented. Laser scans generate spatial thermal gradients of up to 5 °C/μm with peak temperatures ranging from ambient to in excess of 1400 °C, limited only by laser power and materials thermal limits. Discrete spatial property measurements across the temperature gradient are then equivalent to independent measurements after varying temperature anneals. Accurate temperature calibrations, essential to quantitative analysis, are critical and methods for both peak temperature and spatial/temporal temperature profile characterization are presented. These include absolute temperature calibrations based on melting and thermal decomposition, and time-resolved profiles measured using platinum thermistors. A variety of spatially resolved measurement probes, ranging from point-like continuous profiling to large area sampling, are discussed. Examples from annealing of III-V semiconductors, CdSe quantum dots, low-κ dielectrics, and block copolymers are included to demonstrate the flexibility, high throughput, and precision of this technique.
International Nuclear Information System (INIS)
Bunting, R.W.; Callahan, R.J.; Finkelstein, S.; Lees, R.S.; Strauss, H.W.
1982-01-01
When labeling platelets with indium-111 oxine, albumin density-gradient separation minimizes the time spent to resuspend those platelets that have been centrifuged against a hard surface. Labeling efficiency or platelet viability, as measured by platelet survival or aggregation with adenosine diphosphate, are not adversely affected
Tumpa, Anja; Stajić, Ana; Jančić-Stojanović, Biljana; Medenica, Mirjana
2017-02-05
This paper deals with the development of hydrophilic interaction liquid chromatography (HILIC) method with gradient elution, in accordance with Analytical Quality by Design (AQbD) methodology, for the first time. The method is developed for olanzapine and its seven related substances. Following step by step AQbD methodology, firstly as critical process parameters (CPPs) temperature, starting content of aqueous phase and duration of linear gradient are recognized, and as critical quality attributes (CQAs) separation criterion S of critical pairs of substances are investigated. Rechtschaffen design is used for the creation of models that describe the dependence between CPPs and CQAs. The design space that is obtained at the end is used for choosing the optimal conditions (set point). The method is fully validated at the end to verify the adequacy of the chosen optimal conditions and applied to real samples. Copyright © 2016 Elsevier B.V. All rights reserved.
Entry, Descent, and Landing With Propulsive Deceleration
Palaszewski, Bryan
2012-01-01
The future exploration of the Solar System will require innovations in transportation and the use of entry, descent, and landing (EDL) systems at many planetary landing sites. The cost of space missions has always been prohibitive, and using the natural planetary and planet s moons atmospheres for entry, descent, and landing can reduce the cost, mass, and complexity of these missions. This paper will describe some of the EDL ideas for planetary entry and survey the overall technologies for EDL that may be attractive for future Solar System missions.
Mazor, Raphael D; Schiff, Kenneth; Ritter, Kerry; Rehn, Andy; Ode, Peter
2010-08-01
Biomonitoring programs are often required to assess streams for which assessment tools have not been developed. For example, low-gradient streams (slopeindices in the state were developed in high-gradient systems. This study evaluated the performance of three sampling methods [targeted riffle composite (TRC), reach-wide benthos (RWB), and the margin-center-margin modification of RWB (MCM)] and two indices [the Southern California Index of Biotic Integrity (SCIBI) and the ratio of observed to expected taxa (O/E)] in low-gradient streams in California for application in this habitat type. Performance was evaluated in terms of efficacy (i.e., ability to collect enough individuals for index calculation), comparability (i.e., similarity of assemblages and index scores), sensitivity (i.e., responsiveness to disturbance), and precision (i.e., ability to detect small differences in index scores). The sampling methods varied in the degree to which they targeted macroinvertebrate-rich microhabitats, such as riffles and vegetated margins, which may be naturally scarce in low-gradient streams. The RWB method failed to collect sufficient numbers of individuals (i.e., >or=450) to calculate the SCIBI in 28 of 45 samples and often collected fewer than 100 individuals, suggesting it is inappropriate for low-gradient streams in California; failures for the other methods were less common (TRC, 16 samples; MCM, 11 samples). Within-site precision, measured as the minimum detectable difference (MDD) was poor but similar across methods for the SCIBI (ranging from 19 to 22). However, RWB had the lowest MDD for O/E scores (0.20 versus 0.24 and 0.28 for MCM and TRC, respectively). Mantel correlations showed that assemblages were more similar within sites among methods than within methods among sites, suggesting that the sampling methods were collecting similar assemblages of organisms. Statistically significant disagreements among methods were not detected, although O/E scores were higher
International Nuclear Information System (INIS)
1983-01-01
Under the direction of the Cinematography and Photography Standards Committee, a British Standard method has been prepared for determining ISO speed and average gradient of direct-exposure medical and dental radiographic film/film-process combinations. The method determines the speed and gradient, i.e. contrast, of the X-ray films processed according to their manufacturer's recommendations. (U.K.)
Freund, Roland
1988-01-01
Conjugate gradient type methods are considered for the solution of large linear systems Ax = b with complex coefficient matrices of the type A = T + i(sigma)I where T is Hermitian and sigma, a real scalar. Three different conjugate gradient type approaches with iterates defined by a minimal residual property, a Galerkin type condition, and an Euclidian error minimization, respectively, are investigated. In particular, numerically stable implementations based on the ideas behind Paige and Saunder's SYMMLQ and MINRES for real symmetric matrices are proposed. Error bounds for all three methods are derived. It is shown how the special shift structure of A can be preserved by using polynomial preconditioning. Results on the optimal choice of the polynomial preconditioner are given. Also, some numerical experiments for matrices arising from finite difference approximations to the complex Helmholtz equation are reported.
Mazaheri, Alireza; Ricchiuto, Mario; Nishikawa, Hiroaki
2016-01-01
In this paper, we introduce a new hyperbolic first-order system for general dispersive partial differential equations (PDEs). We then extend the proposed system to general advection-diffusion-dispersion PDEs. We apply the fourth-order RD scheme of Ref. 1 to the proposed hyperbolic system, and solve time-dependent dispersive equations, including the classical two-soliton KdV and a dispersive shock case. We demonstrate that the predicted results, including the gradient and Hessian (second derivative), are in a very good agreement with the exact solutions. We then show that the RD scheme applied to the proposed system accurately captures dispersive shocks without numerical oscillations. We also verify that the solution, gradient and Hessian are predicted with equal order of accuracy.
The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes
DEFF Research Database (Denmark)
Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp
2017-01-01
This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow pro......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....
Directory of Open Access Journals (Sweden)
Kolgotin Alexei
2016-01-01
Full Text Available Correlation relationships between aerosol microphysical parameters and optical data are investigated. The results show that surface-area concentrations and extinction coefficients are linearly correlated with a correlation coefficient above 0.99 for arbitrary particle size distribution. The correlation relationships that we obtained can be used as constraints in our inversion of optical lidar data. Simulation studies demonstrate a significant stabilization of aerosol microphysical data products if we apply the gradient correlation method in our traditional regularization technique.
The optimized gradient method for full waveform inversion and its spectral implementation
Wu, Zedong; Alkhalifah, Tariq Ali
2016-01-01
At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.
The optimized gradient method for full waveform inversion and its spectral implementation
Wu, Zedong
2016-03-28
At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.
Adaptive Regularization of Neural Networks Using Conjugate Gradient
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
Andersen et al. (1997) and Larsen et al. (1996, 1997) suggested a regularization scheme which iteratively adapts regularization parameters by minimizing validation error using simple gradient descent. In this contribution we present an improved algorithm based on the conjugate gradient technique........ Numerical experiments with feedforward neural networks successfully demonstrate improved generalization ability and lower computational cost...
Shape tracking with occlusions via coarse-to-fine region-based sobolev descent
Yang, Yanchao
2015-05-01
We present a method to track the shape of an object from video. The method uses a joint shape and appearance model of the object, which is propagated to match shape and radiance in subsequent frames, determining object shape. Self-occlusions and dis-occlusions of the object from camera and object motion pose difficulties to joint shape and appearance models in tracking. They are unable to adapt to new shape and appearance information, leading to inaccurate shape detection. In this work, we model self-occlusions and dis-occlusions in a joint shape and appearance tracking framework. Self-occlusions and the warp to propagate the model are coupled, thus we formulate a joint optimization problem. We derive a coarse-to-fine optimization method, advantageous in tracking, that initially perturbs the model by coarse perturbations before transitioning to finer-scale perturbations seamlessly. This coarse-to-fine behavior is automatically induced by gradient descent on a novel infinite-dimensional Riemannian manifold that we introduce. The manifold consists of planar parameterized regions, and the metric that we introduce is a novel Sobolev metric. Experiments on video exhibiting occlusions/dis-occlusions, complex radiance and background show that occlusion/dis-occlusion modeling leads to superior shape accuracy. © 2014 IEEE.
Burt, Adam O.; Tinker, Michael L.
2014-01-01
In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.
Dimova, E.; Steflekova, V.; Karatodorov, S.; Kyoseva, E.
2018-03-01
We propose a way of achieving efficient and robust second-harmonic generation. The technique proposed is similar to the adiabatic population transfer in a two-state quantum system with crossing energies. If the phase mismatching changes slowly, e.g., due to a temperature gradient along the crystal, and makes the phase match for second-harmonic generation to occur, then the energy would be converted adiabatically to the second harmonic. As an adiabatic technique, the second-harmonic generation scheme presented is stable to variations in the crystal parameters, as well as in the input light, crystal length, input intensity, wavelength and angle of incidence.
Kim, Hwi; Min, Sung-Wook; Lee, Byoungho
2008-12-01
Geometrical optics analysis of the structural imperfection of retroreflection corner cubes is described. In the analysis, a geometrical optics model of six-beam reflection patterns generated by an imperfect retroreflection corner cube is developed, and its structural error extraction is formulated as a nonlinear optimization problem. The nonlinear conjugate gradient method is employed for solving the nonlinear optimization problem, and its detailed implementation is described. The proposed method of analysis is a mathematical basis for the nondestructive optical inspection of imperfectly fabricated retroreflection corner cubes.
International Nuclear Information System (INIS)
Wang, J.J.H.; Dubberley, J.R.
1989-01-01
Electromagnetic (EM) fields in a three-dimensional, arbitrarily shaped heterogeneous dielectric or biological body illuminated by a plane wave are computed by an iterative conjugate gradient method. The method is a generalized method of moments applied to the volume integral equation. Because no matrix is explicitly involved or stored, the present iterative method is capable of computing EM fields in objects an order of magnitude larger than those that can be handled by the conventional method of moments. Excellent numerical convergence is achieved. Perfect convergence to the result of the conventional moment method using the same basis and weighted with delta functions is consistently achieved in all the cases computed, indicating that these two algorithms (direct and interactive) are equivalent
Zhang, Dong; Zhang, Ting-Ting; Zhang, Xiao-Lei; Yang, Yan; Hu, Ying; Qin, Qian-Qing
2013-05-01
We present a new method of three-dimensional (3-D) seismic ray tracing, based on an improvement to the linear traveltime interpolation (LTI) ray tracing algorithm. This new technique involves two separate steps. The first involves a forward calculation based on the LTI method and the dynamic successive partitioning scheme, which is applied to calculate traveltimes on cell boundaries and assumes a wavefront that expands from the source to all grid nodes in the computational domain. We locate several dynamic successive partition points on a cell's surface, the traveltimes of which can be calculated by linear interpolation between the vertices of the cell's boundary. The second is a backward step that uses Fermat's principle and the fact that the ray path is always perpendicular to the wavefront and follows the negative traveltime gradient. In this process, the first-arriving ray path can be traced from the receiver to the source along the negative traveltime gradient, which can be calculated by reconstructing the continuous traveltime field with cubic B-spline interpolation. This new 3-D ray tracing method is compared with the LTI method and the shortest path method (SPM) through a number of numerical experiments. These comparisons show obvious improvements to computed traveltimes and ray paths, both in precision and computational efficiency.
Non-homogeneous updates for the iterative coordinate descent algorithm
Yu, Zhou; Thibault, Jean-Baptiste; Bouman, Charles A.; Sauer, Ken D.; Hsieh, Jiang
2007-02-01
Statistical reconstruction methods show great promise for improving resolution, and reducing noise and artifacts in helical X-ray CT. In fact, statistical reconstruction seems to be particularly valuable in maintaining reconstructed image quality when the dosage is low and the noise is therefore high. However, high computational cost and long reconstruction times remain as a barrier to the use of statistical reconstruction in practical applications. Among the various iterative methods that have been studied for statistical reconstruction, iterative coordinate descent (ICD) has been found to have relatively low overall computational requirements due to its fast convergence. This paper presents a novel method for further speeding the convergence of the ICD algorithm, and therefore reducing the overall reconstruction time for statistical reconstruction. The method, which we call nonhomogeneous iterative coordinate descent (NH-ICD) uses spatially non-homogeneous updates to speed convergence by focusing computation where it is most needed. Experimental results with real data indicate that the method speeds reconstruction by roughly a factor of two for typical 3D multi-slice geometries.
Entry, Descent, and Landing for Human Mars Missions
Munk, Michelle M.; DwyerCianciolo, Alicia M.
2012-01-01
One of the most challenging aspects of a human mission to Mars is landing safely on the Martian surface. Mars has such low atmospheric density that decelerating large masses (tens of metric tons) requires methods that have not yet been demonstrated, and are not yet planned in future Mars missions. To identify the most promising options for Mars entry, descent, and landing, and to plan development of the needed technologies, NASA's Human Architecture Team (HAT) has refined candidate methods for emplacing needed elements of the human Mars exploration architecture (such as ascent vehicles and habitats) on the Mars surface. This paper explains the detailed, optimized simulations that have been developed to define the mass needed at Mars arrival to accomplish the entry, descent, and landing functions. Based on previous work, technology options for hypersonic deceleration include rigid, mid-L/D (lift-to-drag ratio) aeroshells, and inflatable aerodynamic decelerators (IADs). The hypersonic IADs, or HIADs, are about 20% less massive than the rigid vehicles, but both have their technology development challenges. For the supersonic regime, supersonic retropropulsion (SRP) is an attractive option, since a propulsive stage must be carried for terminal descent and can be ignited at higher speeds. The use of SRP eliminates the need for an additional deceleration system, but SRP is at a low Technology Readiness Level (TRL) in that the interacting plumes are not well-characterized, and their effect on vehicle stability has not been studied, to date. These architecture-level assessments have been used to define the key performance parameters and a technology development strategy for achieving the challenging mission of landing large payloads on Mars.
Evaluation of vertical profiles to design continuous descent approach procedure
Pradeep, Priyank
The current research focuses on predictability, variability and operational feasibility aspect of Continuous Descent Approach (CDA), which is among the key concepts of the Next Generation Air Transportation System (NextGen). The idle-thrust CDA is a fuel economical, noise and emission abatement procedure, but requires increased separation to accommodate for variability and uncertainties in vertical and speed profiles of arriving aircraft. Although a considerable amount of researches have been devoted to the estimation of potential benefits of the CDA, only few have attempted to explain the predictability, variability and operational feasibility aspect of CDA. The analytical equations derived using flight dynamics and Base of Aircraft and Data (BADA) Total Energy Model (TEM) in this research gives insight into dependency of vertical profile of CDA on various factors like wind speed and gradient, weight, aircraft type and configuration, thrust settings, atmospheric factors (deviation from ISA (DISA), pressure and density of the air) and descent speed profile. Application of the derived equations to idle-thrust CDA gives an insight into sensitivity of its vertical profile to multiple factors. This suggests fixed geometric flight path angle (FPA) CDA has higher degree of predictability and lesser variability at the cost of non-idle and low thrust engine settings. However, with optimized design this impact can be overall minimized. The CDA simulations were performed using Future ATM Concept Evaluation Tool (FACET) based on radar-track and aircraft type data (BADA) of the real air-traffic to some of the busiest airports in the USA (ATL, SFO and New York Metroplex (JFK, EWR and LGA)). The statistical analysis of the vertical profiles of CDA shows 1) mean geometric FPAs derived from various simulated vertical profiles are consistently shallower than 3° glideslope angle and 2) high level of variability in vertical profiles of idle-thrust CDA even in absence of
Dondurur, Derman
2005-11-01
The Normalized Full Gradient (NFG) method was proposed in the mid 1960s and was generally used for the downward continuation of the potential field data. The method eliminates the side oscillations which appeared on the continuation curves when passing through anomalous body depth. In this study, the NFG method was applied to Slingram electromagnetic anomalies to obtain the depth of the anomalous body. Some experiments were performed on the theoretical Slingram model anomalies in a free space environment using a perfectly conductive thin tabular conductor with an infinite depth extent. The theoretical Slingram responses were obtained for different depths, dip angles and coil separations, and it was observed from NFG fields of the theoretical anomalies that the NFG sections yield the depth information of top of the conductor at low harmonic numbers. The NFG sections consisted of two main local maxima located at both sides of the central negative Slingram anomalies. It is concluded that these two maxima also locate the maximum anomaly gradient points, which indicates the depth of the anomaly target directly. For both theoretical and field data, the depth of the maximum value on the NFG sections corresponds to the depth of the upper edge of the anomalous conductor. The NFG method was applied to the in-phase component and correct depth estimates were obtained even for the horizontal tabular conductor. Depth values could be estimated with a relatively small error percentage when the conductive model was near-vertical and/or the conductor depth was larger.
International Nuclear Information System (INIS)
Ward, G.J.; Heckbert, P.S.; Technische Hogeschool Delft
1992-04-01
A new method for improving the accuracy of a diffuse interreflection calculation is introduced in a ray tracing context. The information from a hemispherical sampling of the luminous environment is interpreted in a new way to predict the change in irradiance as a function of position and surface orientation. The additional computation involved is modest and the benefit is substantial. An improved interpolation of irradiance resulting from the gradient calculation produces smoother, more accurate renderings. This result is achieved through better utilization of ray samples rather than additional samples or alternate sampling strategies. Thus, the technique is applicable to a variety of global illumination algorithms that use hemicubes or Monte Carlo sampling techniques
Videodefaecography combined with measurement of the anorectal angle and of perineal descent
International Nuclear Information System (INIS)
Skomorowska, E.; Henrichsen, S.; Christiansen, J.; Hegedues, V.; Glostrup Sygehus, Copenhagen
1987-01-01
Cineradiographic defaecography combined with measurement of the anorectal angle and descent of the pelvic floor is proposed. The method used in 73 women gave valuable information in 48 patients who complained of anal incompetence, rectal tenesmus, and chronic constipation. In these patients, high and low rectal intussusception, rectocele, and pathologic movement of the pelvic floor were detected. Some of these phenomena could only be diagnosed by the radiologic method here described. Quantitations of the anorectal angle and descent of the pelvic floor placed the group with constipation halfway between normal individuals and those with anal incompetence. The value of this finding is discussed. Recent improvements in anorectal surgery often make videodefaecography decisive for the choice of the optimal operative method. Therefore, videodefaecography together with measurement of the anorectal angle and pelvic floor descent is recommended whenever anorectal surgery for correction of functional disturbances is contemplated. (orig.)
DEFF Research Database (Denmark)
Tatu, Aditya Jayant
This thesis deals with two unrelated issues, restricting curve evolution to subspaces and computing image patches in the equivalence class of Histogram of Gradient orientation based features using nonlinear projection methods. Curve evolution is a well known method used in various applications like...... tracking interfaces, active contour based segmentation methods and others. It can also be used to study shape spaces, as deforming a shape can be thought of as evolving its boundary curve. During curve evolution a curve traces out a path in the infinite dimensional space of curves. Due to application...... specific requirements like shape priors or a given data model, and due to limitations of the computer, the computed curve evolution forms a path in some finite dimensional subspace of the space of curves. We give methods to restrict the curve evolution to a finite dimensional linear or implicitly defined...
Faster PET reconstruction with a stochastic primal-dual hybrid gradient method
Ehrhardt, Matthias J.
2017-08-24
Image reconstruction in positron emission tomography (PET) is computationally challenging due to Poisson noise, constraints and potentially non-smooth priors-let alone the sheer size of the problem. An algorithm that can cope well with the first three of the aforementioned challenges is the primal-dual hybrid gradient algorithm (PDHG) studied by Chambolle and Pock in 2011. However, PDHG updates all variables in parallel and is therefore computationally demanding on the large problem sizes encountered with modern PET scanners where the number of dual variables easily exceeds 100 million. In this work, we numerically study the usage of SPDHG-a stochastic extension of PDHG-but is still guaranteed to converge to a solution of the deterministic optimization problem with similar rates as PDHG. Numerical results on a clinical data set show that by introducing randomization into PDHG, similar results as the deterministic algorithm can be achieved using only around 10 % of operator evaluations. Thus, making significant progress towards the feasibility of sophisticated mathematical models in a clinical setting.
Faster PET reconstruction with a stochastic primal-dual hybrid gradient method
Ehrhardt, Matthias J.; Markiewicz, Pawel; Chambolle, Antonin; Richtárik, Peter; Schott, Jonathan; Schönlieb, Carola-Bibiane
2017-08-01
Image reconstruction in positron emission tomography (PET) is computationally challenging due to Poisson noise, constraints and potentially non-smooth priors-let alone the sheer size of the problem. An algorithm that can cope well with the first three of the aforementioned challenges is the primal-dual hybrid gradient algorithm (PDHG) studied by Chambolle and Pock in 2011. However, PDHG updates all variables in parallel and is therefore computationally demanding on the large problem sizes encountered with modern PET scanners where the number of dual variables easily exceeds 100 million. In this work, we numerically study the usage of SPDHG-a stochastic extension of PDHG-but is still guaranteed to converge to a solution of the deterministic optimization problem with similar rates as PDHG. Numerical results on a clinical data set show that by introducing randomization into PDHG, similar results as the deterministic algorithm can be achieved using only around 10 % of operator evaluations. Thus, making significant progress towards the feasibility of sophisticated mathematical models in a clinical setting.
International Nuclear Information System (INIS)
Werner-Wasik, Maria; Nelson, Arden D.; Choi, Walter; Arai, Yoshio; Faulhaber, Peter F.; Kang, Patrick; Almeida, Fabio D.; Xiao, Ying; Ohri, Nitin; Brockway, Kristin D.; Piper, Jonathan W.; Nelson, Aaron S.
2012-01-01
Purpose: To evaluate the accuracy and consistency of a gradient-based positron emission tomography (PET) segmentation method, GRADIENT, compared with manual (MANUAL) and constant threshold (THRESHOLD) methods. Methods and Materials: Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10–37 mm in diameter and were acquired at five institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25% to 50% at 5% increments. Subsequently, seven physicians segmented 31 lesions (7–264 mL) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL. Results: For spheres 20 mm (p < 0.065) and <20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate (p < 0.01), with a mean absolute % error in volume of 10.99% (11.9% SD), followed by 25% THRESHOLD at 17.5% (29.4% SD), and MANUAL at 19.5% (17.2% SD). GRADIENT had the least systematic bias, with a mean % error in volume of –0.05% (16.2% SD) compared with 25% THRESHOLD at –2.1% (34.2% SD) and MANUAL at –16.3% (20.2% SD; p value <0.01). Interobserver variability was reduced using GRADIENT compared with both 25% THRESHOLD and MANUAL (p value <0.01, Levene’s test). Conclusion: GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in radiation therapy planning and response assessment.
International Nuclear Information System (INIS)
Wang Hua; Liu Feng; Crozier, Stuart; Xia Ling
2008-01-01
This paper presents a stabilized Bi-conjugate gradient algorithm (BiCGstab) that can significantly improve the performance of the impedance method, which has been widely applied to model low-frequency field induction phenomena in voxel phantoms. The improved impedance method offers remarkable computational advantages in terms of convergence performance and memory consumption over the conventional, successive over-relaxation (SOR)-based algorithm. The scheme has been validated against other numerical/analytical solutions on a lossy, multilayered sphere phantom excited by an ideal coil loop. To demonstrate the computational performance and application capability of the developed algorithm, the induced fields inside a human phantom due to a low-frequency hyperthermia device is evaluated. The simulation results show the numerical accuracy and superior performance of the method.
Wang, Hua; Liu, Feng; Xia, Ling; Crozier, Stuart
2008-11-21
This paper presents a stabilized Bi-conjugate gradient algorithm (BiCGstab) that can significantly improve the performance of the impedance method, which has been widely applied to model low-frequency field induction phenomena in voxel phantoms. The improved impedance method offers remarkable computational advantages in terms of convergence performance and memory consumption over the conventional, successive over-relaxation (SOR)-based algorithm. The scheme has been validated against other numerical/analytical solutions on a lossy, multilayered sphere phantom excited by an ideal coil loop. To demonstrate the computational performance and application capability of the developed algorithm, the induced fields inside a human phantom due to a low-frequency hyperthermia device is evaluated. The simulation results show the numerical accuracy and superior performance of the method.
International Nuclear Information System (INIS)
Fouillet, C.
2003-01-01
In this work, we simulate a nucleate boiling problem using direct numerical simulation. The numerical method used is the second gradient method based on a diffuse interface model which represents interfaces as volumetric regions of finite thickness across which the physical properties of the fluid vary continuously. First, this method is successfully applied to nucleate boiling of a pure fluid. Then, the model is extended to dilute binary mixtures. After studying its validity and its limits in simple configurations, it is then applied to nucleate boiling of a dilute mixture. These simulations show a strong decrease of the heat transfer coefficient as the concentration increases, in agreement with the numerous experimental studies published in this domain. (author) [fr
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.
Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L
2017-10-01
The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.
Cimpoiu, Claudia; Hosu, Anamaria; Puscas, Anitta
2012-02-03
The group of hydrophilic vitamins play an important role in human health, and their lack or excess produces specific diseases. Therefore, the analysis of these compounds is indispensable for monitoring their content in pharmaceuticals and food in order to prevent some human diseases. TLC was successfully applied in the analysis of hydrophilic vitamins, but the most difficult problem in the simultaneous analysis of all these compounds is to find an optimum stationary phase-mobile phase system due to different chemical characteristics of analytes. Unfortunately structural analogues are difficult to separate in one chromatographic run, and this is the case in hydrophilic vitamins investigations. TLC gives the possibility to perform two-dimensional separations by using stationary phase gradient achieving the highest resolution by combining two systems with different selectivity. The goal of this work was to develop a method of analysis enabling separation of hydrophilic vitamins using TLC with adsorbent gradient. The developed method was used for identifying the water-soluble vitamins in alcoholic extracts of Hippophae rhamnoides and of Ribes nigrum. Copyright © 2011 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Benn eMacdonald
2015-11-01
Full Text Available Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs, is a challenging problem in contemporary systems biology. Conventional methods involve repeatedly solving the ODEs by numerical integration, which is computationally onerous and does not scale up to complex systems. Aimed at reducing the computational costs, new concepts based on gradient matching have recently been proposed in the computational statistics and machine learning literature. In a preliminary smoothing step, the time series data are interpolated; then, in a second step, the parameters of the ODEs are optimised so as to minimise some metric measuring the difference between the slopes of the tangents to the interpolants, and the time derivatives from the ODEs. In this way, the ODEs never have to be solved explicitly. This review provides a concise methodological overview of the current state-of-the-art methods for gradient matching in ODEs, followed by an empirical comparative evaluation based on a set of widely used and representative benchmark data.
International Nuclear Information System (INIS)
Takahashi, Norio; Hiyama, Keiko; Kodaira, Mieko; Satoh, Chiyoko.
1990-05-01
We have examined the feasibility of denaturing gradient gel electrophoresis (DGGE) of RNA:DNA duplexes to detect variations in genomic and cloned DNAs. The result has demonstrated that use of RNA:DNA duplexes makes DGGE much more practical for screening a large number of samples than use of DNA:DNA heteroduplexes, because preparation of RNA probes is easier than that of DNA probes. Three different 32 P-labeled RNA probes were produced. Genomic or cloned DNAs were digested with restriction enzymes and hybridized to labeled RNA probes, and resulting RNA:DNA duplexes were examined by DGGE. The presence of a mismatch(es) was detected as a difference in the mobility of bands on the gel. The experimental conditions were determined using DNA segments from cloned normal and three thalassemic human β-globin genes. The results from experiments on the cloned DNAs suggest that DGGE of RNA:DNA duplexes will detect nucleotide substitutions and deletions in DNA. In the course of these studies, a polymorphism due to a single-base substitution at position 666 of IVS2 (IVS2-666) of the human β-globin gene was directly identified using genomic DNA samples. A study of 59 unrelated Japanese from Hiroshima was undertaken in which the frequency of the allele with C at IVS2-666 was 0.48 and that of the allele with T was 0.52. This approach was found to be very effective for detecting heritable variation and should be a powerful tool for detecting fresh mutations in DNA, which occur outside the known restriction sites. (author)
Long-Time Asymptotics for the Korteweg-de Vries Equation via Nonlinear Steepest Descent
International Nuclear Information System (INIS)
Grunert, Katrin; Teschl, Gerald
2009-01-01
We apply the method of nonlinear steepest descent to compute the long-time asymptotics of the Korteweg-de Vries equation for decaying initial data in the soliton and similarity region. This paper can be viewed as an expository introduction to this method
Ono, Shunsuke
2017-04-01
Minimizing L 0 gradient, the number of the non-zero gradients of an image, together with a quadratic data-fidelity to an input image has been recognized as a powerful edge-preserving filtering method. However, the L 0 gradient minimization has an inherent difficulty: a user-given parameter controlling the degree of flatness does not have a physical meaning since the parameter just balances the relative importance of the L 0 gradient term to the quadratic data-fidelity term. As a result, the setting of the parameter is a troublesome work in the L 0 gradient minimization. To circumvent the difficulty, we propose a new edge-preserving filtering method with a novel use of the L 0 gradient. Our method is formulated as the minimization of the quadratic data-fidelity subject to the hard constraint that the L 0 gradient is less than a user-given parameter α . This strategy is much more intuitive than the L 0 gradient minimization because the parameter α has a clear meaning: the L 0 gradient value of the output image itself, so that one can directly impose a desired degree of flatness by α . We also provide an efficient algorithm based on the so-called alternating direction method of multipliers for computing an approximate solution of the nonconvex problem, where we decompose it into two subproblems and derive closed-form solutions to them. The advantages of our method are demonstrated through extensive experiments.
A project to study SOC evolution after land use change combining chronosequence and gradient methods
Gabarron-Galeote, Miguel A.; van Wesemael, Bas
2013-04-01
In the last decades the interest in the global C budget has increased enormously and soils have a great importance in this issue since they contain about twice as much carbon as the atmosphere. Land use change (LUC) can cause a change in land cover and an associated change in carbon stocks in soils, so it has a major impact in the balance between inputs and outputs of soil organic carbon (SOC). Improved understanding of land-use impacts on the world's terrestrial carbon balance is thus a necessary part of the global effort to mitigate climate change. The aim of this project is to predict the effects of land use and land management change on (SOC) stocks, characterizing the soil organic carbon cycle and its relationship to the vegetal cover in croplands abandoned different years ago and under different Mediterranean climatic conditions in South of Spain. The study area is located in the Cordillera Bética Litoral, in South of Spain. In this area, a climatic gradient can be observed from West to East: from >1,500 mm year-1 in the Strait of Gibraltar to <250 mm year-1 in the Cabo de Gata. More specifically, the study is focussed on three different areas from the climatic conditions point of view: Gaucín (1010 mm year-1), Almogía, (576 mm year-1) and Gérgal (240 mm year-1). By means of the analyses of aerial photographs (1956, 1977, 1984, 1998 and 2009) all the experimental plots will be selected. After this procedure, the three study areas will be composed by experimental plots of these classes: a) Lands with natural vegetation since 1956. b) Abandoned lands between 1956 and 1977. c) Abandoned lands between 1977 and 1984. d) Abandoned lands between 1984 and 1998. e) Abandoned lands between 1998 and 2005. f) Cultivated lands since 1956. The main expected outcomes of the research project are the characterization of the temporal evolution of SOC in soils, the compilation of experimental areas under different Mediterranean climatic conditions, and the characterization
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bernstein, Andrey [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [IBM Research Center Ireland
2017-11-27
This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claims are established in terms of tracking of the solution of a well-posed time-varying optimization problem.
International Nuclear Information System (INIS)
Krishnamoorthy, Gautham
2017-01-01
Highlights: • The P_1 radiation model was interfaced with high performance linear solvers. • Pre-conditioned conjugate gradient (PC CG) method improved convergence by 50% • PC CG was more than 30 times faster than classical iterative methods. • The time to solution scaled linearly with increase in problem size employing PC CG. • Employing WSGGM with P_1 model compared reasonably well against benchmark data. - Abstract: The iterative convergence of the P_1 radiation model can be slow in optically thin scenarios when employing classical iterative methods. In order to remedy this shortcoming, an in-house P_1 radiation model was interfaced with high performance, scalable, linear solver libraries. Next, the accuracies of P_1 radiation model calculations was assessed by comparing its predictions against discrete ordinates (DO) model calculations for prototypical problems representative of modern combustion systems. Corresponding benchmark results were also included for comparison. Utilizing Pre-Conditioners (PC) to the Conjugate Gradients (CG) method, the convergence time of the P_1 radiation model reduced by a factor of 30 for modest problem sizes and a factor of 70 for larger sized problems when compared against classical Gauss Seidel sweeps. Further, PC provided 50% computational savings compared to employing CG in a standalone mode. The P_1 model calculation times were about 25–30% of the DO model calculation time. The time to solution also scaled linearly with an increase in problem size. The weighted sum of gray gases model employed in this study in conjunction with the P_1 model provided good agreement against benchmark data with L_2 error norms (defined relative to corresponding DO calculations) improving when isotropic intensities were prevalent.
Dobramysl, U; Holcman, D
2018-02-15
Is it possible to recover the position of a source from the steady-state fluxes of Brownian particles to small absorbing windows located on the boundary of a domain? To address this question, we develop a numerical procedure to avoid tracking Brownian trajectories in the entire infinite space. Instead, we generate particles near the absorbing windows, computed from the analytical expression of the exit probability. When the Brownian particles are generated by a steady-state gradient at a single point, we compute asymptotically the fluxes to small absorbing holes distributed on the boundary of half-space and on a disk in two dimensions, which agree with stochastic simulations. We also derive an expression for the splitting probability between small windows using the matched asymptotic method. Finally, when there are more than two small absorbing windows, we show how to reconstruct the position of the source from the diffusion fluxes. The present approach provides a computational first principle for the mechanism of sensing a gradient of diffusing particles, a ubiquitous problem in cell biology.
Stereotypes of women of Asian descent in midwifery: some evidence.
Bowler, I M
1993-03-01
The subject of this paper is part of a larger study which investigated the delivery of maternity care to women of South Asian descent in Britain (Bowler, 1990). An ethnographic approach was used and the main method of data collection was non-participant observation in antenatal clinics, labour and postnatal wards in a teaching hospital maternity unit. These observations were supported by data from interviews with midwives. It was found that the midwives commonly use stereotypes of women in order to help them to provide care. These stereotypes are particularly likely to be used in situations where the midwife has difficulty (through pressure of time or other circumstances) in getting to know an individual woman. The stereotype of women of Asian descent contained four main themes: communication problems; failure to comply with care and service abuse; making a fuss about nothing; a lack of normal maternal instinct. Reasons for stereotyping are explored. Effects on service provision in the areas of family planning and breast feeding are highlighted.
Mars Exploration Rover Terminal Descent Mission Modeling and Simulation
Raiszadeh, Behzad; Queen, Eric M.
2004-01-01
Because of NASA's added reliance on simulation for successful interplanetary missions, the MER mission has developed a detailed EDL trajectory modeling and simulation. This paper summarizes how the MER EDL sequence of events are modeled, verification of the methods used, and the inputs. This simulation is built upon a multibody parachute trajectory simulation tool that has been developed in POST I1 that accurately simulates the trajectory of multiple vehicles in flight with interacting forces. In this model the parachute and the suspended bodies are treated as 6 Degree-of-Freedom (6 DOF) bodies. The terminal descent phase of the mission consists of several Entry, Descent, Landing (EDL) events, such as parachute deployment, heatshield separation, deployment of the lander from the backshell, deployment of the airbags, RAD firings, TIRS firings, etc. For an accurate, reliable simulation these events need to be modeled seamlessly and robustly so that the simulations will remain numerically stable during Monte-Carlo simulations. This paper also summarizes how the events have been modeled, the numerical issues, and modeling challenges.
Nurses of African descent and career advancement.
Wesley, Yvonne; Dobal, May T
2009-01-01
The purpose of this article is to evaluate a leadership institute designed to promote career advancement and leadership in administration, education, and research among nurses of African descent. Government reports indicate that Black Americans receive lower quality health care than other racial groups even when insurance and income are equal. Moreover, the literature suggests that less than 10% of practicing professional nurses in America are Black-and of these, less than 1% are in senior executive leadership positions. However, the literature lacks detailed discussion of the effectiveness of leadership programs. This article provides an in-depth look at a leadership institute for Black nurses and outlines the impact of the program.
Gradient method for blind chaotic signal separation based on proliferation exponent
International Nuclear Information System (INIS)
Lü Shan-Xiang; Wang Zhao-Shan; Hu Zhi-Hui; Feng Jiu-Chao
2014-01-01
A new method to perform blind separation of chaotic signals is articulated in this paper, which takes advantage of the underlying features in the phase space for identifying various chaotic sources. Without incorporating any prior information about the source equations, the proposed algorithm can not only separate the mixed signals in just a few iterations, but also outperforms the fast independent component analysis (FastICA) method when noise contamination is considerable. (general)
Energy Technology Data Exchange (ETDEWEB)
Werner-Wasik, Maria, E-mail: Maria.Werner-wasik@jeffersonhospital.org [Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA (United States); Nelson, Arden D. [MIM Software Inc., Cleveland, OH (United States); Choi, Walter [Department of Radiation Oncology, UPMC Health Systems, Pittsburgh, PA (United States); Arai, Yoshio [Department of Radiation Oncology, Beth Israel Medical Center, New York, NY (Israel); Faulhaber, Peter F. [University Hospitals Case Medical Center, Cleveland, OH (United States); Kang, Patrick [Department of Radiology, Beth Israel Medical Center, New York, NY (Israel); Almeida, Fabio D. [Division of Nuclear Medicine, University of Arizona Health Sciences Center, Tucson, AZ (United States); Xiao, Ying; Ohri, Nitin [Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA (United States); Brockway, Kristin D.; Piper, Jonathan W.; Nelson, Aaron S. [MIM Software Inc., Cleveland, OH (United States)
2012-03-01
Purpose: To evaluate the accuracy and consistency of a gradient-based positron emission tomography (PET) segmentation method, GRADIENT, compared with manual (MANUAL) and constant threshold (THRESHOLD) methods. Methods and Materials: Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10-37 mm in diameter and were acquired at five institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25% to 50% at 5% increments. Subsequently, seven physicians segmented 31 lesions (7-264 mL) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL. Results: For spheres <20 mm in diameter, GRADIENT was the most accurate with a mean absolute % error in diameter of 8.15% (10.2% SD) compared with 49.2% (51.1% SD) for 45% THRESHOLD (p < 0.005). For larger spheres, the methods were statistically equivalent. For varying source-to-background ratios, GRADIENT was the most accurate for spheres >20 mm (p < 0.065) and <20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate (p < 0.01), with a mean absolute % error in volume of 10.99% (11.9% SD), followed by 25% THRESHOLD at 17.5% (29.4% SD), and MANUAL at 19.5% (17.2% SD). GRADIENT had the least systematic bias, with a mean % error in volume of -0.05% (16.2% SD) compared with 25% THRESHOLD at -2.1% (34.2% SD) and MANUAL at -16.3% (20.2% SD; p value <0.01). Interobserver variability was reduced using GRADIENT compared with both 25% THRESHOLD and MANUAL (p value <0.01, Levene's test). Conclusion: GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in
Comparison of methods for measuring flux gradients in type II superconductors
International Nuclear Information System (INIS)
Kroeger, D.M.; Koch, C.C.; Charlesworth, J.P.
1975-01-01
A comparison has been made of four methods of measuring the critical current density J/sub c/ in hysteretic type II superconductors, having a wide range of K and J/sub c/ values, in magnetic fields up to 70 kOe. Two of the methods, (a) resistive measurements and (b) magnetization measurements, were carried out in static magnetic fields. The other two methods involved analysis of the response of the sample to a small alternating field superimposed on the static field. The response was analyzed either (c) by measuring the third-harmonic content or (d) by integration of the waveform to obtain measure of flux penetration. The results are discussed with reference to the agreement between the different techniques and the consistency of the critical state hypothesis on which all these techniques are based. It is concluded that flux-penetration measurements by method (d) provide the most detailed information about J/sub c/ but that one must be wary of minor failures of the critical state hypothesis. Best results are likely to be obtained by using more than one method. (U.S.)
Steganalysis Method for LSB Replacement Based on Local Gradient of Image Histogram
Directory of Open Access Journals (Sweden)
M. Mahdavi
2008-10-01
Full Text Available In this paper we present a new accurate steganalysis method for the LSBreplacement steganography. The suggested method is based on the changes that occur in thehistogram of an image after the embedding of data. Every pair of neighboring bins of ahistogram are either inter-related or unrelated depending on whether embedding of a bit ofdata in the image could affect both bins or not. We show that the overall behavior of allinter-related bins, when compared with that of the unrelated ones, could give an accuratemeasure for the amount of the embedded data. Both analytical analysis and simulationresults show the accuracy of the proposed method. The suggested method has beenimplemented and tested for over 2000 samples and compared with the RS Steganalysismethod. Mean and variance of error were 0.0025 and 0.0037 for the suggested methodwhere these quantities were 0.0070 and 0.0182 for the RS Steganalysis. Using 4800samples, we showed that the performance of the suggested method is comparable withthose of the RS steganalysis for JPEG filtered images. The new approach is applicable forthe detection of both random and sequential LSB embedding.
Noise annoyance caused by continuous descent approaches compared to regular descent procedures
White, K.; Arntzen, M.; Walker, F.; Waiyaki, F.M.; Meeter, M.; Bronkhorst, A.W.
2017-01-01
During Continuous Descent Approaches (CDAs) aircraft glide towards the runway resulting in reduced noise and fuel usage. Here, we investigated whether such landings cause less noise annoyance than a regular stepwise approach. Both landing types were compared in a controlled laboratory setting with a
Development and descent of the testis in relation to cryptorchidism
DEFF Research Database (Denmark)
Virtanen, Helena E; Cortes, Dina; Rajpert-De Meyts, Ewa
2007-01-01
The testis descends in two phases. Animal studies suggest, that the transabdominal descent of the testis depends on the insulin-like hormone 3 (INSL3). Androgens are important in the inguinoscrotal testicular descent in animals and humans. In general, the cause of cryptorchidism is unknown...... and the aetiology is possibly multifactorial. Histological changes in cryptorchid testes demonstrate disturbed development. Conclusion: Since testicular descent is regulated by testis-derived hormones, cryptorchidism may reflect a functional defect of the testis....
Reyes-Acosta, J Leonardo; Vandegehuchte, Maurits W; Steppe, Kathy; Lubczynski, Maciek W
2012-07-01
Sap flow measurements conducted with thermal dissipation probes (TDPs) are vulnerable to natural temperature gradient (NTG) bias. Few studies, however, attempted to explain the dynamics underlying the NTG formation and its influence on the sensors' signal. This study focused on understanding how the TDP signals are affected by negative and positive temperature influences from NTG and tested the novel cyclic heat dissipation (CHD) method to filter out the NTG bias. A series of three experiments were performed in which gravity-driven water flow was enforced on freshly cut stem segments of Fagus sylvatica L., while an artificial temperature gradient (ATG) was induced. The first experiment sought to confirm the incidence of the ATG on sensors. The second experiment established the mis-estimations caused by the biasing effect of the ATG on standard TDP measurements. The third experiment tested the accuracy of the CHD method to account for the ATG biasing effect, as compared with other cyclic correction methods. During experiments, sap flow measured by TDP was assessed against gravimetric measurements. The results show that negative and positive ATGs were comparable in pattern but substantially larger than field NTGs. Second, the ATG bias caused an overestimation of the standard TDP sap flux density of ∼17 cm(3) cm(-2) h(-1) by 76%, and the sap flux density of ∼2 cm(3) cm(-2) h(-1) by over 800%. Finally, the proposed CHD method successfully reduced the max. ATG bias to 25% at ∼11 cm(3) cm(-2) h(-1) and to 40% at ∼1 cm(3) cm(-2) h(-1). We concluded that: (i) the TDP method is susceptible to NTG especially at low flows; (ii) the CHD method successfully corrected the TDP signal and resulted in generally more accurate sap flux density estimates (mean absolute percentage error ranging between 11 and 21%) than standard constant power TDP method and other cyclic power methods; and (iii) the ATG enforcing system is a suitable way of re-creating NTG for future tests.
Optimization of Candu fuel management with gradient methods using generalized perturbation theory
International Nuclear Information System (INIS)
Chambon, R.; Varin, E.; Rozon, D.
2005-01-01
CANDU fuel management problems are solved using time-average representation of the core. Optimization problems based on this representation have been defined in the early nineties. The mathematical programming using the generalized perturbation theory (GPT) that was developed has been implemented in the reactor code DONJON. The use of the augmented Lagrangian (AL) method is presented and evaluated in this paper. This approach is mandatory for new constraint problems. Combined with the classical Lemke method, it proves to be very efficient to reach optimal solution in a very limited number of iterations. (authors)
GOCE in ocean modelling - Point mass method applied on GOCE gravity gradients
DEFF Research Database (Denmark)
Herceg, Matija; Knudsen, Per
This presentation is an introduction to my Ph.D project. The main objective of the study is to improve the methodology for combining GOCE gravity field models with satellite altimetry to derive optimal dynamic ocean topography models for oceanography. Here a method for geoid determination using...
An Introduction to the Conjugate Gradient Method that Even an Idiot Can Understand
1994-03-07
to Omar Ghattas, who taught me much of what I know about numerical methods, and provided me with extensive comments on the first draft of this article...Dongarra, Victor Eijkhout, Roldan Pozo, Charles Romine, and Henk van der Vorst, Templates for the solution of linear systems: Building blocks for iterative
A primal–dual hybrid gradient method for nonlinear operators with applications to MRI
Valkonen, Tuomo
2014-01-01
generalized variation priors. For such problems, we show that our general local convergence result holds when the noise level of the data f is low, and the regularization parameter α is correspondingly small. We verify the numerical performance of the method
On the use of rigid body modes in the deflated preconditioned conjugate gradient method
Jönsthövel, T.B.; Van Gijzen, M.B.; Vuik, C.; Scarpas, A.
2013-01-01
Large discontinuities in material properties, such as those encountered in composite materials, lead to ill-conditioned systems of linear equations. These discontinuities give rise to small eigenvalues that may negatively affect the convergence of iterative solution methods such as the
On the use of rigid body modes in the deflated preconditioned conjugate gradient method
Jönsthövel, T.B.; Van Gijzen, M.B.; Vuik, C.; Scarpas, A.
2011-01-01
Large discontinuities in material properties, such as encountered in composite materials, lead to ill-conditioned systems of linear equations. These discontinuities give rise to small eigenvalues that may negatively affect the convergence of iterative solution methods such as the Preconditioned
Improvement of the variable storage coefficient method with water surface gradient as a variable
The variable storage coefficient (VSC) method has been used for streamflow routing in continuous hydrological simulation models such as the Agricultural Policy/Environmental eXtender (APEX) and the Soil and Water Assessment Tool (SWAT) for more than 30 years. APEX operates on a daily time step and ...
Jönsthövel, T.B.; Van Gijzen, M.B.; MacLachlan, S.; Vuik, C.; Scarpas, A.
2011-01-01
The demand for large FE meshes increases as parallel computing becomes the standard in FE simulations. Direct and iterative solution methods are used to solve the resulting linear systems. Many applications concern composite materials, which are characterized by large discontinuities in the material
Regression Analysis of Top of Descent Location for Idle-thrust Descents
Stell, Laurel; Bronsvoort, Jesper; McDonald, Greg
2013-01-01
In this paper, multiple regression analysis is used to model the top of descent (TOD) location of user-preferred descent trajectories computed by the flight management system (FMS) on over 1000 commercial flights into Melbourne, Australia. The independent variables cruise altitude, final altitude, cruise Mach, descent speed, wind, and engine type were also recorded or computed post-operations. Both first-order and second-order models are considered, where cross-validation, hypothesis testing, and additional analysis are used to compare models. This identifies the models that should give the smallest errors if used to predict TOD location for new data in the future. A model that is linear in TOD altitude, final altitude, descent speed, and wind gives an estimated standard deviation of 3.9 nmi for TOD location given the trajec- tory parameters, which means about 80% of predictions would have error less than 5 nmi in absolute value. This accuracy is better than demonstrated by other ground automation predictions using kinetic models. Furthermore, this approach would enable online learning of the model. Additional data or further knowl- edge of algorithms is necessary to conclude definitively that no second-order terms are appropriate. Possible applications of the linear model are described, including enabling arriving aircraft to fly optimized descents computed by the FMS even in congested airspace. In particular, a model for TOD location that is linear in the independent variables would enable decision support tool human-machine interfaces for which a kinetic approach would be computationally too slow.
Tavakoli, Behnoosh; Zhu, Quing
2013-01-01
Ultrasound-guided diffuse optical tomography (DOT) is a promising method for characterizing malignant and benign lesions in the female breast. We introduce a new two-step algorithm for DOT inversion in which the optical parameters are estimated with the global optimization method, genetic algorithm. The estimation result is applied as an initial guess to the conjugate gradient (CG) optimization method to obtain the absorption and scattering distributions simultaneously. Simulations and phantom experiments have shown that the maximum absorption and reduced scattering coefficients are reconstructed with less than 10% and 25% errors, respectively. This is in contrast with the CG method alone, which generates about 20% error for the absorption coefficient and does not accurately recover the scattering distribution. A new measure of scattering contrast has been introduced to characterize benign and malignant breast lesions. The results of 16 clinical cases reconstructed with the two-step method demonstrates that, on average, the absorption coefficient and scattering contrast of malignant lesions are about 1.8 and 3.32 times higher than the benign cases, respectively.
The grand descent has begun for CMS
2006-01-01
Until recently, the CMS experimental cavern looked relatively empty; its detector was assembled entirely at ground level, to be lowered underground in 15 sections. On 2 November, the first hadronic forward calorimeter led the way with a grand descent. The first section of the CMS detector (centre of photo) arriving from the vertical shaft, viewed from the cavern floor. There is something unusual about the construction of the CMS detector. Instead of being built in the experimental cavern, like all the other detectors in the LHC experiments, it was constructed at ground level. This was to allow for easy access during the assembly of the detector and to minimise the size of the excavated cavern. The slightly nerve-wracking task of lowering it safely into the cavern in separate sections came after the complete detector was successfully tested with a magnetic field at ground level. In the early morning of 2 November, the first section of the CMS detector began its eagerly awaited descent into the underground ca...
Akai, Takashi; Bijeljic, Branko; Blunt, Martin J.
2018-06-01
In the color gradient lattice Boltzmann model (CG-LBM), a fictitious-density wetting boundary condition has been widely used because of its ease of implementation. However, as we show, this may lead to inaccurate results in some cases. In this paper, a new scheme for the wetting boundary condition is proposed which can handle complicated 3D geometries. The validity of our method for static problems is demonstrated by comparing the simulated results to analytical solutions in 2D and 3D geometries with curved boundaries. Then, capillary rise simulations are performed to study dynamic problems where the three-phase contact line moves. The results are compared to experimental results in the literature (Heshmati and Piri, 2014). If a constant contact angle is assumed, the simulations agree with the analytical solution based on the Lucas-Washburn equation. However, to match the experiments, we need to implement a dynamic contact angle that varies with the flow rate.
Directory of Open Access Journals (Sweden)
Mahesh Jangid
2018-02-01
Full Text Available Handwritten character recognition is currently getting the attention of researchers because of possible applications in assisting technology for blind and visually impaired users, human–robot interaction, automatic data entry for business documents, etc. In this work, we propose a technique to recognize handwritten Devanagari characters using deep convolutional neural networks (DCNN which are one of the recent techniques adopted from the deep learning community. We experimented the ISIDCHAR database provided by (Information Sharing Index ISI, Kolkata and V2DMDCHAR database with six different architectures of DCNN to evaluate the performance and also investigate the use of six recently developed adaptive gradient methods. A layer-wise technique of DCNN has been employed that helped to achieve the highest recognition accuracy and also get a faster convergence rate. The results of layer-wise-trained DCNN are favorable in comparison with those achieved by a shallow technique of handcrafted features and standard DCNN.
CSIR Research Space (South Africa)
Wilke, DN
2012-07-01
Full Text Available problems that utilise remeshing (i.e. the mesh topology is allowed to change) between design updates. Here, changes in mesh topology result in abrupt changes in the discretization error of the computed response. These abrupt changes in turn manifests... in shape optimization but may be present whenever (partial) differential equations are ap- proximated numerically with non-constant discretization methods e.g. remeshing of spatial domains or automatic time stepping in temporal domains. Keywords: Complex...
Directory of Open Access Journals (Sweden)
Shweta Gupta
Full Text Available Efavirenz is an anti-viral agent of non-nucleoside reverse transcriptase inhibitor category used as a part of highly active retroviral therapy for the treatment of infections of human immune deficiency virus type-1. A simple, sensitive and rapid reversed-phase high performance liquid chromatographic gradient method was developed and validated for the determination of efavirenz in plasma. The method was developed with high performance liquid chromatography using Waters X-Terra Shield, RP18 50 x 4.6 mm, 3.5 μm column and a mobile phase consisting of phosphate buffer pH 3.5 and Acetonitrile. The elute was monitored with the UV-Visible detector at 260 nm with a flow rate of 1.5 mL/min. Tenofovir disoproxil fumarate was used as internal standard. The method was validated for linearity, precision, accuracy, specificity, robustness and data obtained were statistically analyzed. Calibration curve was found to be linear over the concentration range of 1-300 μg/mL. The retention times of efavirenz and tenofovir disoproxil fumarate (internal standard were 5.941 min and 4.356 min respectively. The regression coefficient value was found to be 0.999. The limit of detection and the limit of quantification obtained were 0.03 and 0.1 μg/mL respectively. The developed HPLC method can be useful for quantitative pharmacokinetic parameters determination of efavirenz in plasma.
Böhme, M.; Ilg, A.; Ossig, A.; Küchenhoff, H.
2006-06-01
Existing methods for determining paleoprecipitation are subject to large errors (±350 400 mm or more using mammalian proxies), or are restricted to wet climate systems due to their strong facies dependence (paleobotanical proxies). Here we describe a new paleoprecipitation tool based on an indexing of ecophysiological groups within herpetological communities. In recent communities these indices show a highly significant correlation to annual precipitation (r2 = 0.88), and yield paleoprecipitation estimates with average errors of ±250 280 mm. The approach was validated by comparison with published paleoprecipitation estimates from other methods. The method expands the application of paleoprecipitation tools to dry climate systems and in this way contributes to the establishment of a more comprehensive paleoprecipitation database. This method is applied to two high-resolution time intervals from the European Neogene: the early middle Miocene (early Langhian) and the early late Miocene (early Tortonian). The results indicate that both periods show significant meridional precipitation gradients in Europe, these being stronger in the early Langhian (threefold decrease toward the south) than in the early Tortonian (twofold decrease toward the south). This pattern indicates a strengthening of climatic belts during the middle Miocene climatic optimum due to Southern Hemisphere cooling and an increased contribution of Arctic low-pressure cells to the precipitation from the late Miocene onward due to Northern Hemisphere cooling.
Energy Technology Data Exchange (ETDEWEB)
Wei, Jun, E-mail: jvwei@umich.edu; Zhou, Chuan; Chan, Heang-Ping; Chughtai, Aamer; Agarwal, Prachi; Kuriakose, Jean; Hadjiiski, Lubomir; Patel, Smita; Kazerooni, Ella [Department of Radiology, University of Michigan, Ann Arbor, Michigan 48109 (United States)
2014-08-15
Purpose: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. Methods: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. Results: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features
International Nuclear Information System (INIS)
Wei, Jun; Zhou, Chuan; Chan, Heang-Ping; Chughtai, Aamer; Agarwal, Prachi; Kuriakose, Jean; Hadjiiski, Lubomir; Patel, Smita; Kazerooni, Ella
2014-01-01
Purpose: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. Methods: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. Results: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features
Murad-Regadas, Sthela M; Pinheiro Regadas, Francisco Sergio; Rodrigues, Lusmar V; da Silva Vilarinho, Adjra; Buchen, Guilherme; Borges, Livia Olinda; Veras, Lara B; da Cruz, Mariana Murad
2016-12-01
Defecography is an established method of evaluating dynamic anorectal dysfunction, but conventional defecography does not allow for visualization of anatomic structures. The purpose of this study was to describe the use of dynamic 3-dimensional endovaginal ultrasonography for evaluating perineal descent in comparison with echodefecography (3-dimensional anorectal ultrasonography) and to study the relationship between perineal descent and symptoms and anatomic/functional abnormalities of the pelvic floor. This was a prospective study. The study was conducted at a large university tertiary care hospital. Consecutive female patients were eligible if they had pelvic floor dysfunction, obstructed defecation symptoms, and a score >6 on the Cleveland Clinic Florida Constipation Scale. Each patient underwent both echodefecography and dynamic 3-dimensional endovaginal ultrasonography to evaluate posterior pelvic floor dysfunction. Normal perineal descent was defined on echodefecography as puborectalis muscle displacement ≤2.5 cm; excessive perineal descent was defined as displacement >2.5 cm. Of 61 women, 29 (48%) had normal perineal descent; 32 (52%) had excessive perineal descent. Endovaginal ultrasonography identified 27 of the 29 patients in the normal group as having anorectal junction displacement ≤1 cm (mean = 0.6 cm; range, 0.1-1.0 cm) and a mean anorectal junction position of 0.6 cm (range, 0-2.3 cm) above the symphysis pubis during the Valsalva maneuver and correctly identified 30 of the 32 patients in the excessive perineal descent group. The κ statistic showed almost perfect agreement (κ = 0.86) between the 2 methods for categorization into the normal and excessive perineal descent groups. Perineal descent was not related to fecal or urinary incontinence or anatomic and functional factors (sphincter defects, pubovisceral muscle defects, levator hiatus area, grade II or III rectocele, intussusception, or anismus). The study did not include a
Three-dimensional reconstruction from real data using a conjugate gradient-coupled dipole method
International Nuclear Information System (INIS)
Chaumet, Patrick C; Belkebir, Kamal
2009-01-01
The aim of the present work is to validate a full vectorial electromagnetic inverse scattering algorithm against experimental data. Data were provided courtesy of Institut Fresnel, Marseille, France. These data were carried out in an anechoic chamber and correspond to different canonical targets as well as one mysterious object which is known only by experimentalists who measured the associated scattered field. The inverse algorithm was first developed in the optical domain and is adapted herein to the microwave domain. It is an iterative approach where the parameter of interest, namely the relative permittivity distribution, is updated gradually by minimizing a cost function describing the discrepancy between data and those that would be obtained via a forward solver for the best available estimate of the relative permittivity. The forward solver is based on the coupled dipole method which was introduced in the seventies to study the scattering of light by non-spherical dielectric grains. The forward and inverse schemes are briefly described and various examples are presented that demonstrate the efficiency of the inverse algorithm
Direct method of design and stress analysis of rotating disks with temperature gradient
Manson, S S
1950-01-01
A method is presented for the determination of the contour of disks, typified by those of aircraft gas turbines, to incorporate arbitrary elastic-stress distributions resulting from either centrifugal or combined centrifugal and thermal effects. The specified stress may be radial, tangential, or any combination of the two. Use is made of the finite-difference approach in solving the stress equations, the amount of computation necessary in the evolution of a design being greatly reduced by the judicious selection of point stations by the aid of a design chart. Use of the charts and of a preselected schedule of point stations is also applied to the direct problem of finding the elastic and plastic stress distribution in disks of a given design, thereby effecting a great reduction in the amount of calculation. Illustrative examples are presented to show computational procedures in the determination of a new design and in analyzing an existing design for elastic stress and for stresses resulting from plastic flow.
Kou, Jisheng
2015-08-01
Surface tension significantly impacts subsurface flow and transport, and it is the main cause of capillary effect, a major immiscible two-phase flow mechanism for systems with a strong wettability preference. In this paper, we consider the numerical simulation of the surface tension of multi-component mixtures with the gradient theory of fluid interfaces. Major numerical challenges include that the system of the Euler-Lagrange equations is solved on the infinite interval and the coefficient matrix is not positive definite. We construct a linear transformation to reduce the Euler-Lagrange equations, and naturally introduce a path function, which is proven to be a monotonic function of the spatial coordinate variable. By using the linear transformation and the path function, we overcome the above difficulties and develop the efficient methods for calculating the interface and its interior compositions. Moreover, the computation of the surface tension is also simplified. The proposed methods do not need to solve the differential equation system, and they are easy to be implemented in practical applications. Numerical examples are tested to verify the efficiency of the proposed methods. © 2014 Elsevier B.V.
International Nuclear Information System (INIS)
Kim, Hyun Keol; Charette, Andre
2007-01-01
The Sensitivity Function-based Conjugate Gradient Method (SFCGM) is described. This method is used to solve the inverse problems of function estimation, such as the local maps of absorption and scattering coefficients, as applied to optical tomography for biomedical imaging. A highly scattering, absorbing, non-reflecting, non-emitting medium is considered here and simultaneous reconstructions of absorption and scattering coefficients inside the test medium are achieved with the proposed optimization technique, by using the exit intensity measured at boundary surfaces. The forward problem is solved with a discrete-ordinates finite-difference method on the framework of the frequency-domain full equation of radiative transfer. The modulation frequency is set to 600 MHz and the frequency data, obtained with the source modulation, is used as the input data. The inversion results demonstrate that the SFCGM can retrieve simultaneously the spatial distributions of optical properties inside the medium within a reasonable accuracy, by significantly reducing a cross-talk between inter-parameters. It is also observed that the closer-to-detector objects are better retrieved
Barkeshli, Kasra; Volakis, John L.
1991-01-01
The theoretical and computational aspects related to the application of the Conjugate Gradient FFT (CGFFT) method in computational electromagnetics are examined. The advantages of applying the CGFFT method to a class of large scale scattering and radiation problems are outlined. The main advantages of the method stem from its iterative nature which eliminates a need to form the system matrix (thus reducing the computer memory allocation requirements) and guarantees convergence to the true solution in a finite number of steps. Results are presented for various radiators and scatterers including thin cylindrical dipole antennas, thin conductive and resistive strips and plates, as well as dielectric cylinders. Solutions of integral equations derived on the basis of generalized impedance boundary conditions (GIBC) are also examined. The boundary conditions can be used to replace the profile of a material coating by an impedance sheet or insert, thus, eliminating the need to introduce unknown polarization currents within the volume of the layer. A general full wave analysis of 2-D and 3-D rectangular grooves and cavities is presented which will also serve as a reference for future work.
Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods.
Gramfort, Alexandre; Kowalski, Matthieu; Hämäläinen, Matti
2012-04-07
Magneto- and electroencephalography (M/EEG) measure the electromagnetic fields produced by the neural electrical currents. Given a conductor model for the head, and the distribution of source currents in the brain, Maxwell's equations allow one to compute the ensuing M/EEG signals. Given the actual M/EEG measurements and the solution of this forward problem, one can localize, in space and in time, the brain regions that have produced the recorded data. However, due to the physics of the problem, the limited number of sensors compared to the number of possible source locations, and measurement noise, this inverse problem is ill-posed. Consequently, additional constraints are needed. Classical inverse solvers, often called minimum norm estimates (MNE), promote source estimates with a small ℓ₂ norm. Here, we consider a more general class of priors based on mixed norms. Such norms have the ability to structure the prior in order to incorporate some additional assumptions about the sources. We refer to such solvers as mixed-norm estimates (MxNE). In the context of M/EEG, MxNE can promote spatially focal sources with smooth temporal estimates with a two-level ℓ₁/ℓ₂ mixed-norm, while a three-level mixed-norm can be used to promote spatially non-overlapping sources between different experimental conditions. In order to efficiently solve the optimization problems of MxNE, we introduce fast first-order iterative schemes that for the ℓ₁/ℓ₂ norm give solutions in a few seconds making such a prior as convenient as the simple MNE. Furthermore, thanks to the convexity of the optimization problem, we can provide optimality conditions that guarantee global convergence. The utility of the methods is demonstrated both with simulations and experimental MEG data.
Piret, Cé cile
2012-01-01
Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper
Enumerating set partitions according to the number of descents of ...
Indian Academy of Sciences (India)
) according to the number of descents of size or more, where ≥ 1 is fixed. An explicit expression in terms of Stirling numbers of the second kind may be given for the total number of such descents in all the members of (,). We also ...
Testicular descent: INSL3, testosterone, genes and the intrauterine milieu
DEFF Research Database (Denmark)
Bay, Katrine; Main, Katharina M; Toppari, Jorma
2011-01-01
Complete testicular descent is a sign of, and a prerequisite for, normal testicular function in adult life. The process of testis descent is dependent on gubernacular growth and reorganization, which is regulated by the Leydig cell hormones insulin-like peptide 3 (INSL3) and testosterone. Investi...
43 CFR 10.14 - Lineal descent and cultural affiliation.
2010-10-01
... Hawaiian organization and the human remains, funerary objects, sacred objects, or objects of cultural... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Lineal descent and cultural affiliation... GRAVES PROTECTION AND REPATRIATION REGULATIONS General § 10.14 Lineal descent and cultural affiliation...
Planetary entry, descent, and landing technologies
Pichkhadze, K.; Vorontsov, V.; Polyakov, A.; Ivankov, A.; Taalas, P.; Pellinen, R.; Harri, A.-M.; Linkin, V.
2003-04-01
Martian meteorological lander (MML) is intended for landing on the Martian surface in order to monitor the atmosphere at landing point for one Martian year. MMLs shall become the basic elements of a global network of meteorological mini-landers, observing the dynamics of changes of the atmospheric parameters on the Red Planet. The MML main scientific tasks are as follows: (1) Study of vertical structure of the Martian atmosphere throughout the MML descent; (2) On-surface meteorological observations for one Martian year. One of the essential factors influencing the lander's design is its entry, descent, and landing (EDL) sequence. During Phase A of the MML development, five different options for the lander's design were carefully analyzed. All of these options ensure the accomplishment of the above-mentioned scientific tasks with high effectiveness. CONCEPT A (conventional approach): Two lander options (with a parachute system + airbag and an inflatable airbrake + airbag) were analyzed. They are similar in terms of fulfilling braking phases and completely analogous in landing by means of airbags. CONCEPT B (innovative approach): Three lander options were analyzed. The distinguishing feature is the presence of inflatable braking units (IBU) in their configurations. SELECTED OPTION (innovative approach): Incorporating a unique design approach and modern technologies, the selected option of the lander represents a combination of the options analyzed in the framework of Concept B study. Currently, the selected lander option undergoes systems testing (Phase D1). Several MMLs can be delivered to Mars in frameworks of various missions as primary or piggybacking payload: (1) USA-led "Mars Scout" (2007); (2) France-led "NetLander" (2007/2009); (3) Russia-led "Mars-Deimos-Phobos sample return" (2007); (4) Independent mission (currently under preliminary study); etc.
Focus measure method based on the modulus of the gradient of the color planes for digital microscopy
Hurtado-Pérez, Román; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso; Aguilar-Valdez, J. Félix; Ortega-Mendoza, Gabriel
2018-02-01
The modulus of the gradient of the color planes (MGC) is implemented to transform multichannel information to a grayscale image. This digital technique is used in two applications: (a) focus measurements during autofocusing (AF) process and (b) extending the depth of field (EDoF) by means of multifocus image fusion. In the first case, the MGC procedure is based on an edge detection technique and is implemented in over 15 focus metrics that are typically handled in digital microscopy. The MGC approach is tested on color images of histological sections for the selection of in-focus images. An appealing attribute of all the AF metrics working in the MGC space is their monotonic behavior even up to a magnification of 100×. An advantage of the MGC method is its computational simplicity and inherent parallelism. In the second application, a multifocus image fusion algorithm based on the MGC approach has been implemented on graphics processing units (GPUs). The resulting fused images are evaluated using a nonreference image quality metric. The proposed fusion method reveals a high-quality image independently of faulty illumination during the image acquisition. Finally, the three-dimensional visualization of the in-focus image is shown.
Mini-batch optimized full waveform inversion with geological constrained gradient filtering
Yang, Hui; Jia, Junxiong; Wu, Bangyu; Gao, Jinghuai
2018-05-01
High computation cost and generating solutions without geological sense have hindered the wide application of Full Waveform Inversion (FWI). Source encoding technique is a way to dramatically reduce the cost of FWI but subject to fix-spread acquisition setup requirement and slow convergence for the suppression of cross-talk. Traditionally, gradient regularization or preconditioning is applied to mitigate the ill-posedness. An isotropic smoothing filter applied on gradients generally gives non-geological inversion results, and could also introduce artifacts. In this work, we propose to address both the efficiency and ill-posedness of FWI by a geological constrained mini-batch gradient optimization method. The mini-batch gradient descent optimization is adopted to reduce the computation time by choosing a subset of entire shots for each iteration. By jointly applying the structure-oriented smoothing to the mini-batch gradient, the inversion converges faster and gives results with more geological meaning. Stylized Marmousi model is used to show the performance of the proposed method on realistic synthetic model.
Su, Cui; Su, Yunlan; Li, Zhiyong; Haq, Muhammad Abdul; Zhou, Yong; Wang, Dujin
2017-08-01
Bilayered poly(vinyl alcohol) (PVA)/hydroxyapatite (HA) composite hydrogels with anisotropic and gradient mechanical properties were prepared by the combination of directional freezing-thawing (DFT) and electrophoresis method. Firstly, PVA hydrogels with aligned channel structure were prepared by the DFT method. Then, HA nanoparticles were in situ synthesized within the PVA hydrogels via electrophoresis. By controlling the time of the electrophoresis process, a bilayered gradient hydrogel containing HA particles in only half of the gel region was obtained. The PVA/HA composite hydrogel exhibited gradient mechanical strength depending on the distance to the cathode. The gradient initial tensile modulus ranging from 0.18MPa to 0.27MPa and the gradient initial compressive modulus from 0.33MPa to 0.51MPa were achieved. The binding strength of the two regions was relatively high and no apparent internal stress or defect was observed at the boundary. The two regions of the bilayered hydrogel also showed different osteoblast cell adhesion properties. Copyright © 2017 Elsevier B.V. All rights reserved.
Radrizzani, Marina; Lo Cicero, Viviana; Soncin, Sabrina; Bolis, Sara; Sürder, Daniel; Torre, Tiziano; Siclari, Francesco; Moccetti, Tiziano; Vassalli, Giuseppe; Turchetto, Lucia
2014-09-27
Cardiovascular cell therapy represents a promising field, with several approaches currently being tested. The advanced therapy medicinal product (ATMP) for the ongoing METHOD clinical study ("Bone marrow derived cell therapy in the stable phase of chronic ischemic heart disease") consists of fresh mononuclear cells (MNC) isolated from autologous bone marrow (BM) through density gradient centrifugation on standard Ficoll-Paque. Cells are tested for safety (sterility, endotoxin), identity/potency (cell count, CD45/CD34/CD133, viability) and purity (contaminant granulocytes and platelets). BM-MNC were isolated by density gradient centrifugation on Ficoll-Paque. The following process parameters were optimized throughout the study: gradient medium density; gradient centrifugation speed and duration; washing conditions. A new manufacturing method was set up, based on gradient centrifugation on low density Ficoll-Paque, followed by 2 washing steps, of which the second one at low speed. It led to significantly higher removal of contaminant granulocytes and platelets, improving product purity; the frequencies of CD34+ cells, CD133+ cells and functional hematopoietic and mesenchymal precursors were significantly increased. The methodological optimization described here resulted in a significant improvement of ATMP quality, a crucial issue to clinical applications in cardiovascular cell therapy.
Directory of Open Access Journals (Sweden)
Shang Wang
2015-04-01
Full Text Available A methodology (HPLC proposed in this paper for simultaneously quantitative determination of ilaprazole and its related impurities in commercial tablets was developed and validated. The chromatographic separation was carried out by gradient elution using an Agilent C8 column (4.6 mm × 250 mm, 5 μm which was maintained at 25 °C. The mobile phase composed of solvent A (methanol and solvent B (solution consisting 0.02 mmol/l monopotassium phosphate and 0.025 mmol/l sodium hydroxide was at a flow rate of 1.0 ml/min. The samples were detected and quantified at 237 nm using an ultraviolet absorbance detector. Calibration curves of all analytes from 0.5 to 3.5 μg/ml were good linearity (r ≥ 0.9990 and recovery was greater than 99.5% for each analyte. The lower limit of detection (LLOD and quantification (LOQ of this analytical method were 10 ng/ml and 25 ng/ml for all impurities, respectively. The stress studies indicated that the degradation products could not interfere with the detection of ilaprazole and its related impurities and the assay can thus be considered stability-indicating. The method precisions were in the range of 0.41–1.21 while the instrument precisions were in the range of 0.38–0.95 in terms of peak area RSD% for all impurities, respectively. This method is considered stability-indicating and is applicable for accurate and simultaneous measuring of the ilaprazole and its related impurities in commercial enteric-coated tablets.
Tietjen, Gregory T; Kong, Yupeng; Parthasarathy, Raghuveer
2008-07-07
Interparticle interaction energies and other useful physical characteristics can be extracted from the statistical properties of the motion of particles confined by an optical line trap. In practice, however, the potential energy landscape, U(x), imposed by the line provides an extra, and in general unknown, influence on particle dynamics. We describe a new class of line traps in which both the optical gradient and scattering forces acting on a trapped particle are designed to be linear functions of the line coordinate and in which their magnitude can be counterbalanced to yield a flat U(x). These traps are formed using approximate solutions to general relations concerning non-conservative optical forces that have been the subject of recent investigations [Y. Roichman, B. Sun, Y. Roichman, J. Amato-Grill, and D. G. Grier, Phys. Rev. Lett. 100, 013602-4 (2008).]. We implement the lines using holographic optical trapping and measure the forces acting on silica microspheres, demonstrating the tunability of the confining potential energy landscape. Furthermore, we show that our approach efficiently directs available laser power to the trap, in contrast to other methods.
Directory of Open Access Journals (Sweden)
Shuang Rong
2015-12-01
Full Text Available Aiming to relieve the large amount of wind power curtailment during the heating period in the North China region, a thermal-electric decoupling (TED approach is proposed to both bring down the constraint of forced power output of combined heat and power plants and increase the electric load level during valley load times that assist the power grid in consuming more wind power. The operating principles of the thermal-electric decoupling approach is described, the mathematical model of its profits is developed, the constraint conditions of its operation are listed, also, an improved parallel conjugate gradient is utilized to bypass the saddle problem and accelerate the optimal speed. Numerical simulations are implemented and reveal an optimal allocation of TED which with a rated power of 280 MW and 185 MWh heat storage capacity are possible. This allocation of TED could bring approximately 16.9 billion Yuan of economic profit and consume more than 80% of the surplus wind energy which would be curtailed without the participation of TED. The results in this article verify the effectiveness of this method that could provide a referential guidance for thermal-electric decoupling system allocation in practice.
Jung, Youngkyoo; Samsonov, Alexey A; Bydder, Mark; Block, Walter F
2011-04-01
To remove phase inconsistencies between multiple echoes, an algorithm using a radial acquisition to provide inherent phase and magnitude information for self correction was developed. The information also allows simultaneous support for parallel imaging for multiple coil acquisitions. Without a separate field map acquisition, a phase estimate from each echo in multiple echo train was generated. When using a multiple channel coil, magnitude and phase estimates from each echo provide in vivo coil sensitivities. An algorithm based on the conjugate gradient method uses these estimates to simultaneously remove phase inconsistencies between echoes, and in the case of multiple coil acquisition, simultaneously provides parallel imaging benefits. The algorithm is demonstrated on single channel, multiple channel, and undersampled data. Substantial image quality improvements were demonstrated. Signal dropouts were completely removed and undersampling artifacts were well suppressed. The suggested algorithm is able to remove phase cancellation and undersampling artifacts simultaneously and to improve image quality of multiecho radial imaging, the important technique for fast three-dimensional MRI data acquisition. Copyright © 2011 Wiley-Liss, Inc.
Ge, Lan; Kino, Aya; Lee, Daniel; Dharmakumar, Rohan; Carr, James C; Li, Debiao
2010-01-01
First-pass perfusion magnetic resonance imaging (MRI) is a promising technique for detecting ischemic heart disease. However, the diagnostic value of the method is limited by the low spatial coverage, resolution, signal-to-noise ratio (SNR), and cardiac motion-related image artifacts. A combination of sliding window and conjugate-gradient HighlY constrained back-PRojection reconstruction (SW-CG-HYPR) method has been proposed in healthy volunteer studies to reduce the acquisition window for each slice while maintaining the temporal resolution of 1 frame per heartbeat in myocardial perfusion MRI. This method allows for improved spatial coverage, resolution, and SNR. In this study, we use a controlled animal model to test whether the myocardial territory supplied by a stenotic coronary artery can be detected accurately by SW-CG-HYPR perfusion method under pharmacological stress. Results from 6 mongrel dogs (15-25 kg) studies demonstrate the feasibility of SW-CG-HYPR to detect regional perfusion defects. Using this method, the acquisition time per cardiac cycle was reduced by a factor of 4, and the spatial coverage was increased from 2 to 3 slices to 6 slices as compared with the conventional techniques including both turbo-Fast Low Angle Short (FLASH) and echoplanar imaging (EPI). The SNR of the healthy myocardium at peak enhancement with SW-CG-HYPR (12.68 ± 2.46) is significantly higher (P < 0.01) than the turbo-FLASH (8.65 ± 1.93) and EPI (5.48 ± 1.24). The spatial resolution of SW-CG-HYPR images is 1.2 × 1.2 × 8.0 mm, which is better than the turbo-FLASH (1.8 × 1.8 × 8.0 mm) and EPI (2.0 × 1.8 × 8.0 mm). Sliding-window CG-HYPR is a promising technique for myocardial perfusion MRI. This technique provides higher image quality with respect to significantly improved SNR and spatial resolution of the myocardial perfusion images, which might improve myocardial perfusion imaging in a clinical setting.
Energy Technology Data Exchange (ETDEWEB)
Peter W. Carr; K.M. Fuller; D.R. Stoll; L.D. Steinkraus; M.S. Pasha; Glenn G. Hardin
2005-12-30
A new approach has been developed by modifying a conventional gradient elution liquid chromatograph for the high throughput screening of biological samples to detect the presence of regulated intoxicants. The goal of this work was to improve the speed of a gradient elution screening method over current approaches by optimizing the operational parameters of both the column and the instrument without compromising the reproducibility of the retention times, which are the basis for the identification. Most importantly, the novel instrument configuration substantially reduces the time needed to re-equilibrate the column between gradient runs, thereby reducing the total time for each analysis. The total analysis time for each gradient elution run is only 2.8 minutes, including 0.3 minutes for column reequilibration between analyses. Retention times standard calibration solutes are reproducible to better than 0.002 minutes in consecutive runs. A corrected retention index was adopted to account for day-to-day and column-to-column variations in retention time. The discriminating power and mean list length were calculated for a library of 47 intoxicants and compared with previous work from other laboratories to evaluate fast gradient elution HPLC as a screening tool.
in a Family of South Indian Descent
Directory of Open Access Journals (Sweden)
Muthiah Subramanian
2015-01-01
Full Text Available Inherited channelopathies are a heterogeneous group of disorders resulting from dysfunction of ion channels in cellular membranes. They may manifest as diseases affecting skeletal muscle contraction, the conduction system of the heart, nervous system function, and vision syndromes. We describe a family of South Indian descent with hypokalemic periodic paralysis in which four members also have idiopathic generalized epilepsy. Hypokalemic periodic paralysis is a genetically heterogeneous channelopathy that has been linked to mutations in genes encoding three ion channels CACNIAS, SCN4A, and KCNJ2 predominantly. Although data on specific gene in idiopathic generalized epilepsy is relatively scarce, mutations of voltage gated sodium channel subunit genes (CACNB4 and nonsense mutations in voltage gated calcium channels (CACNA1A have been linked to idiopathic generalized epilepsy in two families. We speculate that gene mutations altering the ability of the beta subunit to interact with the alpha subunit of the CaV1.1 channel and mutations in the pore-forming potassium channel subunit may be possible explanations for the combined manifestation of both diseases. Functional analysis of voltage gated calcium channel and other ion channels mutations may provide additional support and insight for the causal role of these mutations. The understanding of mutations in ion-channel genes will lead to improved diagnosis and treatment of such inherited channelopathies.
An Efficient Approach for Solving Mesh Optimization Problems Using Newton’s Method
Directory of Open Access Journals (Sweden)
Jibum Kim
2014-01-01
Full Text Available We present an efficient approach for solving various mesh optimization problems. Our approach is based on Newton’s method, which uses both first-order (gradient and second-order (Hessian derivatives of the nonlinear objective function. The volume and surface mesh optimization algorithms are developed such that mesh validity and surface constraints are satisfied. We also propose several Hessian modification methods when the Hessian matrix is not positive definite. We demonstrate our approach by comparing our method with nonlinear conjugate gradient and steepest descent methods in terms of both efficiency and mesh quality.
Directory of Open Access Journals (Sweden)
Meliefste Kees
2006-06-01
Full Text Available Abstract Background Air pollution in São Paulo is constantly being measured by the State of Sao Paulo Environmental Agency, however there is no information on the variation between places with different traffic densities. This study was intended to identify a gradient of exposure to traffic-related air pollution within different areas in São Paulo to provide information for future epidemiological studies. Methods We measured NO2 using Palmes' diffusion tubes in 36 sites on streets chosen to be representative of different road types and traffic densities in São Paulo in two one-week periods (July and August 2000. In each study period, two tubes were installed in each site, and two additional tubes were installed in 10 control sites. Results Average NO2 concentrations were related to traffic density, observed on the spot, to number of vehicles counted, and to traffic density strata defined by the city Traffic Engineering Company (CET. Average NO2concentrations were 63μg/m3 and 49μg/m3 in the first and second periods, respectively. Dividing the sites by the observed traffic density, we found: heavy traffic (n = 17: 64μg/m3 (95% CI: 59μg/m3 – 68μg/m3; local traffic (n = 16: 48μg/m3 (95% CI: 44μg/m3 – 52μg/m3 (p Conclusion The differences in NO2 levels between heavy and local traffic sites are large enough to suggest the use of a more refined classification of exposure in epidemiological studies in the city. Number of vehicles counted, traffic density observed on the spot and traffic density strata defined by the CET might be used as a proxy for traffic exposure in São Paulo when more accurate measurements are not available.
On the efficiency of a randomized mirror descent algorithm in online optimization problems
Gasnikov, A. V.; Nesterov, Yu. E.; Spokoiny, V. G.
2015-04-01
A randomized online version of the mirror descent method is proposed. It differs from the existing versions by the randomization method. Randomization is performed at the stage of the projection of a subgradient of the function being optimized onto the unit simplex rather than at the stage of the computation of a subgradient, which is common practice. As a result, a componentwise subgradient descent with a randomly chosen component is obtained, which admits an online interpretation. This observation, for example, has made it possible to uniformly interpret results on weighting expert decisions and propose the most efficient method for searching for an equilibrium in a zero-sum two-person matrix game with sparse matrix.
Directory of Open Access Journals (Sweden)
Bingfei Fan
2017-05-01
Full Text Available Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm.
Automation for Accommodating Fuel-Efficient Descents in Constrained Airspace
Coopenbarger, Richard A.
2010-01-01
Continuous descents at low engine power are desired to reduce fuel consumption, emissions and noise during arrival operations. The challenge is to allow airplanes to fly these types of efficient descents without interruption during busy traffic conditions. During busy conditions today, airplanes are commonly forced to fly inefficient, step-down descents as airtraffic controllers work to ensure separation and maximize throughput. NASA in collaboration with government and industry partners is developing new automation to help controllers accommodate continuous descents in the presence of complex traffic and airspace constraints. This automation relies on accurate trajectory predictions to compute strategic maneuver advisories. The talk will describe the concept behind this new automation and provide an overview of the simulations and flight testing used to develop and refine its underlying technology.
Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm
Desmal, Abdulla; Bagci, Hakan
2017-01-01
steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without
ExoMars entry, descent and landing science
Ferri, F.; Lewis, S. R.; Withers, P.; Aboudan, A.; Bettanini, C.; Colombatti, G.; Debei, S.; Golombek, M.; Harri, A. M.; Komatsu, G.; Leese, M. R.; Mäkinen, T.; Müller-Wodarg, I.; Ori, G. G.; Patel, M. R.
2011-01-01
The entry, descent and landing of ExoMars offer a rare (once-per-mission) opportunity to perform in situ investigation of the martian environment over a wide altitude range. Entry, Descent and Landing System (EDLS) measurements can provide essential data for atmospheric scientific investigations.\\ud \\ud We intend to perform atmospheric science measurements by exploiting data from EDLS engineering sensors and exploiting their readings beyond the expected engineering information.
International Nuclear Information System (INIS)
Roidl, B.; Meinke, M.; Schröder, W.
2013-01-01
Highlights: • A synthetic turbulence generation method (STGM) is presented. • STGM is applied to sub and supersonic flows at low and moderate Reynolds numbers. • STGM shows a convincing quality in zonal RANS–LES for flat-plate boundary layers (BLs). • A good agreement with the pure LES and reference DNS findings is obtained. • RANS-to-LES transition length is reduced to less than four boundary-layer thicknesses. -- Abstract: A synthetic turbulence generation (STG) method for subsonic and supersonic flows at low and moderate Reynolds numbers to provide inflow distributions of zonal Reynolds-averaged Navier–Stokes (RANS) – large-eddy simulation (LES) methods is presented. The STG method splits the LES inflow region into three planes where a local velocity signal is decomposed from the turbulent flow properties of the upstream RANS solution. Based on the wall-normal position and the local flow Reynolds number, specific length and velocity scales with different vorticity content are imposed at the inlet plane of the boundary layer. The quality of the STG method for incompressible and compressible zero-pressure gradient boundary layers is shown by comparing the zonal RANS–LES data with pure LES, pure RANS, and direct numerical simulation (DNS) solutions. The distributions of the time and spanwise wall-shear stress, Reynolds stress distributions, and two point correlations of the zonal RANS–LES simulations are smooth in the transition region and in good agreement with the pure LES and reference DNS findings. The STG approach reduces the RANS-to-LES transition length to less than four boundary-layer thicknesses
Batty, Christopher
2017-02-01
This paper introduces a two-dimensional cell-centred finite volume discretization of the Poisson problem on adaptive Cartesian quadtree grids which exhibits second order accuracy in both the solution and its gradients, and requires no grading condition between adjacent cells. At T-junction configurations, which occur wherever resolution differs between neighboring cells, use of the standard centred difference gradient stencil requires that ghost values be constructed by interpolation. To properly recover second order accuracy in the resulting numerical gradients, prior work addressing block-structured grids and graded trees has shown that quadratic, rather than linear, interpolation is required; the gradients otherwise exhibit only first order convergence, which limits potential applications such as fluid flow. However, previous schemes fail or lose accuracy in the presence of the more complex T-junction geometries arising in the case of general non-graded quadtrees, which place no restrictions on the resolution of neighboring cells. We therefore propose novel quadratic interpolant constructions for this case that enable second order convergence by relying on stencils oriented diagonally and applied recursively as needed. The method handles complex tree topologies and large resolution jumps between neighboring cells, even along the domain boundary, and both Dirichlet and Neumann boundary conditions are supported. Numerical experiments confirm the overall second order accuracy of the method in the L∞ norm.
A modified three-term PRP conjugate gradient algorithm for optimization models.
Wu, Yanlin
2017-01-01
The nonlinear conjugate gradient (CG) algorithm is a very effective method for optimization, especially for large-scale problems, because of its low memory requirement and simplicity. Zhang et al. (IMA J. Numer. Anal. 26:629-649, 2006) firstly propose a three-term CG algorithm based on the well known Polak-Ribière-Polyak (PRP) formula for unconstrained optimization, where their method has the sufficient descent property without any line search technique. They proved the global convergence of the Armijo line search but this fails for the Wolfe line search technique. Inspired by their method, we will make a further study and give a modified three-term PRP CG algorithm. The presented method possesses the following features: (1) The sufficient descent property also holds without any line search technique; (2) the trust region property of the search direction is automatically satisfied; (3) the steplengh is bounded from below; (4) the global convergence will be established under the Wolfe line search. Numerical results show that the new algorithm is more effective than that of the normal method.
A neural method for determining electromagnetic shower positions in laterally segmented calorimeters
International Nuclear Information System (INIS)
Roy, A.; Ray, A.; Mitra, T.; Roy, A.
1995-01-01
A method based on a neural network technique is proposed to calculate the coordinates of an incident photon striking a laterally segmented calorimeter and depositing shower energies in different segments. The technique uses a multilayer perceptron trained by back-propagation implemented through standard gradient descent followed by conjugate gradient algorithms and has been demonstrated with GEANT simulations of a BAF2 detector array. The position resolution results obtained by using this method are found to be substantially better than the first moment method with logarithmic weighting. (orig.)
International Nuclear Information System (INIS)
Aruchunan, E.
2015-01-01
In this paper, we have examined the effectiveness of the quarter-sweep iteration concept on conjugate gradient normal residual (CGNR) iterative method by using composite Simpson's (CS) and finite difference (FD) discretization schemes in solving Fredholm integro-differential equations. For comparison purposes, Gauss- Seidel (GS) and the standard or full- and half-sweep CGNR methods namely FSCGNR and HSCGNR are also presented. To validate the efficacy of the proposed method, several analyses were carried out such as computational complexity and percentage reduction on the proposed and existing methods. (author)
Wang, Yaohui; Xin, Xuegang; Guo, Lei; Chen, Zhifeng; Liu, Feng
2018-05-01
The switching of a gradient coil current in magnetic resonance imaging will induce an eddy current in the surrounding conducting structures while the secondary magnetic field produced by the eddy current is harmful for the imaging. To minimize the eddy current effects, the stray field shielding in the gradient coil design is usually realized by minimizing the magnetic fields on the cryostat surface or the secondary magnetic fields over the imaging region. In this work, we explicitly compared these two active shielding design methods. Both the stray field and eddy current on the cryostat inner surface were quantitatively discussed by setting the stray field constraint with an ultra-low maximum intensity of 2 G and setting the secondary field constraint with an extreme small shielding ratio of 0.000 001. The investigation revealed that the secondary magnetic field control strategy can produce coils with a better performance. However, the former (minimizing the magnetic fields) is preferable when designing a gradient coil with an ultra-low eddy current that can also strictly control the stray field leakage at the edge of the cryostat inner surface. A wrapped-edge gradient coil design scheme was then optimized for a more effective control of the stray fields. The numerical simulation on the wrapped-edge coil design shows that the optimized wrapping angles for the x and z coils in terms of our coil dimensions are 40° and 90°, respectively.
Seasonal variability and descent of mid-latitude sporadic E layers at Arecibo
Directory of Open Access Journals (Sweden)
N. Christakis
2009-03-01
Full Text Available Sporadic E layers (Es follow regular daily patterns in variability and altitude descent, which are determined primarily by the vertical tidal wind shears in the lower thermosphere. In the present study a large set of sporadic E layer incoherent scatter radar (ISR measurements are analyzed. These were made at Arecibo (Geog. Lat. ~18° N; Magnetic Dip ~50° over many years with ISR runs lasting from several hours to several days, covering evenly all seasons. A new methodology is applied, in which both weak and strong layers are clearly traced by using the vertical electron density gradient as a function of altitude and time. Taking a time base equal to the 24-h local day, statistics were obtained on the seasonal behavior of the diurnal and semidiurnal tidal variability and altitude descent patterns of sporadic E at Arecibo. The diurnal tide, most likely the S(1,1 tide with a vertical wavelength around 25 km, controls fully the formation and descent of the metallic Es layers at low altitudes below 110 km. At higher altitudes, there are two prevailing layers formed presumably by vertical wind shears associated mainly with semidiurnal tides. These include: 1 a daytime layer starting at ~130 km around midday and descending down to 105 km by local midnight, and 2 a less frequent and weaker nighttime layer which starts prior to midnight at ~130 km, descending downwards at somewhat faster rate to reach 110 km by sunrise. The diurnal and semidiurnal-like pattern prevails, with some differences, in all seasons. The differences in occurrence, strength and descending speeds between the daytime and nighttime upper layers are not well understood from the present data alone and require further study.
Design of automation tools for management of descent traffic
Erzberger, Heinz; Nedell, William
1988-01-01
The design of an automated air traffic control system based on a hierarchy of advisory tools for controllers is described. Compatibility of the tools with the human controller, a key objective of the design, is achieved by a judicious selection of tasks to be automated and careful attention to the design of the controller system interface. The design comprises three interconnected subsystems referred to as the Traffic Management Advisor, the Descent Advisor, and the Final Approach Spacing Tool. Each of these subsystems provides a collection of tools for specific controller positions and tasks. This paper focuses primarily on the Descent Advisor which provides automation tools for managing descent traffic. The algorithms, automation modes, and graphical interfaces incorporated in the design are described. Information generated by the Descent Advisor tools is integrated into a plan view traffic display consisting of a high-resolution color monitor. Estimated arrival times of aircraft are presented graphically on a time line, which is also used interactively in combination with a mouse input device to select and schedule arrival times. Other graphical markers indicate the location of the fuel-optimum top-of-descent point and the predicted separation distances of aircraft at a designated time-control point. Computer generated advisories provide speed and descent clearances which the controller can issue to aircraft to help them arrive at the feeder gate at the scheduled times or with specified separation distances. Two types of horizontal guidance modes, selectable by the controller, provide markers for managing the horizontal flightpaths of aircraft under various conditions. The entire system consisting of descent advisor algorithm, a library of aircraft performance models, national airspace system data bases, and interactive display software has been implemented on a workstation made by Sun Microsystems, Inc. It is planned to use this configuration in operational
Directory of Open Access Journals (Sweden)
Andre Lamert
2018-03-01
Full Text Available We present and compare two flexible and effective methodologies to predict disturbance zones ahead of underground tunnels by using elastic full-waveform inversion. One methodology uses a linearized, iterative approach based on misfit gradients computed with the adjoint method while the other uses iterative, gradient-free unscented Kalman filtering in conjunction with a level-set representation. Whereas the former does not involve a priori assumptions on the distribution of elastic properties ahead of the tunnel, the latter introduces a massive reduction in the number of explicit model parameters to be inverted for by focusing on the geometric form of potential disturbances and their average elastic properties. Both imaging methodologies are validated through successful reconstructions of simple disturbances. As an application, we consider an elastic multiple disturbance scenario. By using identical synthetic time-domain seismograms as test data, we obtain satisfactory, albeit different, reconstruction results from the two inversion methodologies. The computational costs of both approaches are of the same order of magnitude, with the gradient-based approach showing a slight advantage. The model parameter space reduction approach compensates for this by additionally providing a posteriori estimates of model parameter uncertainty. Keywords: Tunnel seismics, Full waveform inversion, Seismic waves, Level-set method, Adjoint method, Kalman filter
Electric field gradients in metals
International Nuclear Information System (INIS)
Schatz, G.
1979-01-01
A review of the recent works on electric field gradient in metals is given. The main emphasis is put on the temperature dependence of the electric field gradient in nonmagnetic metals. Some methods of investigation of this effect using nuclear probes are described. One of them is nuclear accoustic resonance method. (S.B.)
Rendell, Alistair P.; Lee, Timothy J.
1991-01-01
The analytic energy gradient for the single and double excitation coupled-cluster (CCSD) wave function has been reformulated and implemented in a new set of programs. The reformulated set of gradient equations have a smaller computational cost than any previously published. The iterative solution of the linear equations and the construction of the effective density matrices are fully vectorized, being based on matrix multiplications. The new method has been used to investigate the Cl2O2 molecule, which has recently been postulated as an important intermediate in the destruction of ozone in the stratosphere. In addition to reporting computational timings, the CCSD equilibrium geometries, harmonic vibrational frequencies, infrared intensities, and relative energetics of three isomers of Cl2O2 are presented.
International Nuclear Information System (INIS)
Junlowjiraya, V.
1989-01-01
In a nuclear power plant the use of high quality water is very important to minimize corrosion and downtime of a plant system. To evaluate the quality of water the most widely used instrument is a conductivity analyzer. However, conductivity monitor is nonspecific, the conductivity signal cannot give information about what species or impurities are presented in the water, steam, and condensate. To determine these impurities qualitatively and quantitatively, the ion chromatography is an effective technique. This presentation demonstrates an improvement of gradient ion chromatographic technique to solve lithium interference in the borated samples. The data acquisition system and computer automation setup for the analysis are also discussed
Distributed Gradient Descent for Solving Optimal Power Flow in Radial Networks
Gan, Lingwen; Low, Steven H.
2016-01-01
Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control, One embodiment includes a node controller comprising a memory containing: a plurality of node operating parameters; and a plurality of node operating parameters describing operating parameters for a set of at least one node selected from the group consisting of at least one downstream node and at least one upstream node; wherein the processor is configured by the ...
A Numerical Approach to Optimal Coherent Quantum LQG Controller Design Using Gradient Descent
Sichani, Arash Kh.; Vladimirov, Igor G.; Petersen, Ian R.
2016-01-01
This paper is concerned with coherent quantum linear quadratic Gaussian (CQLQG) control. The problem is to find a stabilizing measurement-free quantum controller for a quantum plant so as to minimize a mean square cost for the fully quantum closed-loop system. The plant and controller are open quantum systems interconnected through bosonic quantum fields. In comparison with the observation-actuation structure of classical controllers, coherent quantum feedback is less invasive to the quantum ...
Ryan, Niall J.; Kinnison, Douglas E.; Garcia, Rolando R.; Hoffmann, Christoph G.; Palm, Mathias; Raffalski, Uwe; Notholt, Justus
2018-02-01
We investigate the reliability of using trace gas measurements from remote sensing instruments to infer polar atmospheric descent rates during winter within 46-86 km altitude. Using output from the Specified Dynamics Whole Atmosphere Community Climate Model (SD-WACCM) between 2008 and 2014, tendencies of carbon monoxide (CO) volume mixing ratios (VMRs) are used to assess a common assumption of dominant vertical advection of tracers during polar winter. The results show that dynamical processes other than vertical advection are not negligible, meaning that the transport rates derived from trace gas measurements do not represent the mean descent of the atmosphere. The relative importance of vertical advection is lessened, and exceeded by other processes, during periods directly before and after a sudden stratospheric warming, mainly due to an increase in eddy transport. It was also found that CO chemistry cannot be ignored in the mesosphere due to the night-time layer of OH at approximately 80 km altitude. CO VMR profiles from the Kiruna Microwave Radiometer and the Microwave Limb Sounder were compared to SD-WACCM output, and show good agreement on daily and seasonal timescales. SD-WACCM CO profiles are combined with the CO tendencies to estimate errors involved in calculating the mean descent of the atmosphere from remote sensing measurements. The results indicate errors on the same scale as the calculated descent rates, and that the method is prone to a misinterpretation of the direction of air motion. The true rate of atmospheric descent is seen to be masked by processes, other than vertical advection, that affect CO. We suggest an alternative definition of the rate calculated using remote sensing measurements: not as the mean descent of the atmosphere, but as an effective rate of vertical transport for the trace gas under observation.
Directory of Open Access Journals (Sweden)
de Graft Aikins Ama
2009-08-01
Full Text Available Abstract Background Most European countries are ethnically and culturally diverse. Globally, cardiovascular disease (CVD is the leading cause of death. The major risk factors for CVD have been well established. This picture holds true for all regions of the world and in different ethnic groups. However, the prevalence of CVD and related risk factors vary among ethnic groups. Methods This article provides a review of current understanding of the epidemiology of vascular disease, principally coronary heart disease (CHD, stroke and related risk factors among populations of Sub-Sahara African descent (henceforth, African descent in comparison with the European populations in Europe. Results Compared with European populations, populations of African descent have an increased risk of stroke, whereas CHD is less common. They also have higher rates of hypertension and diabetes than European populations. Obesity is highly prevalent, but smoking rate is lower among African descent women. Older people of African descent have more favourable lipid profile and dietary habits than their European counterparts. Alcohol consumption is less common among populations of African descent. The rate of physical activity differs between European countries. Dutch African-Suriname men and women are less physically active than the White-Dutch whereas British African women are more physically active than women in the general population. Literature on psychosocial stress shows inconsistent results. Conclusion Hypertension and diabetes are highly prevalent among African populations, which may explain their high rate of stroke in Europe. The relatively low rate of CHD may be explained by the low rates of other risk factors including a more favourable lipid profile and the low prevalence of smoking. The risk factors are changing, and on the whole, getting worse especially among African women. Cohort studies and clinical trials are therefore needed among these groups to
Gender difference in metacarpal descent of fifth metacarpal
International Nuclear Information System (INIS)
Rafique, A.; Ali, H.; Ghani, S.
2006-01-01
To determine the difference in metacarpal descent of fifth metacarpal between men and women. Skyline of the 2nd and 3rd metacarpals were used as reference line, from which the descent of the 5th metacarpal head was measured. The position of 5th metacarpal head was documented as angle X. Metacarpal descent was defined as the difference between angle 'X' in relaxed and clenched fist position. The relaxed position was standardized by placing the forearm, wrist and palm on a shaped woodblock such that the wrist would be held in 25 - 30 degree in extension by a triangular spur, supported the 3rd metacarpal only. It was ensured that the movement of 4th and 5th metacarpals were not impaired. Analysis of variance was performed to compare the significance of means between genders at p < 0.05 level of significance. Metacarpal descent of the 5th metacarpal of both hands was significantly greater for women, with a mean of 7 degree as compared with a mean of 4 degree for the men. This decrease in angle 'X' was significant for the right 5th metacarpal relaxed and fist position and the fist position on the left. In contrast, women showed no significant differences between the various age groups for any of the variables tested.There was no relationship between metacarpal descent and hand dominance.Difference in metacarpal descent between men and women is significant and must be kept in mind when hand function is evaluated in both genders to assess the outcome of treatment and rehabilitation. (author)
INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES
Directory of Open Access Journals (Sweden)
H. Shen
2012-08-01
Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.
Bates, Kevin R.; Daniels, Andrew D.; Scuseria, Gustavo E.
1998-01-01
We report a comparison of two linear-scaling methods which avoid the diagonalization bottleneck of traditional electronic structure algorithms. The Chebyshev expansion method (CEM) is implemented for carbon tight-binding calculations of large systems and its memory and timing requirements compared to those of our previously implemented conjugate gradient density matrix search (CG-DMS). Benchmark calculations are carried out on icosahedral fullerenes from C60 to C8640 and the linear scaling memory and CPU requirements of the CEM demonstrated. We show that the CPU requisites of the CEM and CG-DMS are similar for calculations with comparable accuracy.
Entry, Descent and Landing Systems Analysis Study: Phase 1 Report
DwyerCianciolo, Alicia M.; Davis, Jody L.; Komar, David R.; Munk, Michelle M.; Samareh, Jamshid A.; Powell, Richard W.; Shidner, Jeremy D.; Stanley, Douglas O.; Wilhite, Alan W.; Kinney, David J.;
2010-01-01
NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to make in order to successfully land large payloads at Mars for both robotic and human-scale missions. This paper summarizes the motivation, approach and top-level results from Year 1 of the study, which focused on landing 10-50 mt on Mars, but also included a trade study of the best advanced parachute design for increasing the landed payloads within the EDL architecture of the Mars Science Laboratory (MSL) mission
Assessment of diagnosing metastatic bone tumor on T2*-weighted images. Comparison between turbo spin echo (TSE) method and gradient echo (GE) method
International Nuclear Information System (INIS)
Hayashi, Takahiko; Sugiyama, Akira; Katayama, Motoyuki
1996-01-01
We examined the usefulness of T2 * weighted gradient field echo images for diagnosis for metastatic bone tumors in comparison with T2 weighted turbo spin echo (fast spin echo) images. In T2 * weighted gradient field echo sequence to obtain maximum contrast-to-noise ratio (CNR), we experimentally manipulated flip angle (FA) (5deg-90deg), repetition time (TR) (400, 700 msec), and echo time (TE) (10-50 msec). The best CNR was 16.4 in fast low angle shot (FLASH) (TE: 24 msec, TR: 700 msec, FA: 40deg). Magnetic resonance imaging was carried out in 28 patients with metastatic bone tumors. In addition to conventional T1 weighted spin echo images, T2 weighted turbo spin echo (fast spin echo images) and T2 * weighted gradient field echo images were obtained. T2 * weighted gradient field echo images were superior to T2 weighted turbo spin echo (fast spin echo) images in delineating the tumors, adjacent fat tissues, and bone marrow. (author)
Connan, O; Maro, D; Hébert, D; Solier, L; Caldeira Ideas, P; Laguionie, P; St-Amant, N
2015-10-01
The behaviour of tritium in the environment is linked to the water cycle. We compare three methods of calculating the tritium evapotranspiration flux from grassland cover. The gradient and eddy covariance methods, together with a method based on the theoretical Penmann-Monteith model were tested in a study carried out in 2013 in an environment characterised by high levels of tritium activity. The results show that each of the three methods gave similar results. The various constraints applying to each method are discussed. The results show a tritium evapotranspiration flux of around 15 mBq m(-2) s(-1) in this environment. These results will be used to improve the entry parameters for the general models of tritium transfers in the environment. Copyright © 2015 Elsevier Ltd. All rights reserved.
Klett, James W [Knoxville, TN; Cameron, Christopher Stan [Sanford, NC
2010-03-02
A carbon based foam article is made by heating the surface of a carbon foam block to a temperature above its graphitizing temperature, which is the temperature sufficient to graphitize the carbon foam. In one embodiment, the surface is heated with infrared pulses until heat is transferred from the surface into the core of the foam article such that the graphitizing temperature penetrates into the core to a desired depth below the surface. The graphitizing temperature is maintained for a time sufficient to substantially entirely graphitize the portion of the foam article from the surface to the desired depth below the surface. Thus, the foam article is an integral monolithic material that has a desired conductivity gradient with a relatively high thermal conductivity in the portion of the core that was graphitized and a relatively low thermal conductivity in the remaining portion of the foam article.
Pixel-based OPC optimization based on conjugate gradients.
Ma, Xu; Arce, Gonzalo R
2011-01-31
Optical proximity correction (OPC) methods are resolution enhancement techniques (RET) used extensively in the semiconductor industry to improve the resolution and pattern fidelity of optical lithography. In pixel-based OPC (PBOPC), the mask is divided into small pixels, each of which is modified during the optimization process. Two critical issues in PBOPC are the required computational complexity of the optimization process, and the manufacturability of the optimized mask. Most current OPC optimization methods apply the steepest descent (SD) algorithm to improve image fidelity augmented by regularization penalties to reduce the complexity of the mask. Although simple to implement, the SD algorithm converges slowly. The existing regularization penalties, however, fall short in meeting the mask rule check (MRC) requirements often used in semiconductor manufacturing. This paper focuses on developing OPC optimization algorithms based on the conjugate gradient (CG) method which exhibits much faster convergence than the SD algorithm. The imaging formation process is represented by the Fourier series expansion model which approximates the partially coherent system as a sum of coherent systems. In order to obtain more desirable manufacturability properties of the mask pattern, a MRC penalty is proposed to enlarge the linear size of the sub-resolution assistant features (SRAFs), as well as the distances between the SRAFs and the main body of the mask. Finally, a projection method is developed to further reduce the complexity of the optimized mask pattern.
Gradient Boosting Machines, A Tutorial
Directory of Open Access Journals (Sweden)
Alexey eNatekin
2013-12-01
Full Text Available Gradient boosting machines are a family of powerful machine-learning techniques that have shown considerable success in a wide range of practical applications. They are highly customizable to the particular needs of the application, like being learned with respect to different loss functions. This article gives a tutorial introduction into the methodology of gradient boosting methods. A theoretical information is complemented with many descriptive examples and illustrations which cover all the stages of the gradient boosting model design. Considerations on handling the model complexity are discussed. A set of practical examples of gradient boosting applications are presented and comprehensively analyzed.
Integrated Targeting and Guidance for Powered Planetary Descent
Azimov, Dilmurat M.; Bishop, Robert H.
2018-02-01
This paper presents an on-board guidance and targeting design that enables explicit state and thrust vector control and on-board targeting for planetary descent and landing. These capabilities are developed utilizing a new closed-form solution for the constant thrust arc of the braking phase of the powered descent trajectory. The key elements of proven targeting and guidance architectures, including braking and approach phase quartics, are employed. It is demonstrated that implementation of the proposed solution avoids numerical simulation iterations, thereby facilitating on-board execution of targeting procedures during the descent. It is shown that the shape of the braking phase constant thrust arc is highly dependent on initial mass and propulsion system parameters. The analytic solution process is explicit in terms of targeting and guidance parameters, while remaining generic with respect to planetary body and descent trajectory design. These features increase the feasibility of extending the proposed integrated targeting and guidance design to future cargo and robotic landing missions.
Screening for homozygosity by descent in families with autosomal
Indian Academy of Sciences (India)
Home; Journals; Journal of Genetics; Volume 81; Issue 2 ... Perspectives Volume 81 Issue 2 August 2002 pp 59-63 ... disease locus in families with the recessive form of the disease, we used the approach of screening for homozygosity by descent in offspring of consanguineous and nonconsanguineous families with RP.
Neuromuscular function during stair descent in meniscectomized patients and controls
DEFF Research Database (Denmark)
Thorlund, Jonas Bloch; Roos, Ewa M; Aagaard, Per
2011-01-01
The aim of this study was to identify differences in knee range of motion (ROM), movement speed, ground reaction forces (GRF) profile, neuromuscular activity, and muscle coactivation during the transition between stair descent and level walking in meniscectomized patients at high risk of knee...
Steepest descent method for set-valued locally accretive mappings
International Nuclear Information System (INIS)
Chidume, C.E.
1993-05-01
Let E be a real q-uniformly smooth Banach space. Suppose T is a set-valued locally strongly accretive map with open domain D(T) in E and that 0 is an element of Tx has a solution x* in D(T). Then there exists a neighbourhood B in D(T) of x* and a real number r 1 >0 such that for any r>r 1 and some real sequence {c n }, any initial guess x 1 is an element of B and any single-valued selection T 0 of T, the sequence {x n } generated from x 1 by x n+1 =x n -c n T 0 x n , n≥1, remains in D(T) and converges strongly to x* with ||x n -x*|| O(n -(q-1)/ q). A related result deals with iterative approximation of a solution of the equation f is an element of x+Ax when A is a locally accretive map. Our theorems generalize important known results and resolve a problem of interest. (author). 39 refs
International Nuclear Information System (INIS)
Jamet, Didier; Torres, David; Brackbill, J.U.
2002-01-01
Errors in the computation of fluid flows with surface tension are examined. These errors cause large parasitic flows when the capillary number is large and have often been attributed to truncation error in underresolved interfacial regions. A study using the second-gradient method reveals that when truncation error is eliminated in the computation of energy exchanges between surface and kinetic energies so that energy is strictly conserved, the parasitic currents are reduced to round-off. The results are based on general thermodynamic arguments and can be used to guide improvements in other methods, such as the continuum-surface-force (CSF) method, which is commonly used with the volume-of-fluid (VOF) method
Jamet, D; Brackbill, J U
2002-01-01
Errors in the computation of fluid flows with surface tension are examined. These errors cause large parasitic flows when the capillary number is large and have often been attributed to truncation error in underresolved interfacial regions. A study using the second-gradient method reveals that when truncation error is eliminated in the computation of energy exchanges between surface and kinetic energies so that energy is strictly conserved, the parasitic currents are reduced to round-off. The results are based on general thermodynamic arguments and can be used to guide improvements in other methods, such as the continuum-surface-force (CSF) method, which is commonly used with the volume-of-fluid (VOF) method.
Zhang, Xia; Hu, Changqin
2017-09-08
Penicillins are typical of complex ionic samples which likely contain large number of degradation-related impurities (DRIs) with different polarities and charge properties. It is often a challenge to develop selective and robust high performance liquid chromatography (HPLC) methods for the efficient separation of all DRIs. In this study, an analytical quality by design (AQbD) approach was proposed for stability-indicating method development of cloxacillin. The structures, retention and UV characteristics rules of penicillins and their impurities were summarized and served as useful prior knowledge. Through quality risk assessment and screen design, 3 critical process parameters (CPPs) were defined, including 2 mixture variables (MVs) and 1 process variable (PV). A combined mixture-process variable (MPV) design was conducted to evaluate the 3 CPPs simultaneously and a response surface methodology (RSM) was used to achieve the optimal experiment parameters. A dual gradient elution was performed to change buffer pH, mobile-phase type and strength simultaneously. The design spaces (DSs) was evaluated using Monte Carlo simulation to give their possibility of meeting the specifications of CQAs. A Plackett-Burman design was performed to test the robustness around the working points and to decide the normal operating ranges (NORs). Finally, validation was performed following International Conference on Harmonisation (ICH) guidelines. To our knowledge, this is the first study of using MPV design and dual gradient elution to develop HPLC methods and improve separations for complex ionic samples. Copyright © 2017 Elsevier B.V. All rights reserved.
Dalmau Codina, Ramon; Prats Menéndez, Xavier
2017-01-01
Continuous descent operations with controlled times of arrival at one or several metering fixes could enable environmentally friendly procedures without compromising terminal airspace capacity. This paper focuses on controlled time of arrival updates once the descent has been already initiated, assessing the feasible time window (and associated fuel consumption) of continuous descent operations requiring neither thrust nor speed-brake usage along the whole descent (i.e. only elevator control ...
International Nuclear Information System (INIS)
Biffle, J.H.; Blanford, M.L.
1994-05-01
JAC2D is a two-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equations. The method is implemented in a two-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. A four-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic/plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere
International Nuclear Information System (INIS)
Biffle, J.H.
1993-02-01
JAC3D is a three-dimensional finite element program designed to solve quasi-static nonlinear mechanics problems. A set of continuum equations describes the nonlinear mechanics involving large rotation and strain. A nonlinear conjugate gradient method is used to solve the equation. The method is implemented in a three-dimensional setting with various methods for accelerating convergence. Sliding interface logic is also implemented. An eight-node Lagrangian uniform strain element is used with hourglass stiffness to control the zero-energy modes. This report documents the elastic and isothermal elastic-plastic material model. Other material models, documented elsewhere, are also available. The program is vectorized for efficient performance on Cray computers. Sample problems described are the bending of a thin beam, the rotation of a unit cube, and the pressurization and thermal loading of a hollow sphere
De Candia, T.r.; Lee, S.H.; Yang, J.; Browning, B.L.; Gejman, P. V.; Levinson, D. F.; Mowry, B. J.; Hewitt, J.K.; Goddard, M.E.; O'Donovan, M.C.; Purcell, S.M.; Posthuma, D.; Visscher, P. M.; Wray, N.R.; Keller, M. C.
2013-01-01
To investigate the extent to which the proportion of schizophrenia's additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control
Monitoring of internal pH gradients within multi-layer tablets by optical methods and EPR imaging.
Eisenächer, Friederike; Schädlich, Andreas; Mäder, Karsten
2011-09-30
The high variability of gastrointestinal pH is a general challenge regarding constant release from oral drug delivery systems, especially for ionisable drugs. These drugs often show a pH-dependent solubility and therewith associated intra- and inter-individual variability of emerging drug plasma levels. Several strategies have been investigated with the intention to influence the microenvironmental pH (pH(M)) within solid formulations and therefore achieve pH-independent release profiles. Because of the heterogeneity of solid systems, a precise prediction of the occurring pH(M) is rather difficult. It is therefore important to monitor the pH(M) within the formulations to achieve requested release as well as to minimise pH-dependent degradation processes of the active compound. The purpose of the current study was the analysis of pH(M) gradients within 2- and 3-layer tablets during hydration using 3 different techniques for comparison intensions, in particular a pH indicator dye, fluorescence imaging and EPR imaging. The influence of the presence or absence of pH modifying substances and of an additional lipophilic inter layer on the pH(M) was investigated as well as the variation of matrix forming excipient and buffer pH. The influence of the pH(M) on drug release was analysed as well. In addition, benchtop MRI was accomplished to gain a deeper insight on the hydration and erosion behaviour of 2- and 3-layer tablets. Copyright © 2010 Elsevier B.V. All rights reserved.
A unified framework of descent algorithms for nonlinear programs and variational inequalities
International Nuclear Information System (INIS)
Patriksson, M.
1993-01-01
We present a framework of algorithms for the solution of continuous optimization and variational inequality problems. In the general algorithm, a search direction finding auxiliary problems is obtained by replacing the original cost function with an approximating monotone cost function. The proposed framework encompasses algorithm classes presented earlier by Cohen, Dafermos, Migdalas, and Tseng, and includes numerous descent and successive approximation type methods, such as Newton methods, Jacobi and Gauss-Siedel type decomposition methods for problems defined over Cartesian product sets, and proximal point methods, among others. The auxiliary problem of the general algorithm also induces equivalent optimization reformulation and descent methods for asymmetric variational inequalities. We study the convergence properties of the general algorithm when applied to unconstrained optimization, nondifferentiable optimization, constrained differentiable optimization, and variational inequalities; the emphasis of the convergence analyses is placed on basic convergence results, convergence using different line search strategies and truncated subproblem solutions, and convergence rate results. This analysis offer a unification of known results; moreover, it provides strengthenings of convergence results for many existing algorithms, and indicates possible improvements of their realizations. 482 refs
Gaebler, John A.; Tolson, Robert H.
2010-01-01
In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.
International Nuclear Information System (INIS)
Potard, C.
1975-01-01
A new method was developed to study and control solidification processes by means of differential dilatometry. A mathematical analysis of this method is made and first results are presented. A relation is established between the variations of the volume of the sample and that of the solid obtained. The gravimetric method used for volume measurement is also mathematically analyzed. These results are applied to two solidification experiments on InSb, in strongly perturbed and controlled cooling regimes. Precisions are given on the limits of this method, and further developments towards phase transformation studies and control are envisaged [fr
International Nuclear Information System (INIS)
Yoon, Jong Seon; Choi, Hyoung Gwon; Jeon, Byoung Jin; Jung, Hye Dong
2016-01-01
A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.
Energy Technology Data Exchange (ETDEWEB)
Yoon, Jong Seon; Choi, Hyoung Gwon [Seoul Nat’l Univ. of Science and Technology, Seoul (Korea, Republic of); Jeon, Byoung Jin [Yonsei Univ., Seoul (Korea, Republic of); Jung, Hye Dong [Korea Electronics Technology Institute, Seongnam (Korea, Republic of)
2016-09-15
A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.
Gradient waveform synthesis for magnetic propulsion using MRI gradient coils
International Nuclear Information System (INIS)
Han, B H; Lee, S Y; Park, S
2008-01-01
Navigating an untethered micro device in a living subject is of great interest for both diagnostic and therapeutic applications. Magnetic propulsion of an untethered device carrying a magnetic core in it is one of the promising methods to navigate the device. MRI gradients coils are thought to be suitable for navigating the device since they are capable of magnetic propulsion in any direction while providing magnetic resonance images. For precise navigation of the device, especially in the peripheral region of the gradient coils, the concomitant gradient fields, as well as the linear gradient fields in the main magnetic field direction, should be considered in driving the gradient coils. For simple gradient coil configurations, the Maxwell coil in the z-direction and the Golay coil in the x- and y-directions, we have calculated the magnetic force fields, which are not necessarily the same as the conventional linear gradient fields of MRI. Using the calculated magnetic force fields, we have synthesized gradient waveforms to navigate the device along a desired path
Valko, Klara; Nunhuck, Shenaz; Bevan, Chris; Abraham, Michael H; Reynolds, Derek P
2003-11-01
A fast gradient HPLC method (cycle time 15 min) has been developed to determine Human Serum Albumin (HSA) binding of discovery compounds using chemically bonded protein stationary phases. The HSA binding values were derived from the gradient retention times that were converted to the logarithm of the equilibrium constants (logK HSA) using data from a calibration set of molecules. The method has been validated using literature plasma protein binding data of 68 known drug molecules. The method is fully automated, and has been used for lead optimization in more than 20 company projects. The HSA binding data obtained for more than 4000 compounds were suitable to set up global and project specific quantitative structure binding relationships that helped compound design in early drug discovery. The obtained HSA binding of known drug molecules were compared to the Immobilized Artificial Membrane binding data (CHI IAM) obtained by our previously described HPLC-based method. The solvation equation approach has been used to characterize the normal binding ability of HSA, and this relationship shows that compound lipophilicity is a significant factor. It was found that the selectivity of the "baseline" lipophilicity governing HSA binding, membrane interaction, and octanol/water partition are very similar. However, the effect of the presence of positive or negative charges have very different effects. It was found that negatively charged compounds bind more strongly to HSA than it would be expected from the lipophilicity of the ionized species at pH 7.4. Several compounds showed stronger HSA binding than can be expected from their lipophilicity alone, and comparison between predicted and experimental binding affinity allows the identification of compounds that have good complementarities with any of the known binding sites. Copyright 2003 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 92:2236-2248, 2003
Environmental effects on hormonal regulation of testicular descent
DEFF Research Database (Denmark)
Toppari, J; Virtanen, H E; Skakkebaek, N E
2006-01-01
cause some cases of undescended testis. Similarly, androgen insensitivity or androgen deficiency can cause cryptorchidism. Estrogens have been shown to down regulate INSL3 and thereby cause maldescent. Thus, a reduced androgen-estrogen ratio may disturb testicular descent. Environmental effects changing......Regulation of testicular descent is hormonally regulated, but the reasons for maldescent remain unknown in most cases. The main regulatory hormones are Leydig cell-derived testosterone and insulin-like factor 3 (INSL3). Luteinizing hormone (LH) stimulates the secretion of these hormones...... hypothesize that an exposure to a mixture of chemicals with anti-androgenic or estrogenic properties (either their own activity or their effect on androgen-estrogen ratio) may be involved in cryptorchidism....
Reversible cerebral vasoconstriction syndrome precipitated by airplane descent: Case report.
Hiraga, Akiyuki; Aotsuka, Yuya; Koide, Kyosuke; Kuwabara, Satoshi
2017-10-01
Background Reversible cerebral vasoconstriction syndrome (RCVS) is characterized by segmental vasospasm. Vasoactive agents and childbirth have been reported as precipitating factors for RCVS; however, RCVS induced by altitude change or air travel has rarely been reported. Case We present a case of a 74-year-old woman who presented with thunderclap headache during airplane descent. Magnetic resonance angiography demonstrated segmental vasoconstriction that improved 9 days after onset. Conclusion These findings indicate that airplane descent may be a trigger of RCVS. The time course of headache in the present case was similar to that of prolonged headache attributed to airplane travel, indicating that RCVS during air travel may have previously been overlooked and that some headache attributed to airplane travel cases may represent a milder form of RCVS.
RITD - Adapting Mars Entry, Descent and Landing System for Earth
Haukka, H.; Heilimo, J.; Harri, A.-M.; Aleksashkin, S.; Koryanov, V.; Arruego, I.; Schmidt, W.; Finchenko, V.; Martynov, M.; Ponomarenko, A.; Kazakovtsev, V.; Martin, S.
2015-10-01
We have developed an atmospheric re-entry and descent system concept based on inflatable hypersonic decelerator techniques that were originally developed for Mars. The ultimate goal of this EU-funded RITD-project (Re-entry: Inflatable Technology Development) was to assess the benefits of this technology when deploying small payloads from low Earth orbits to the surface of the Earth with modest costs. The principal goal was to assess and develop a preliminary EDLS design for the entire relevant range of aerodynamic regimes expected to be encountered in Earth's atmosphere during entry, descent and landing. Low Earth Orbit (LEO) and even Lunar applications envisaged include the use of the EDLS approach in returning payloads of 4-8 kg down to the surface.
Whole-body angular momentum during stair ascent and descent.
Silverman, Anne K; Neptune, Richard R; Sinitski, Emily H; Wilken, Jason M
2014-04-01
The generation of whole-body angular momentum is essential in many locomotor tasks and must be regulated in order to maintain dynamic balance. However, angular momentum has not been investigated during stair walking, which is an activity that presents a biomechanical challenge for balance-impaired populations. We investigated three-dimensional whole-body angular momentum during stair ascent and descent and compared it to level walking. Three-dimensional body-segment kinematic and ground reaction force (GRF) data were collected from 30 healthy subjects. Angular momentum was calculated using a 13-segment whole-body model. GRFs, external moment arms and net joint moments were used to interpret the angular momentum results. The range of frontal plane angular momentum was greater for stair ascent relative to level walking. In the transverse and sagittal planes, the range of angular momentum was smaller in stair ascent and descent relative to level walking. Significant differences were also found in the ground reaction forces, external moment arms and net joint moments. The sagittal plane angular momentum results suggest that individuals alter angular momentum to effectively counteract potential trips during stair ascent, and reduce the range of angular momentum to avoid falling forward during stair descent. Further, significant differences in joint moments suggest potential neuromuscular mechanisms that account for the differences in angular momentum between walking conditions. These results provide a baseline for comparison to impaired populations that have difficulty maintaining dynamic balance, particularly during stair ascent and descent. Copyright © 2014 Elsevier B.V. All rights reserved.
Additive preservers of the ascent, descent and related subsets
Czech Academy of Sciences Publication Activity Database
Mbekhta, M.; Müller, Vladimír; Oudghiri, M.
2014-01-01
Roč. 71, č. 1 (2014), s. 63-83 ISSN 0379-4024 R&D Projects: GA ČR GA201/09/0473; GA AV ČR IAA100190903 Institutional support: RVO:67985840 Keywords : additive preservers * ascent * descent Subject RIV: BA - General Mathematics Impact factor: 0.550, year: 2014 http://www.mathjournals.org/jot/2014-071-001/2014-071-001-004.html
Flight Management System Execution of Idle-Thrust Descents in Operations
Stell, Laurel L.
2011-01-01
To enable arriving aircraft to fly optimized descents computed by the flight management system (FMS) in congested airspace, ground automation must accurately predict descent trajectories. To support development of the trajectory predictor and its error models, commercial flights executed idle-thrust descents, and the recorded data includes the target speed profile and FMS intent trajectories. The FMS computes the intended descent path assuming idle thrust after top of descent (TOD), and any intervention by the controllers that alters the FMS execution of the descent is recorded so that such flights are discarded from the analysis. The horizontal flight path, cruise and meter fix altitudes, and actual TOD location are extracted from the radar data. Using more than 60 descents in Boeing 777 aircraft, the actual speeds are compared to the intended descent speed profile. In addition, three aspects of the accuracy of the FMS intent trajectory are analyzed: the meter fix crossing time, the TOD location, and the altitude at the meter fix. The actual TOD location is within 5 nmi of the intent location for over 95% of the descents. Roughly 90% of the time, the airspeed is within 0.01 of the target Mach number and within 10 KCAS of the target descent CAS, but the meter fix crossing time is only within 50 sec of the time computed by the FMS. Overall, the aircraft seem to be executing the descents as intended by the designers of the onboard automation.
Hazard avoidance via descent images for safe landing
Yan, Ruicheng; Cao, Zhiguo; Zhu, Lei; Fang, Zhiwen
2013-10-01
In planetary or lunar landing missions, hazard avoidance is critical for landing safety. Therefore, it is very important to correctly detect hazards and effectively find a safe landing area during the last stage of descent. In this paper, we propose a passive sensing based HDA (hazard detection and avoidance) approach via descent images to lower the landing risk. In hazard detection stage, a statistical probability model on the basis of the hazard similarity is adopted to evaluate the image and detect hazardous areas, so that a binary hazard image can be generated. Afterwards, a safety coefficient, which jointly utilized the proportion of hazards in the local region and the inside hazard distribution, is proposed to find potential regions with less hazards in the binary hazard image. By using the safety coefficient in a coarse-to-fine procedure and combining it with the local ISD (intensity standard deviation) measure, the safe landing area is determined. The algorithm is evaluated and verified with many simulated descent downward looking images rendered from lunar orbital satellite images.
Airborne Management of Traffic Conflicts in Descent With Arrival Constraints
Doble, Nathan A.; Barhydt, Richard; Krishnamurthy, Karthik
2005-01-01
NASA is studying far-term air traffic management concepts that may increase operational efficiency through a redistribution of decisionmaking authority among airborne and ground-based elements of the air transportation system. One component of this research, En Route Free Maneuvering, allows trained pilots of equipped autonomous aircraft to assume responsibility for traffic separation. Ground-based air traffic controllers would continue to separate traffic unequipped for autonomous operations and would issue flow management constraints to all aircraft. To evaluate En Route Free Maneuvering operations, a human-in-the-loop experiment was jointly conducted by the NASA Ames and Langley Research Centers. In this experiment, test subject pilots used desktop flight simulators to resolve conflicts in cruise and descent, and to adhere to air traffic flow constraints issued by test subject controllers. Simulators at NASA Langley were equipped with a prototype Autonomous Operations Planner (AOP) flight deck toolset to assist pilots with conflict management and constraint compliance tasks. Results from the experiment are presented, focusing specifically on operations during the initial descent into the terminal area. Airborne conflict resolution performance in descent, conformance to traffic flow management constraints, and the effects of conflicting traffic on constraint conformance are all presented. Subjective data from subject pilots are also presented, showing perceived levels of workload, safety, and acceptability of autonomous arrival operations. Finally, potential AOP functionality enhancements are discussed along with suggestions to improve arrival procedures.
Inflammatory bowel disease in children of middle eastern descent.
Naidoo, Christina Mai Ying; Leach, Steven T; Day, Andrew S; Lemberg, Daniel A
2014-01-01
Increasing rates of inflammatory bowel disease (IBD) are now seen in populations where it was once uncommon. The pattern of IBD in children of Middle Eastern descent in Australia has never been reported. This study aimed to investigate the burden of IBD in children of Middle Eastern descent at the Sydney Children's Hospital, Randwick (SCHR). The SCHR IBD database was used to identify patients of self-reported Middle Eastern ethnicity diagnosed between 1987 and 2011. Demographic, diagnosis, and management data was collected for all Middle Eastern children and an age and gender matched non-Middle Eastern IBD control group. Twenty-four patients of Middle Eastern descent were identified. Middle Eastern Crohn's disease patients had higher disease activity at diagnosis, higher use of thiopurines, and less restricted colonic disease than controls. Although there were limitations with this dataset, we estimated a higher prevalence of IBD in Middle Eastern children and they had a different disease phenotype and behavior compared to the control group, with less disease restricted to the colon and likely a more active disease course.
Testicular descent: INSL3, testosterone, genes and the intrauterine milieu.
Bay, Katrine; Main, Katharina M; Toppari, Jorma; Skakkebæk, Niels E
2011-04-01
Complete testicular descent is a sign of, and a prerequisite for, normal testicular function in adult life. The process of testis descent is dependent on gubernacular growth and reorganization, which is regulated by the Leydig cell hormones insulin-like peptide 3 (INSL3) and testosterone. Investigation of the role of INSL3 and its receptor, relaxin-family peptide receptor 2 (RXFP2), has contributed substantially to our understanding of the hormonal control of testicular descent. Cryptorchidism is a common congenital malformation, which is seen in 2-9% of newborn boys, and confers an increased risk of infertility and testicular cancer in adulthood. Although some cases of isolated cryptorchidism in humans can be ascribed to known genetic defects, such as mutations in INSL3 or RXFP2, the cause of cryptorchidism remains unknown in most patients. Several animal and human studies are currently underway to test the hypothesis that in utero factors, including environmental and maternal lifestyle factors, may be involved in the etiology of cryptorchidism. Overall, the etiology of isolated cryptorchidism seems to be complex and multifactorial, involving both genetic and nongenetic components.
Energy Technology Data Exchange (ETDEWEB)
Serai, Suraj D.; Fleck, Robert J. [Cincinnati Children' s Hospital Medical Center, Department of Radiology, MLC 5031, Cincinnati, OH (United States); Quinn, Charles T. [Cincinnati Children' s Hospital Medical Center, Division of Hematology, Cincinnati, OH (United States); Zhang, Bin [Cincinnati Children' s Hospital Medical Center, Division of Biostatistics and Epidemiology, Cincinnati, OH (United States); Podberesky, Daniel J. [Nemours Children' s Health System Nemours Children' s Hospital, Department of Radiology, Orlando, FL (United States)
2015-10-15
Serial surveillance of liver iron concentration (LIC) provides guidance for chelation therapy in patients with iron overload. The diagnosis of iron overload traditionally relies on core liver biopsy, which is limited by invasiveness, sampling error, cost and general poor acceptance by pediatric patients and parents. Thus noninvasive diagnostic methods such as MRI are highly attractive for quantification of liver iron concentration. To compare two MRI-based methods for liver iron quantification in children. 64 studies on 48 children and young adults (age range 4-21 years) were examined by gradient recalled echo (GRE) R2* and spin-echo R2 MRI at 1.5T to evaluate liver iron concentration. Scatter plots and Bland-Altman difference plots were generated to display and assess the relationship between the methods. With the protocols used in this investigation, Bland-Altman agreement between the methods is best when LIC is <20 mg/g dry tissue. Scatter plots show that all values with LIC <20 mg/g dry tissue fall within the 95% prediction limits. Liver iron concentration as determined by the R2* and R2 MR methods is statistically comparable, with no statistical difference between these methods for LIC <20 mg/g. (orig.)
NON–DESCENT VAGINAL HYSTERECTOMY FOR BENIGN GYNAECOLOGICAL DISEASE – A PROSPECTIVE STUDY
Directory of Open Access Journals (Sweden)
Thulasi
2016-04-01
Full Text Available OBJECTIVE To assess safety and feasibility of non-descent vaginal hysterectomy for benign gynaecological disease. METHODS A prospective study was conducted at the Department of Obstetrics and Gynaecology of P K Das Institute of Medical Sciences from January 2013 to December 2013. An effort was made to perform hysterectomies vaginally in women with benign or premalignant conditions in the absence of prolapse. A suspected adnexal pathology, endometriosis, immobility of uterus, uterus size more than 16 weeks was excluded from the study. Vaginal hysterectomy was done in usual manner. In bigger size uterus, morcellation techniques like bisection, debulking, coring, myomectomy, or combination of these were used to remove the uterus. Data regarding age, parity, uterine size, estimated blood loss, length of operation, intraoperative and postoperative complications and hospital stay were recorded. RESULTS A total of 100 cases were selected for non-descent vaginal hysterectomy. Among them, 97 cases successfully underwent nondescent vaginal hysterectomy. Majority of the patients (55% were in age group 40-45 yrs. Four patients were nulligravida and eight patients had previous LSCS. Uterine size was ≤ 12 weeks in 84 cases and > 12-16 weeks in 16 cases. Commonest indication was leiomyoma of uterus (43%. Mean duration of surgery was 70±20.5 minutes. Mean blood loss was 150±65 mL. Reasons for failure to perform NDVH was difficulty in opening pouch of Douglas in two cases because of adhesions and in one case there was difficulty in reaching the fundal myoma which prevented the uterine descent. Intra–operatively, one case had bladder injury (1% that had previous 2 LSCS. Postoperatively, complications were minimal which included postoperative fever (11%, UTI (8% and vaginal cuff infection was (4%. Mean hospital stay was 3.5 days. CONCLUSION Vaginal hysterectomy is safe, feasible in most of the women requiring hysterectomy for benign conditions with less
Deep kernel learning method for SAR image target recognition
Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao
2017-10-01
With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.
Heier, W. C. (Inventor)
1974-01-01
A method is described for compression molding of thermosetting plastics composition. Heat is applied to the compressed load in a mold cavity and adjusted to hold molding temperature at the interface of the cavity surface and the compressed compound to produce a thermal front. This thermal front advances into the evacuated compound at mean right angles to the compression load and toward a thermal fence formed at the opposite surface of the compressed compound.
Najar, Mehdi; Rodrigues, Robim M; Buyl, Karolien; Branson, Steven; Vanhaecke, Tamara; Lagneaux, Laurence; Rogiers, Vera; De Kock, Joery
2014-09-01
Adult human subcutaneous adipose tissue harbors a multipotent stem cell population, the so-called human adipose tissue-derived mesenchymal stromal cells (AT-MSCs). These cells are able to differentiate in vitro into various cell types and possess immunomodulatory features. Yet procedures to obtain AT-MSCs can vary significantly. The two most extensively used AT-MSC purification techniques are (i) density gradient centrifugation using Ficoll and (ii) red blood cell (RBC) lysis buffer treatment of the stromal vascular fraction. In the context of potential clinical cell therapy, the stem cell yield after purification and upon consecutive passages, as well as the purity of the obtained cell population, are of utmost importance. We investigated the expansion capacity and purity of AT-MSCs purified by both procedures immediately after isolation and upon consecutive passages. We also investigated possible purification-dependent differences in their expression of immune-inhibitory factors and cell adhesion molecules. We found that RBC lysis buffer treatment is a more robust and easier method to purify AT-MSCs than density gradient fractionation. However, the resulting AT-MSC-RBC population contains a significantly higher number of CD34(+) cells, particularly during the first passages after plating. From passage 4 onward, no significant differences could be observed between both populations with respect to the immunophenotype, expansion capacity and expression of immune inhibitory factors and cell adhesion molecules. Our data show that RBC lysis buffer treatment may be a good alternative to density fractionation, providing a faster, more robust and easier method to purify AT-MSCs with biologically preserved characteristics. Copyright © 2014 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Wei-hui Liu
Full Text Available BACKGROUND: Because few definitive markers are available for hepatic cancer stem cells (HCSCs, based on physical rather than immunochemical properties, we applied a novel method to enrich HCSCs. METHODOLOGY: After hepatic tumor cells (HTCs were first isolated from diethylinitrosamine-induced F344 rat HCC model using percoll discontinuous gradient centrifugation (PDGC and purified via differential trypsinization and differential attachment (DTDA, they were separated into four fractions using percoll continuous gradient centrifugation (PCGC and sequentially designated as fractions I-IV (FI-IV. Morphological characteristics, mRNA and protein levels of stem cell markers, proliferative abilities, induced differentiation, in vitro migratory capacities, in vitro chemo-resistant capacities, and in vivo malignant capacities were determined for the cells of each fraction. FINDINGS: As the density of cells increased, 22.18%, 11.62%, 4.73% and 61.47% of primary cultured HTCs were segregated in FI-FIV, respectively. The cells from FIII (density between 1.041 and 1.062 g/ml displayed a higher nuclear-cytoplasmic ratio and fewer organelles and expressed higher levels of stem cell markers (AFP, EpCAM and CD133 than cells from other fractions (P<0.01. Additionally, in vitro, the cells from FIII showed a greater capacity to self-renew, differentiate into mature HTCs, transit across membranes, close scratches, and carry resistance to chemotherapy than did cells from any other fraction; in vivo, injection of only 1×10(4 cells from FIII could generate tumors not only in subcutaneous tissue but also in the livers of nude mice. CONCLUSIONS: Through our novel method, HCSC-like cells were successfully enriched in FIII. This study will greatly contribute to two important areas of biological interest: CSC isolation and HCC therapy.
Dictionary Learning Based on Nonnegative Matrix Factorization Using Parallel Coordinate Descent
Directory of Open Access Journals (Sweden)
Zunyi Tang
2013-01-01
Full Text Available Sparse representation of signals via an overcomplete dictionary has recently received much attention as it has produced promising results in various applications. Since the nonnegativities of the signals and the dictionary are required in some applications, for example, multispectral data analysis, the conventional dictionary learning methods imposed simply with nonnegativity may become inapplicable. In this paper, we propose a novel method for learning a nonnegative, overcomplete dictionary for such a case. This is accomplished by posing the sparse representation of nonnegative signals as a problem of nonnegative matrix factorization (NMF with a sparsity constraint. By employing the coordinate descent strategy for optimization and extending it to multivariable case for processing in parallel, we develop a so-called parallel coordinate descent dictionary learning (PCDDL algorithm, which is structured by iteratively solving the two optimal problems, the learning process of the dictionary and the estimating process of the coefficients for constructing the signals. Numerical experiments demonstrate that the proposed algorithm performs better than the conventional nonnegative K-SVD (NN-KSVD algorithm and several other algorithms for comparison. What is more, its computational consumption is remarkably lower than that of the compared algorithms.
Directory of Open Access Journals (Sweden)
Lanfa Liu
2017-12-01
Full Text Available Soil spectroscopy has experienced a tremendous increase in soil property characterisation, and can be used not only in the laboratory but also from the space (imaging spectroscopy. Partial least squares (PLS regression is one of the most common approaches for the calibration of soil properties using soil spectra. Besides functioning as a calibration method, PLS can also be used as a dimension reduction tool, which has scarcely been studied in soil spectroscopy. PLS components retained from high-dimensional spectral data can further be explored with the gradient-boosted decision tree (GBDT method. Three soil sample categories were extracted from the Land Use/Land Cover Area Frame Survey (LUCAS soil library according to the type of land cover (woodland, grassland, and cropland. First, PLS regression and GBDT were separately applied to build the spectroscopic models for soil organic carbon (OC, total nitrogen content (N, and clay for each soil category. Then, PLS-derived components were used as input variables for the GBDT model. The results demonstrate that the combined PLS-GBDT approach has better performance than PLS or GBDT alone. The relative important variables for soil property estimation revealed by the proposed method demonstrated that the PLS method is a useful dimension reduction tool for soil spectra to retain target-related information.
M'Garrech, S
2002-01-01
Within the framework of the ALTO project (Linear Accelerator near the Orsay Tandem), IPNO will recover the LAL station NEPAL, which will be used as the ALTO injecting system. To calculate the beam optics through the linear accelerator, it is necessary to determine the electron beam emittance at the exit of the buncher station. There are several methods to determine this emittance: direct methods, like the Pepper Pot technique, and indirect ones, like the three distances method and the three gradients one. The latter requires a variable optic element (quadrupole, solenoid...). In the case of the use of a solenoid, the horizontal and vertical motions are coupled, which implies an additional difficulty for the analysis of the measurements. The main goal of this report is to identify and to solve these mathematical difficulties, so as to determine at last the initial emittance. The treated example comes from a paper by R.Chehab et al [12], the code used is BETA, and resolution is done using the last square method...
International Nuclear Information System (INIS)
Gelebart, Lionel; Mondon-Cancel, Romain
2013-01-01
FFT-based methods are used to solve the problem of a heterogeneous unit-cell submitted to periodic boundary conditions, which is of a great interest in the context of numerical homogenization. Recently (in 2010), Brisard and Zeman proposed simultaneously to use Conjugate Gradient based solvers in order to improve the convergence properties (when compared to the basic scheme, proposed initially in 1994). The purpose of the paper is to extend this idea to the case of non-linear behaviors. The proposed method is based on a Newton-Raphson algorithm and can be applied to various kinds of behaviors (time dependant or independent, with or without internal variables) through a conventional integration procedure as used in finite element codes. It must be pointed out that this approach is fundamentally different from the traditional FFT-based approaches which rely on a fixed-point algorithm (e.g. basic scheme, Eyre and Milton accelerated scheme, Augmented Lagrangian scheme, etc.). The method is compared to the basic scheme on the basis of a simple application (a linear elastic spherical inclusion within a non-linear elastic matrix): a low sensitivity to the reference material and an improved efficiency, for a soft or a stiff inclusion, are observed. At first proposed for a prescribed macroscopic strain, the method is then extended to mixed loadings. (authors)
Acosta, Eva; Vazquez, Daniel; Garner, Leon; Smith, George
2005-03-01
We present an iterative tomographic algorithm to reconstruct refractive-index profiles for meridional planes of the lens of the spherical fish eye from measurements of deflection angles of refracted rays. Numerical simulations show that the algorithm allows accuracy up to the fourth decimal place, provided that the refractive index can be regarded as an analytical function of the radial coordinate and the experimental errors are neglected. An experimental demonstration is given by applying the algorithm to retrieve the refractive-index profile of a spherical fish lens. The method is conceptually simple and does not require matching of the index of the surrounding medium to that of the surface of the lens, and the related iterative algorithm rapidly converges.
Lubczynski, Maciek W; Chavarro-Rincon, Diana; Roy, Jean
2012-07-01
Natural temperature gradient (NTG) can be a significant problem in thermal sap flow measurements, particularly in dry environments with sparse vegetation. To resolve this problem, we propose a novel correction method called cyclic heat dissipation (CHD) in its thermal dissipation probe (TDP) application. The CHD method is based on cyclic, switching ON/OFF power schema measurements and a three-exponential model, extrapolating measured signal to steady state thermal equilibrium. The extrapolated signal OFF represents NTG, whereas the extrapolated signal ON represents standard TDP signal, biased by NTG. Therefore, subtraction of the OFF signal from the ON signal allows defining the unbiased TDP signal, finally processed according to standard Granier calibration. The in vivo Kalahari measurements were carried out in three steps on four different tree species, first as NTG, then as standard TDP and finally in CHD mode, each step for ∼1-2 days. Afterwards, each tree was separated from its stem following modified Roberts' (1977) procedure, and CHD verification was applied. The typical NTG varying from ∼0.5 °C during night-time to -1 °C during day-time, after CHD correction, resulted in significant reduction of sap flux densities (J(p)) as compared with the standard TDP, particularly distinct for low J(p). The verification of the CHD method indicated ∼20% agreement with the reference method, largely dependent on the sapwood area estimate. The proposed CHD method offers the following advantages: (i) in contrast to any other NTG correction method, it removes NTG bias from the measured signal by using in situ, extrapolated to thermal equilibrium signal; (ii) it does not need any specific calibration making use of the standard Granier calibration; (iii) it provides a physical background to the proposed NTG correction; (iv) it allows for power savings; (v) it is not tied to TDP, and so can be adapted to other thermal methods. In its current state, the CHD data
Ly, Uy-Loi; Schoemig, Ewald
1993-01-01
In the past few years, the mixed H(sub 2)/H-infinity control problem has been the object of much research interest since it allows the incorporation of robust stability into the LQG framework. The general mixed H(sub 2)/H-infinity design problem has yet to be solved analytically. Numerous schemes have considered upper bounds for the H(sub 2)-performance criterion and/or imposed restrictive constraints on the class of systems under investigation. Furthermore, many modern control applications rely on dynamic models obtained from finite-element analysis and thus involve high-order plant models. Hence the capability to design low-order (fixed-order) controllers is of great importance. In this research a new design method was developed that optimizes the exact H(sub 2)-norm of a certain subsystem subject to robust stability in terms of H-infinity constraints and a minimal number of system assumptions. The derived algorithm is based on a differentiable scalar time-domain penalty function to represent the H-infinity constraints in the overall optimization. The scheme is capable of handling multiple plant conditions and hence multiple performance criteria and H-infinity constraints and incorporates additional constraints such as fixed-order and/or fixed structure controllers. The defined penalty function is applicable to any constraint that is expressible in form of a real symmetric matrix-inequity.
Predictive Modeling for NASA Entry, Descent and Landing Missions
Wright, Michael
2016-01-01
Entry, Descent and Landing (EDL) Modeling and Simulation (MS) is an enabling capability for complex NASA entry missions such as MSL and Orion. MS is used in every mission phase to define mission concepts, select appropriate architectures, design EDL systems, quantify margin and risk, ensure correct system operation, and analyze data returned from the entry. In an environment where it is impossible to fully test EDL concepts on the ground prior to use, accurate MS capability is required to extrapolate ground test results to expected flight performance.
A different approach to estimate nonlinear regression model using numerical methods
Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.
2017-11-01
This research paper concerns with the computational methods namely the Gauss-Newton method, Gradient algorithm methods (Newton-Raphson method, Steepest Descent or Steepest Ascent algorithm method, the Method of Scoring, the Method of Quadratic Hill-Climbing) based on numerical analysis to estimate parameters of nonlinear regression model in a very different way. Principles of matrix calculus have been used to discuss the Gradient-Algorithm methods. Yonathan Bard [1] discussed a comparison of gradient methods for the solution of nonlinear parameter estimation problems. However this article discusses an analytical approach to the gradient algorithm methods in a different way. This paper describes a new iterative technique namely Gauss-Newton method which differs from the iterative technique proposed by Gorden K. Smyth [2]. Hans Georg Bock et.al [10] proposed numerical methods for parameter estimation in DAE’s (Differential algebraic equation). Isabel Reis Dos Santos et al [11], Introduced weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel. For large-scale non smooth convex minimization the Hager and Zhang (HZ) conjugate gradient Method and the modified HZ (MHZ) method were presented by Gonglin Yuan et al [12].
Diviš, Pavel; Kadlecová, Milada; Ouddane, Baghdad
2016-05-01
The distribution of mercury in surface water and in sediment from Deûle River in Northern France was studied by application of conventional sampling methods and by diffusive gradients in thin films technique (DGT). Concentration of total dissolved mercury in surface water was 20.8 ± 0.8 ng l(-1). The particulate mercury concentration was 6.2 ± 0.6 µg g(-1). The particulate mercury was accumulated in sediment (9.9 ± 2.3 mg kg(-1)), and it was transformed by methylating bacteria to methylmercury, mainly in the first 2-cm layer of the sediment. Total dissolved concentration of mercury in sediment pore water obtained by application of centrifugation extraction was 17.6 ± 4.1 ng l(-1), and it was comparable with total dissolved pore water mercury concentration measured by DGT probe containing Duolite GT-73 resin gel (18.2 ± 4.3 ng l(-1)), taking the sediment heterogeneity and different principles of the applied methods into account. By application of two DGT probes with different resin gels specific for mercury, it was found that approximately 30% of total dissolved mercury in sediment pore water was present in labile forms easy available for biota. The resolution of mercury DGT depth profiles was 0.5 cm, which allows, unlike conventional techniques, to study the connection of the geochemical cycle of mercury with geochemical cycles of iron and manganese.
Directory of Open Access Journals (Sweden)
Sahbi Marrouchi
2014-01-01
Full Text Available Due to the continuous increase of the population and the perpetual progress of industry, the energy management presents nowadays a relevant topic that concerns researchers in electrical engineering. Indeed, in order to establish a good exploitation of the electrical grid, it is necessary to solve technical and economic problems. This can only be done through the resolution of the Unit Commitment Problem. Unit Commitment Problem allows optimizing the combination of the production units’ states and determining their production planning, in order to satisfy the expected consumption with minimal cost during a specified period which varies usually from 24 hours to one week. However, each production unit has some constraints that make this problem complex, combinatorial, and nonlinear. This paper presents a comparative study between a strategy based on hybrid gradient-genetic algorithm method and two strategies based on metaheuristic methods, fuzzy logic, and genetic algorithm, in order to predict the combinations and the unit commitment scheduling of each production unit in one side and to minimize the total production cost in the other side. To test the performance of the optimization proposed strategies, strategies have been applied to the IEEE electrical network 14 busses and the obtained results are very promising.
International Nuclear Information System (INIS)
Lindinger, C.; Jordan, A.; Karl, T.; Guenther, A.; Tschiersch, J.; Ruckerbauer, F.; Paretzke, H.
2002-01-01
PTR-MS technique was used to measure fluxes of various VOC's including oxygenates using surface layer gradient method. The VOC concentrations and temperature were measured at heights of about 0.5 m and 3.9 m above ground at field site in St. Johann in Tirol during and after grass cutting (24th and 25th of May 2000) in order to calculate fluxes. The sensible heat flux was obtained by a sonic anemometer with turbulence data analyzer. The major crop in this part of Austria are perennial grasses used for livestock farming. We observed VOC emission fluxes including methanol and acetaldehyde as the major volatile, C 5 and C 6 leaf wound compounds with lesser amounts and traces of acetone and butanone. This composition of VOC's is very similar to that released from slashed pasture grass. At the same time, VOC fluxes were measured with PTR-MS and eddy covariance method. Comparing the flux data of methanol and acetaldehyde of both days have shown very similar results. (author)
Spatial gradient tuning in metamaterials
Driscoll, Tom; Goldflam, Michael; Jokerst, Nan; Basov, Dimitri; Smith, David
2011-03-01
Gradient Index (GRIN) metamaterials have been used to create devices inspired by, but often surpassing the potential of, conventional GRIN optics. The unit-cell nature of metamaterials presents the opportunity to exert much greater control over spatial gradients than is possible in natural materials. This is true not only during the design phase but also offers the potential for real-time reconfiguration of the metamaterial gradient. This ability fits nicely into the picture of transformation-optics, in which spatial gradients can enable an impressive suite of innovative devices. We discuss methods to exert control over metamaterial response, focusing on our recent demonstrations using Vanadium Dioxide. We give special attention to role of memristance and mem-capacitance observed in Vanadium Dioxide, which simplify the demands of stimuli and addressing, as well as intersecting metamaterials with the field of memory-materials.
Crosswind Shear Gradient Affect on Wake Vortices
Proctor, Fred H.; Ahmad, Nashat N.
2011-01-01
Parametric simulations with a Large Eddy Simulation (LES) model are used to explore the influence of crosswind shear on aircraft wake vortices. Previous studies based on field measurements, laboratory experiments, as well as LES, have shown that the vertical gradient of crosswind shear, i.e. the second vertical derivative of the environmental crosswind, can influence wake vortex transport. The presence of nonlinear vertical shear of the crosswind velocity can reduce the descent rate, causing a wake vortex pair to tilt and change in its lateral separation. The LES parametric studies confirm that the vertical gradient of crosswind shear does influence vortex trajectories. The parametric results also show that vortex decay from the effects of shear are complex since the crosswind shear, along with the vertical gradient of crosswind shear, can affect whether the lateral separation between wake vortices is increased or decreased. If the separation is decreased, the vortex linking time is decreased, and a more rapid decay of wake vortex circulation occurs. If the separation is increased, the time to link is increased, and at least one of the vortices of the vortex pair may have a longer life time than in the case without shear. In some cases, the wake vortices may never link.
Sagagd method for the beam shaping of uniform illumination
International Nuclear Information System (INIS)
Li Yongping; Chen Dewei; Wang Wei
2002-01-01
The simulated annealing algorithm, the genetic and the gradient descent algorithm are retrospectively and successfully amalgamated to optimal design of pure phase element for uniform beams. The process of this method is divided into three steps, first the energy enhancement of the main lobe, then the process to make the top of the main lobe to be smooth and the fringe to be steep, at last the full optimization beam. After these three steps of optimization, the beam is good enough to be applied to ICF
Lambert, M.; Lesselier, D.; Kooij, B. J.
1998-10-01
The retrieval of an unknown, possibly inhomogeneous, penetrable cylindrical obstacle buried entirely in a known homogeneous half-space - the constitutive material parameters of the obstacle and of its embedding obey a Maxwell model - is considered from single- or multiple-frequency aspect-limited data collected by ideal sensors located in air above the embedding half-space, when a small number of time-harmonic transverse electric (TE)-polarized line sources - the magnetic field H is directed along the axis of the cylinder - is also placed in air. The wavefield is modelled from a rigorous H-field domain integral-differential formulation which involves the dot product of the gradients of the single component of H and of the Green function of the stratified environment times a scalar-valued contrast function which contains the obstacle parameters (the frequency-independent, position-dependent relative permittivity and conductivity). A modified gradient method is developed in order to reconstruct the maps of such parameters within a prescribed search domain from the iterative minimization of a cost functional which incorporates both the error in reproducing the data and the error on the field built inside this domain. Non-physical values are excluded and convergence reached by incorporating in the solution algorithm, from a proper choice of unknowns, the condition that the relative permittivity be larger than or equal to 1, and the conductivity be non-negative. The efficiency of the constrained method is illustrated from noiseless and noisy synthetic data acquired independently. The importance of the choice of the initial values of the sought quantities, the need for a periodic refreshment of the constitutive parameters to avoid the algorithm providing inconsistent results, and the interest of a frequency-hopping strategy to obtain finer and finer features of the obstacle when the frequency is raised, are underlined. It is also shown that though either the permittivity
Arachnid aloft: directed aerial descent in neotropical canopy spiders.
Yanoviak, Stephen P; Munk, Yonatan; Dudley, Robert
2015-09-06
The behaviour of directed aerial descent has been described for numerous taxa of wingless hexapods as they fall from the tropical rainforest canopy, but is not known in other terrestrial arthropods. Here, we describe similar controlled aerial behaviours for large arboreal spiders in the genus Selenops (Selenopidae). We dropped 59 such spiders from either canopy platforms or tree crowns in Panama and Peru; the majority (93%) directed their aerial trajectories towards and then landed upon nearby tree trunks. Following initial dorsoventral righting when necessary, falling spiders oriented themselves and then translated head-first towards targets; directional changes were correlated with bilaterally asymmetric motions of the anterolaterally extended forelegs. Aerial performance (i.e. the glide index) decreased with increasing body mass and wing loading, but not with projected surface area of the spider. Along with the occurrence of directed aerial descent in ants, jumping bristletails, and other wingless hexapods, this discovery of targeted gliding in selenopid spiders further indicates strong selective pressures against uncontrolled falls into the understory for arboreal taxa. © 2015 The Author(s).
Combining Step Gradients and Linear Gradients in Density.
Kumar, Ashok A; Walz, Jenna A; Gonidec, Mathieu; Mace, Charles R; Whitesides, George M
2015-06-16
Combining aqueous multiphase systems (AMPS) and magnetic levitation (MagLev) provides a method to produce hybrid gradients in apparent density. AMPS—solutions of different polymers, salts, or surfactants that spontaneously separate into immiscible but predominantly aqueous phases—offer thermodynamically stable steps in density that can be tuned by the concentration of solutes. MagLev—the levitation of diamagnetic objects in a paramagnetic fluid within a magnetic field gradient—can be arranged to provide a near-linear gradient in effective density where the height of a levitating object above the surface of the magnet corresponds to its density; the strength of the gradient in effective density can be tuned by the choice of paramagnetic salt and its concentrations and by the strength and gradient in the magnetic field. Including paramagnetic salts (e.g., MnSO4 or MnCl2) in AMPS, and placing them in a magnetic field gradient, enables their use as media for MagLev. The potential to create large steps in density with AMPS allows separations of objects across a range of densities. The gradients produced by MagLev provide resolution over a continuous range of densities. By combining these approaches, mixtures of objects with large differences in density can be separated and analyzed simultaneously. Using MagLev to add an effective gradient in density also enables tuning the range of densities captured at an interface of an AMPS by simply changing the position of the container in the magnetic field. Further, by creating AMPS in which phases have different concentrations of paramagnetic ions, the phases can provide different resolutions in density. These results suggest that combining steps in density with gradients in density can enable new classes of separations based on density.
Natural selection and the distribution of identity-by-descent in the human genome
DEFF Research Database (Denmark)
Albrechtsen, Anders; Moltke, Ida; Nielsen, Rasmus
2010-01-01
There has recently been considerable interest in detecting natural selection in the human genome. Selection will usually tend to increase identity-by-descent (IBD) among individuals in a population, and many methods for detecting recent and ongoing positive selection indirectly take advantage...... of this. In this article we show that excess IBD sharing is a general property of natural selection and we show that this fact makes it possible to detect several types of selection including a type that is otherwise difficult to detect: selection acting on standing genetic variation. Motivated by this......, we use a recently developed method for identifying IBD sharing among individuals from genome-wide data to scan populations from the new HapMap phase 3 project for regions with excess IBD sharing in order to identify regions in the human genome that have been under strong, very recent selection...
Degni, F; Koivusilta, L; Ojanlatva, A
2006-09-01
To assess attitudes towards and perceptions about contraceptive use among married refugee women of Somali descent living in Finland. A sample of 100 married refugee women of Somali descent (18-50 years of age) were invited to participate in a study on contraceptive use in Finland (30 women refused). Qualitative and quantitative methods were used to collect the data. Questionnaire of the first data set was written in the Somali language. Interviews were conducted in the Somali language. The attitudes and opinions of these women towards contraceptive use (73% did not use contraceptives, 27% did use them) were connected with religious beliefs and issues involving marital relations. Religious or gender issues did not seem to influence those who used contraception. The findings indicated that the majority of the married refugee women of Somali descent living in Finland did not use contraception. The process of starting the use of contraception was possible because of an access to good reproductive health care and family planning services, changes in life situations, and adaptations to Finnish social and cultural norms.
Directory of Open Access Journals (Sweden)
Rosa Sayoko Kawasaki-Oyama
2008-03-01
Ficoll-Paque gradient density method (d=1.077g/ml. METHODS: Ten samples of the umbilical cord blood obtained from full-term deliveries were submitted to two different procedures of mesenchymal stem cell culture: a Method without the Ficoll-Paque density gradient, which concentrates all nucleated cells; b Method with the Ficoll-Paque density gradient, which selects only low-density mononuclear cells. Cells were initially plated into 25 cm² cultures flasks at a density of 1x10(7 nucleated cells/cm² and 1x10(6 mononuclear cells/cm². RESULTS: It was obtained 2-13x10(7 (median = 2.35x10(7 nucleated cells/cm² by the method without the Ficoll-Paque gradient density, and 3.7-15.7x10(6 (median = 7.2x10(6 mononuclear cells/cm² by the method with the Ficoll-Paque gradient density. In all cultures adherent cells were observed 24 hours after being cultured. Cells presented fibroblastoid and epithelioid morphology. In most of the cultures, cell proliferation occurred in the first week, but after the second week only some cultures - derived from the method without the Ficoll-Paque gradient density - maintained the growth rate reaching confluence. Those cultures were submitted to trypsinization with 0.25% trypsin/EDTA solution and cultured for two to three months. CONCLUSION: In the samples analyzed, cell separation and mesenchymal stem cell culture techniques from human umbilical cord blood by the method without the Ficoll-Paque density gradient was more efficient than the method with the Ficoll-Paque density gradient.
Marko Gómez-Hernández; Guadalupe Williams-Linera; Roger Guevara; D. Jean Lodge
2012-01-01
Gradient analysis is rarely used in studies of fungal communities. Data on macromycetes from eight sites along an elevation gradient in central Veracruz, Mexico, were used to demonstrate methods for gradient analysis that can be applied to studies of communities of fungi. Selected sites from 100 to 3,500 m altitude represent tropical dry forest, tropical montane cloud...
Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José; Liu, Qinya; Zhou, Bing
2017-05-01
We carry out full waveform inversion (FWI) in time domain based on an alternative frequency-band selection strategy that allows us to implement the method with success. This strategy aims at decomposing the seismic data within partially overlapped frequency intervals by carrying out a concatenated treatment of the wavelet to largely avoid redundant frequency information to adapt to wavelength or wavenumber coverage. A pertinent numerical test proves the effectiveness of this strategy. Based on this strategy, we comparatively analyze the effects of update parameters for the nonlinear conjugate gradient (CG) method and step-length formulas on the multiscale FWI through several numerical tests. The investigations of up to eight versions of the nonlinear CG method with and without Gaussian white noise make clear that the HS (Hestenes and Stiefel in J Res Natl Bur Stand Sect 5:409-436, 1952), CD (Fletcher in Practical methods of optimization vol. 1: unconstrained optimization, Wiley, New York, 1987), and PRP (Polak and Ribière in Revue Francaise Informat Recherche Opertionelle, 3e Année 16:35-43, 1969; Polyak in USSR Comput Math Math Phys 9:94-112, 1969) versions are more efficient among the eight versions, while the DY (Dai and Yuan in SIAM J Optim 10:177-182, 1999) version always yields inaccurate result, because it overestimates the deeper parts of the model. The application of FWI algorithms using distinct step-length formulas, such as the direct method ( Direct), the parabolic search method ( Search), and the two-point quadratic interpolation method ( Interp), proves that the Interp is more efficient for noise-free data, while the Direct is more efficient for Gaussian white noise data. In contrast, the Search is less efficient because of its slow convergence. In general, the three step-length formulas are robust or partly insensitive to Gaussian white noise and the complexity of the model. When the initial velocity model deviates far from the real model or the