Towards Stable Adversarial Feature Learning for LiDAR based Loop Closure Detection

OpenAIRE

Xu, Lingyun; Yin, Peng; Luo, Haibo; Liu, Yunhui; Han, Jianda

2017-01-01

Stable feature extraction is the key for the Loop closure detection (LCD) task in the simultaneously localization and mapping (SLAM) framework. In our paper, the feature extraction is operated by using a generative adversarial networks (GANs) based unsupervised learning. GANs are powerful generative models, however, GANs based adversarial learning suffers from training instability. We find that the data-code joint distribution in the adversarial learning is a more complex manifold than in the...

"Accelerated Perceptron": A Self-Learning Linear Decision Algorithm

OpenAIRE

Zuev, Yu. A.

2003-01-01

The class of linear decision rules is studied. A new algorithm for weight correction, called an "accelerated perceptron", is proposed. In contrast to classical Rosenblatt's perceptron this algorithm modifies the weight vector at each step. The algorithm may be employed both in learning and in self-learning modes. The theoretical aspects of the behaviour of the algorithm are studied when the algorithm is used for the purpose of increasing the decision reliability by means of weighted voting. I...

Linearly decoupled energy-stable numerical methods for multi-component two-phase compressible flow

KAUST Repository

Kou, Jisheng

2017-12-06

In this paper, for the first time we propose two linear, decoupled, energy-stable numerical schemes for multi-component two-phase compressible flow with a realistic equation of state (e.g. Peng-Robinson equation of state). The methods are constructed based on the scalar auxiliary variable (SAV) approaches for Helmholtz free energy and the intermediate velocities that are designed to decouple the tight relationship between velocity and molar densities. The intermediate velocities are also involved in the discrete momentum equation to ensure a consistency relationship with the mass balance equations. Moreover, we propose a component-wise SAV approach for a multi-component fluid, which requires solving a sequence of linear, separate mass balance equations. We prove that the methods have the unconditional energy-dissipation feature. Numerical results are presented to verify the effectiveness of the proposed methods.

Stable particle motion in a linear accelerator with solenoid focusing

International Nuclear Information System (INIS)

Wadlinger, E.A.

1979-01-01

The equation governing stable particle motion in a linear ion accelerator containing discrete rf and either discrete or continuous solenoid focusing was derived. It was found for discrete solenoid focusing that: cos μ = (1 + dΔ) cos theta/2 + (lΔ/theta - dtheta/2l - thetaΔd 2 /4l) sin theta/2, Δ = 1/f and l + 2d = βlambda, where μ, theta, f, l, and d are the phase advance per cell, precession angle in the solenoid, focal length of the rf lens, length of the solenoid in one cell, and the drift distance between the center of the rf gap and the effective edge of the solenoid. The relation for a continuous solenoid is found by setting d equal to zero. The boundaries of the stability region for theta vs Δ with fixed l and d are obtained when cos μ =+-1

Active learning for semi-supervised clustering based on locally linear propagation reconstruction.

Science.gov (United States)

Chang, Chin-Chun; Lin, Po-Yi

2015-03-01

The success of semi-supervised clustering relies on the effectiveness of side information. To get effective side information, a new active learner learning pairwise constraints known as must-link and cannot-link constraints is proposed in this paper. Three novel techniques are developed for learning effective pairwise constraints. The first technique is used to identify samples less important to cluster structures. This technique makes use of a kernel version of locally linear embedding for manifold learning. Samples neither important to locally linear propagation reconstructions of other samples nor on flat patches in the learned manifold are regarded as unimportant samples. The second is a novel criterion for query selection. This criterion considers not only the importance of a sample to expanding the space coverage of the learned samples but also the expected number of queries needed to learn the sample. To facilitate semi-supervised clustering, the third technique yields inferred must-links for passing information about flat patches in the learned manifold to semi-supervised clustering algorithms. Experimental results have shown that the learned pairwise constraints can capture the underlying cluster structures and proven the feasibility of the proposed approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Research and evaluation of the effectiveness of e-learning in the case of linear programming

Directory of Open Access Journals (Sweden)

Ljiljana Miletić

2016-04-01

Full Text Available The paper evaluates the effectiveness of the e-learning approach to linear programming. The goal was to investigate how proper use of information and communication technologies (ICT and interactive learning helps to improve high school students’ understanding, learning and retention of advanced non-curriculum material. The hypothesis was that ICT and e-learning is helpful in teaching linear programming methods. In the first phase of the research, a module of lessons for linear programming (LP was created using the software package Loomen Moodle and other interactive software packages such as Geogebra. In the second phase, the LP module was taught as a short course to two groups of high school students. These two groups of students were second-grade students in a Croatian high school. In Class 1, the module was taught using ICT and e-learning, while the module was taught using classical methods in Class 2. The action research methodology was an integral part in delivering the course to both student groups. The sample student groups were carefully selected to ensure that differences in background knowledge and learning potential were statistically negligible. Relevant data was collected while delivering the course. Statistical analysis of the collected data showed that the student group using the e-learning method produced better results than the group using a classical learning method. These findings support previous results on the effectiveness of e-learning, and also establish a specific approach to e-learning in linear programming.

Machine learning-based methods for prediction of linear B-cell epitopes.

Science.gov (United States)

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

A Modified Approach to Team-Based Learning in Linear Algebra Courses

Science.gov (United States)

Nanes, Kalman M.

2014-01-01

This paper documents the author's adaptation of team-based learning (TBL), an active learning pedagogy developed by Larry Michaelsen and others, in the linear algebra classroom. The paper discusses the standard components of TBL and the necessary changes to those components for the needs of the course in question. There is also an empirically…

Full-Stokes polarimetry with circularly polarized feeds. Sources with stable linear and circular polarization in the GHz regime

Science.gov (United States)

Myserlis, I.; Angelakis, E.; Kraus, A.; Liontas, C. A.; Marchili, N.; Aller, M. F.; Aller, H. D.; Karamanavis, V.; Fuhrmann, L.; Krichbaum, T. P.; Zensus, J. A.

2018-01-01

We present an analysis pipeline that enables the recovery of reliable information for all four Stokes parameters with high accuracy. Its novelty relies on the effective treatment of the instrumental effects even before the computation of the Stokes parameters, contrary to conventionally used methods such as that based on the Müller matrix. For instance, instrumental linear polarization is corrected across the whole telescope beam and significant Stokes Q and U can be recovered even when the recorded signals are severely corrupted by instrumental effects. The accuracy we reach in terms of polarization degree is of the order of 0.1-0.2%. The polarization angles are determined with an accuracy of almost 1°. The presented methodology was applied to recover the linear and circular polarization of around 150 active galactic nuclei, which were monitored between July 2010 and April 2016 with the Effelsberg 100-m telescope at 4.85 GHz and 8.35 GHz with a median cadence of 1.2 months. The polarized emission of the Moon was used to calibrate the polarization angle measurements. Our analysis showed a small system-induced rotation of about 1° at both observing frequencies. Over the examined period, five sources have significant and stable linear polarization; three sources remain constantly linearly unpolarized; and a total of 11 sources have stable circular polarization degree mc, four of them with non-zero mc. We also identify eight sources that maintain a stable polarization angle. All this is provided to the community for future polarization observations reference. We finally show that our analysis method is conceptually different from those traditionally used and performs better than the Müller matrix method. Although it has been developed for a system equipped with circularly polarized feeds, it can easily be generalized to systems with linearly polarized feeds as well. The data used to create Fig. C.1 are only available at the CDS via anonymous ftp to http

New stable multiply charged negative atomic ions in linearly polarized superintense laser fields

International Nuclear Information System (INIS)

Wei Qi; Kais, Sabre; Moiseyev, Nimrod

2006-01-01

Singly charged negative atomic ions exist in the gas phase and are of fundamental importance in atomic and molecular physics. However, theoretical calculations and experimental results clearly exclude the existence of any stable doubly-negatively-charged atomic ion in the gas phase, only one electron can be added to a free atom in the gas phase. In this report, using the high-frequency Floquet theory, we predict that in a linear superintense laser field one can stabilize multiply charged negative atomic ions in the gas phase. We present self-consistent field calculations for the linear superintense laser fields needed to bind extra one and two electrons to form He - , He 2- , and Li 2- , with detachment energies dependent on the laser intensity and maximal values of 1.2, 0.12, and 0.13 eV, respectively. The fields and frequencies needed for binding extra electrons are within experimental reach. This method of stabilization is general and can be used to predict stability of larger multiply charged negative atomic ions

Danish stable schools for experiential common learning in groups of organic dairy farmers

DEFF Research Database (Denmark)

Waarst, M.; Nissen, T.B; Østergaard, I.

2007-01-01

in phasing out antibiotics from their herds through promotion of animal health. One way of reaching this goal was to form participatory focused farmer groups in an FFS approach, which was adapted to Danish conditions and named "stable schools." Four stable schools were established and went through a 1-yr......The farmer field school (FFS) is a concept for farmers' learning, knowledge exchange, and empowerment that has been developed and used in developing countries. In Denmark, a research project focusing on explicit non-antibiotic strategies involves farmers who have actively expressed an interest...

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan; Shamma, Jeff S.

2018-01-01

dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through

High-temperature stable absorber coatings for linear concentrating solar thermal power plants; Hochtemperaturstabile Absorberschichten fuer linear konzentrierende solarthermische Kraftwerke

Energy Technology Data Exchange (ETDEWEB)

Hildebrandt, Christina

2009-03-23

This work describes the development of new absorber coatings for different applications - para-bolic trough and linear Fresnel collectors - and operating conditions - absorber in vacuum or in air. The demand for higher efficiencies of solar thermal power plants using parabolic trough technology results in higher temperatures in the collectors and on the absorber tubes. As heat losses increase strongly with increasing temperatures, the need for a lower emissivity of the absorber coating at constant absorptivity arises. The linear Fresnel application envisions ab-sorber tubes stable in air at high temperatures of about 450 C, which are to date commercially not available. This work comprises the theoretical background, the modeling and the fabrication of absorber tubes including the technology transfer to a production-size inline sputter coater. In annealing tests and accompanying optical measurements, degradation processes have been observed and specified more precisely by material characterization techniques. The simulations provided the capability of different materials used as potential IR-reflector. The highest selectivity can be achieved by applying silver which consequently has been chosen for the application in absorber coatings of the parabolic trough technology. Thin silver films how-ever need to be stabilized when used at high temperatures. Appropriate barrier layers as well as process and layer parameters were identified. A high selectivity was achieved and stability of the absorber coating for 1200 h at 500 C in vacuum has been demonstrated. For the application in air, silver was also analyzed as a potential IR-reflector. Even though the stability could be increased considerably, it nevertheless proved to be insufficient. The main factors influencing stability in a positive way are the use of higher quality polishing, additional barrier layers and adequate process parameters. This knowledge was applied for developing coatings which are stable in air at

Stable single longitudinal mode erbium-doped silica fiber laser based on an asymmetric linear three-cavity structure

International Nuclear Information System (INIS)

Feng Ting; Yan Feng-Ping; Li Qi; Peng Wan-Jing; Feng Su-Chun; Tan Si-Yu; Wen Xiao-Dong

2013-01-01

We present a stable linear-cavity single longitudinal mode (SLM) erbium-doped silica fiber laser. It consists of four fiber Bragg gratings (FBGs) directly written in a section of photosensitive erbium-doped fiber (EDF) to form an asymmetric three-cavity structure. The stable SLM operation at a wavelength of 1545.112 nm with a 3-dB bandwidth of 0.012 nm and an optical signal-to-noise ratio (OSNR) of about 60 dB is verified experimentally. Under laboratory conditions, the performance of a power fluctuation of less than 0.05 dB observed from the power meter for 6 h and a wavelength variation of less than 0.01 nm obtained from the optical spectrum analyzer (OSA) for about 1.5 h are demonstrated. The gain fiber length is no longer limited to only several centimeters for SLM operation because of the excellent mode-selecting ability of the asymmetric three-cavity structure. The proposed scheme provides a simple and cost-effective approach to realizing a stable SLM fiber laser. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

On combining principal components with Fisher's linear discriminants for supervised learning

NARCIS (Netherlands)

Pechenizkiy, M.; Tsymbal, A.; Puuronen, S.

2006-01-01

"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic increase of computational complexity and classification error in high dimensions. In this paper, principal component analysis (PCA), parametric feature extraction (FE) based on Fisher’s linear

Using Cognitive Tutor Software in Learning Linear Algebra Word Concept

Science.gov (United States)

Yang, Kai-Ju

2015-01-01

This paper reports on a study of twelve 10th grade students using Cognitive Tutor, a math software program, to learn linear algebra word concept. The study's purpose was to examine whether students' mathematics performance as it is related to using Cognitive Tutor provided evidence to support Koedlinger's (2002) four instructional principles used…

Stable explicit coupling of the Yee scheme with a linear current model in fluctuating magnetized plasmas

International Nuclear Information System (INIS)

Silva, Filipe da; Pinto, Martin Campos; Després, Bruno; Heuraux, Stéphane

2015-01-01

This work analyzes the stability of the Yee scheme for non-stationary Maxwell's equations coupled with a linear current model with density fluctuations. We show that the usual procedure may yield unstable scheme for physical situations that correspond to strongly magnetized plasmas in X-mode (TE) polarization. We propose to use first order clustered discretization of the vectorial product that gives back a stable coupling. We validate the schemes on some test cases representative of direct numerical simulations of X-mode in a magnetic fusion plasma including turbulence

Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.

Science.gov (United States)

Wei, Qinglai; Li, Benkai; Song, Ruizhuo

2018-04-01

In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task.

Science.gov (United States)

Kinjo, Ken; Uchibe, Eiji; Doya, Kenji

2013-01-01

Linearly solvable Markov Decision Process (LMDP) is a class of optimal control problem in which the Bellman's equation can be converted into a linear equation by an exponential transformation of the state value function (Todorov, 2009b). In an LMDP, the optimal value function and the corresponding control policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunction problem in a continuous state using the knowledge of the system dynamics and the action, state, and terminal cost functions. In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in which the dynamics of the body and the environment have to be learned from experience. We first perform a simulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynamics model on the derived the action policy. The result shows that a crude linear approximation of the non-linear dynamics can still allow solution of the task, despite with a higher total cost. We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robot platform. The state is given by the position and the size of a battery in its camera view and two neck joint angles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servo controller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state cost functions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics model performed equivalently with the optimal linear quadratic regulator (LQR). In the non-quadratic task, the LMDP controller with a linear dynamics model showed the best performance. The results demonstrate the usefulness of the LMDP framework in real robot control even when simple linear models are used for dynamics learning.

Motivation, Classroom Environment, and Learning in Introductory Geology: A Hierarchical Linear Model

Science.gov (United States)

Gilbert, L. A.; Hilpert, J. C.; Van Der Hoeven Kraft, K.; Budd, D.; Jones, M. H.; Matheney, R.; Mcconnell, D. A.; Perkins, D.; Stempien, J. A.; Wirth, K. R.

2013-12-01

Prior research has indicated that highly motivated students perform better and that learning increases in innovative, reformed classrooms, but untangling the student effects from the instructor effects is essential to understanding how to best support student learning. Using a hierarchical linear model, we examine these effects separately and jointly. We use data from nearly 2,000 undergraduate students surveyed by the NSF-funded GARNET (Geoscience Affective Research NETwork) project in 65 different introductory geology classes at research universities, public masters-granting universities, liberal arts colleges and community colleges across the US. Student level effects were measured as increases in expectancy and self-regulation using the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991). Instructor level effects were measured using the Reformed Teaching Observation Protocol, (RTOP; Sawada et al., 2000), with higher RTOP scores indicating a more reformed, student-centered classroom environment. Learning was measured by learning gains on a Geology Concept Inventory (GCI; Libarkin and Anderson, 2005) and normalized final course grade. The hierarchical linear model yielded significant results at several levels. At the student level, increases in expectancy and self-regulation are significantly and positively related to higher grades regardless of instructor; the higher the increase, the higher the grade. At the instructor level, RTOP scores are positively related to normalized average GCI learning gains. The higher the RTOP score, the higher the average class GCI learning gains. Across both levels, average class GCI learning gains are significantly and positively related to student grades; the higher the GCI learning gain, the higher the grade. Further, the RTOP scores are significantly and negatively related to the relationship between expectancy and course grade. The lower the RTOP score, the higher the correlation between change in

Learning linear spatial-numeric associations improves accuracy of memory for numbers

Directory of Open Access Journals (Sweden)

Clarissa Ann Thompson

2016-01-01

Full Text Available Memory for numbers improves with age and experience. One potential source of improvement is a logarithmic-to-linear shift in children’s representations of magnitude. To test this, Kindergartners and second graders estimated the location of numbers on number lines and recalled numbers presented in vignettes (Study 1. Accuracy at number-line estimation predicted memory accuracy on a numerical recall task after controlling for the effect of age and ability to approximately order magnitudes (mapper status. To test more directly whether linear numeric magnitude representations caused improvements in memory, half of children were given feedback on their number-line estimates (Study 2. As expected, learning linear representations was again linked to memory for numerical information even after controlling for age and mapper status. These results suggest that linear representations of numerical magnitude may be a causal factor in development of numeric recall accuracy.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task

Directory of Open Access Journals (Sweden)

Ken eKinjo

2013-04-01

Full Text Available Linearly solvable Markov Decision Process (LMDP is a class of optimal control problem in whichthe Bellman’s equation can be converted into a linear equation by an exponential transformation ofthe state value function (Todorov, 2009. In an LMDP, the optimal value function and the correspondingcontrol policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunctionproblem in a continuous state using the knowledge of the system dynamics and the action, state, andterminal cost functions.In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in whichthe dynamics of the body and the environment have to be learned from experience. We first perform asimulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynam-ics model on the derived the action policy. The result shows that a crude linear approximation of thenonlinear dynamics can still allow solution of the task, despite with a higher total cost.We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robotplatform. The state is given by the position and the size of a battery in its camera view and two neck jointangles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servocontroller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state costfunctions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics modelperformed equivalently with the optimal linear quadratic controller (LQR. In the non-quadratic task, theLMDP controller with a linear dynamics model showed the best performance. The results demonstratethe usefulness of the LMDP framework in real robot control even when simple linear models are usedfor dynamics learning.

Stable schizophrenia patients learn equally well as age-matched controls and better than elderly controls in two sensorimotor rotary pursuit tasks

NARCIS (Netherlands)

Picker, L.J. De; Cornelis, C.; Hulstijn, W.; Dumont, G.J.H.; Fransen, E.; Timmers, M.; Janssens, L.; Morrens, M.; Sabbe, B.G.C.

2014-01-01

Objective: To compare sensorimotor performance and learning in stable schizophrenia patients, healthy age- and sex-matched controls and elderly controls on two variations of the rotary pursuit: circle pursuit (true motor learning) and figure pursuit (motor and sequence learning). Method: In the

Longitudinal mathematics development of students with learning disabilities and students without disabilities: a comparison of linear, quadratic, and piecewise linear mixed effects models.

Science.gov (United States)

Kohli, Nidhi; Sullivan, Amanda L; Sadeh, Shanna; Zopluoglu, Cengiz

2015-04-01

Effective instructional planning and intervening rely heavily on accurate understanding of students' growth, but relatively few researchers have examined mathematics achievement trajectories, particularly for students with special needs. We applied linear, quadratic, and piecewise linear mixed-effects models to identify the best-fitting model for mathematics development over elementary and middle school and to ascertain differences in growth trajectories of children with learning disabilities relative to their typically developing peers. The analytic sample of 2150 students was drawn from the Early Childhood Longitudinal Study - Kindergarten Cohort, a nationally representative sample of United States children who entered kindergarten in 1998. We first modeled students' mathematics growth via multiple mixed-effects models to determine the best fitting model of 9-year growth and then compared the trajectories of students with and without learning disabilities. Results indicate that the piecewise linear mixed-effects model captured best the functional form of students' mathematics trajectories. In addition, there were substantial achievement gaps between students with learning disabilities and students with no disabilities, and their trajectories differed such that students without disabilities progressed at a higher rate than their peers who had learning disabilities. The results underscore the need for further research to understand how to appropriately model students' mathematics trajectories and the need for attention to mathematics achievement gaps in policy. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

L1-norm locally linear representation regularization multi-source adaptation learning.

Science.gov (United States)

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

An Example of Competence-Based Learning: Use of Maxima in Linear Algebra for Engineers

Science.gov (United States)

Diaz, Ana; Garcia, Alfonsa; de la Villa, Agustin

2011-01-01

This paper analyses the role of Computer Algebra Systems (CAS) in a model of learning based on competences. The proposal is an e-learning model Linear Algebra course for Engineering, which includes the use of a CAS (Maxima) and focuses on problem solving. A reference model has been taken from the Spanish Open University. The proper use of CAS is…

Learning oncogenetic networks by reducing to mixed integer linear programming.

Science.gov (United States)

Shahrabi Farahani, Hossein; Lagergren, Jens

2013-01-01

Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

A Neural Circuit for Acoustic Navigation combining Heterosynaptic and Non-synaptic Plasticity that learns Stable Trajectories

DEFF Research Database (Denmark)

Shaikh, Danish; Manoonpong, Poramate

2017-01-01

controllers be resolved in a manner that generates consistent and stable robot trajectories? We propose a neural circuit that minimises this conflict by learning sensorimotor mappings as neuronal transfer functions between the perceived sound direction and wheel velocities of a simulated non-holonomic mobile...

Investigating Students' Modes of Thinking in Linear Algebra: The Case of Linear Independence

Science.gov (United States)

Çelik, Derya

2015-01-01

Linear algebra is one of the most challenging topics to learn and teach in many countries. To facilitate the teaching and learning of linear algebra, priority should be given to epistemologically analyze the concepts that the undergraduate students have difficulty in conceptualizing and to define their ways of reasoning in linear algebra. After…

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

Science.gov (United States)

Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

2017-01-01

In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

Participatory Common Learning in Groups of Dairy Farmers in Uganda (FFS approach) and Danish Stable Schools

DEFF Research Database (Denmark)

Vaarst, Mette

on a Master Thesis in Health Anthropology and a mini manual to the so-called Stable Schools. Improvements of farming practices should be based on the context of the individual farm and include the goals of the farmer and the farming system. This should be the case in all types of farming systems. Viewing...... learning as a social phenomenon and process, as well as an interaction between the learner and the learning environment (including other farmers) may give opportunities for context based innovations and developments towards a common goal in a group of farmers....

Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS Severity

Directory of Open Access Journals (Sweden)

Jorge Bosch-Bayard

2018-01-01

Full Text Available In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia, Mathematics (Dyscalculia, or Writing (Dysgraphia. By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

Sensitivity, specificity and predictive values of linear and nonlinear indices of heart rate variability in stable angina patients

Directory of Open Access Journals (Sweden)

Pivatelli Flávio

2012-10-01

Full Text Available Abstract Background Decreased heart rate variability (HRV is related to higher morbidity and mortality. In this study we evaluated the linear and nonlinear indices of the HRV in stable angina patients submitted to coronary angiography. Methods We studied 77 unselected patients for elective coronary angiography, which were divided into two groups: coronary artery disease (CAD and non-CAD groups. For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 40 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal], NN50 [total number of adjacent RR intervals with a difference of duration greater than 50ms] and RMSSD [root-mean square of differences] and frequency domains ultra-low frequency (ULF ≤ 0,003 Hz, very low frequency (VLF 0,003 – 0,04 Hz, low frequency (LF (0.04–0.15 Hz, and high frequency (HF (0.15–0.40 Hz as well as the ratio between LF and HF components (LF/HF. In relation to the nonlinear indices we evaluated SD1, SD2, SD1/SD2, approximate entropy (−ApEn, α1, α2, Lyapunov Exponent, Hurst Exponent, autocorrelation and dimension correlation. The definition of the cutoff point of the variables for predictive tests was obtained by the Receiver Operating Characteristic curve (ROC. The area under the ROC curve was calculated by the extended trapezoidal rule, assuming as relevant areas under the curve ≥ 0.650. Results Coronary arterial disease patients presented reduced values of SDNN, RMSSD, NN50, HF, SD1, SD2 and -ApEn. HF ≤ 66 ms2, RMSSD ≤ 23.9 ms, ApEn ≤−0.296 and NN50 ≤ 16 presented the best discriminatory power for the presence of significant coronary obstruction. Conclusion We suggest the use of Heart Rate Variability Analysis in linear and nonlinear domains, for prognostic purposes in patients with stable angina pectoris, in view of their overall impairment.

Stable and High OSNR Compound Linear-Cavity Single-Longitudinal-Mode Erbium-Doped Silica Fiber Laser Based on an Asymmetric Four-Cavity Structure

International Nuclear Information System (INIS)

Feng Ting; Yan Feng-Ping; Li Qi; Peng Wan-Jing; Feng Su-Chun; Wen Xiao-Dong; Tan Si-Yu; Liu Peng

2012-01-01

We propose a stable and high optical signal-to-noise ratio (OSNR) compound linear-cavity single-longitudinal-mode (SLM) erbium-doped silica fiber laser. It consists of three uniform fiber Bragg gratings (FBGs) and two fiber couplers to form a simple asymmetric four-cavity structure to select the longitudinal mode. The stable SLM operation at the wavelength of 1544.053 nm with a 3 dB bandwidth of 0.014 nm and an OSNR of ∼60 dB was verified experimentally. Under laboratory conditions, a power fluctuation performance of less than 0.05 dB for 5 h and wavelength variation of less than 0.01 nm for about 150 min is demonstrated. Finally, the characteristic of laser output power as a function of pump power is investigated. The proposed system provides a simple and cost-effective approach to realize a stable SLM fiber laser

An Improved EMD-Based Dissimilarity Metric for Unsupervised Linear Subspace Learning

Directory of Open Access Journals (Sweden)

Xiangchun Yu

2018-01-01

Full Text Available We investigate a novel way of robust face image feature extraction by adopting the methods based on Unsupervised Linear Subspace Learning to extract a small number of good features. Firstly, the face image is divided into blocks with the specified size, and then we propose and extract pooled Histogram of Oriented Gradient (pHOG over each block. Secondly, an improved Earth Mover’s Distance (EMD metric is adopted to measure the dissimilarity between blocks of one face image and the corresponding blocks from the rest of face images. Thirdly, considering the limitations of the original Locality Preserving Projections (LPP, we proposed the Block Structure LPP (BSLPP, which effectively preserves the structural information of face images. Finally, an adjacency graph is constructed and a small number of good features of a face image are obtained by methods based on Unsupervised Linear Subspace Learning. A series of experiments have been conducted on several well-known face databases to evaluate the effectiveness of the proposed algorithm. In addition, we construct the noise, geometric distortion, slight translation, slight rotation AR, and Extended Yale B face databases, and we verify the robustness of the proposed algorithm when faced with a certain degree of these disturbances.

Transient Response Analysis of Metropolis Learning in Games

KAUST Repository

Jaleel, Hassan

2017-10-19

The objective of this work is to provide a qualitative description of the transient properties of stochastic learning dynamics like adaptive play, log-linear learning, and Metropolis learning. The solution concept used in these learning dynamics for potential games is that of stochastic stability, which is based on the stationary distribution of the reversible Markov chain representing the learning process. However, time to converge to a stochastically stable state is exponential in the inverse of noise, which limits the use of stochastic stability as an effective solution concept for these dynamics. We propose a complete solution concept that qualitatively describes the state of the system at all times. The proposed concept is prevalent in control systems literature where a solution to a linear or a non-linear system has two parts, transient response and steady state response. Stochastic stability provides the steady state response of stochastic learning rules. In this work, we study its transient properties. Starting from an initial condition, we identify the subsets of the state space called cycles that have small hitting times and long exit times. Over the long time scales, we provide a description of how the distributions over joint action profiles transition from one cycle to another till it reaches the globally optimal state.

Transient Response Analysis of Metropolis Learning in Games

KAUST Repository

Jaleel, Hassan; Shamma, Jeff S.

2017-01-01

The objective of this work is to provide a qualitative description of the transient properties of stochastic learning dynamics like adaptive play, log-linear learning, and Metropolis learning. The solution concept used in these learning dynamics for potential games is that of stochastic stability, which is based on the stationary distribution of the reversible Markov chain representing the learning process. However, time to converge to a stochastically stable state is exponential in the inverse of noise, which limits the use of stochastic stability as an effective solution concept for these dynamics. We propose a complete solution concept that qualitatively describes the state of the system at all times. The proposed concept is prevalent in control systems literature where a solution to a linear or a non-linear system has two parts, transient response and steady state response. Stochastic stability provides the steady state response of stochastic learning rules. In this work, we study its transient properties. Starting from an initial condition, we identify the subsets of the state space called cycles that have small hitting times and long exit times. Over the long time scales, we provide a description of how the distributions over joint action profiles transition from one cycle to another till it reaches the globally optimal state.

STRIP: stream learning of influence probabilities

DEFF Research Database (Denmark)

Kutzkov, Konstantin

2013-01-01

cascades, and developing applications such as viral marketing. Motivated by modern microblogging platforms, such as twitter, in this paper we study the problem of learning influence probabilities in a data-stream scenario, in which the network topology is relatively stable and the challenge of a learning...... algorithm is to keep up with a continuous stream of tweets using a small amount of time and memory. Our contribution is a number of randomized approximation algorithms, categorized according to the available space (superlinear, linear, and sublinear in the number of nodes n) and according to dierent models...

Stability properties of nonlinear dynamical systems and evolutionary stable states

Energy Technology Data Exchange (ETDEWEB)

Gleria, Iram, E-mail: iram@fis.ufal.br [Instituto de Física, Universidade Federal de Alagoas, 57072-970 Maceió-AL (Brazil); Brenig, Leon [Faculté des Sciences, Université Libre de Bruxelles, 1050 Brussels (Belgium); Rocha Filho, Tarcísio M.; Figueiredo, Annibal [Instituto de Física and International Center for Condensed Matter Physics, Universidade de Brasília, 70919-970 Brasília-DF (Brazil)

2017-03-18

Highlights: • We address the problem of equilibrium stability in a general class of non-linear systems. • We link Evolutionary Stable States (ESS) to stable fixed points of square quasi-polynomial (QP) systems. • We show that an interior ES point may be related to stable interior fixed points of QP systems. - Abstract: In this paper we address the problem of stability in a general class of non-linear systems. We establish a link between the concepts of asymptotic stable interior fixed points of square Quasi-Polynomial systems and evolutionary stable states, a property of some payoff matrices arising from evolutionary games.

Some Stiffly Stable Second Derivative Continuous Linear Multistep ...

African Journals Online (AJOL)

Dr Grace Nwachukwu

G. C. Nwachukwu, Department of Mathematics, University of Benin, Benin City, Nigeria ...... perform better than Enright's method when applied to the linear problem. ... author is grateful to Dr. R. I. Okuonghae for benefiting from his Ph.D. Thesis.

The Effect of Using Concept Maps in Elementary Linear Algebra Course on Students’ Learning

Science.gov (United States)

Syarifuddin, H.

2018-04-01

This paper presents the results of a classroom action research that was done in Elementary Linear Algebra course at Universitas Negeri Padang. The focus of the research want to see the effect of using concept maps in the course on students’ learning. Data in this study were collected through classroom observation, students’ reflective journal and concept maps that were created by students. The result of the study was the using of concept maps in Elementary Linera Algebra course gave positive effect on students’ learning.

Student Reactions to Learning Theory Based Curriculum Materials in Linear Algebra--A Survey Analysis

Science.gov (United States)

Cooley, Laurel; Vidakovic, Draga; Martin, William O.; Dexter, Scott; Suzuki, Jeff

2016-01-01

In this report we examine students' perceptions of the implementation of carefully designed curriculum materials (called modules) in linear algebra courses at three different universities. The curricular materials were produced collaboratively by STEM and mathematics education faculty as members of a professional learning community (PLC) over…

Adaptive rival penalized competitive learning and combined linear predictor model for financial forecast and investment.

Science.gov (United States)

Cheung, Y M; Leung, W M; Xu, L

1997-01-01

We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learning mechanism as well as a data pre-and-post processing scheme. We compare them with some existing models by demonstrating their performance on two real-world financial time series--a China stock price and an exchange-rate series of US Dollar (USD) versus Deutschmark (DEM). Experiments have shown that Adaptive RPCL-CLP not only outperforms the other approaches with the smallest prediction error and training costs, but also brings in considerable high profits in the trading simulation of foreign exchange market.

Learning Bayesian network structure: towards the essential graph by integer linear programming tools

Czech Academy of Sciences Publication Activity Database

Studený, Milan; Haws, D.

2014-01-01

Roč. 55, č. 4 (2014), s. 1043-1071 ISSN 0888-613X R&D Projects: GA ČR GA13-20012S Institutional support: RVO:67985556 Keywords : learning Bayesian network structure * integer linear programming * characteristic imset * essential graph Subject RIV: BA - General Mathematics Impact factor: 2.451, year: 2014 http://library.utia.cas.cz/separaty/2014/MTR/studeny-0427002.pdf

Case Studies Listening to Students Using Kinesthetic Movement While Learning to Graph Linear Functions

Science.gov (United States)

Novak, Melissa A.

2017-01-01

The purpose of this qualitative practitioner research study was to describe middle school algebra students' experiences of learning linear functions through kinesthetic movement. Participants were comprised of 8th grade algebra students. Practitioner research was used because I wanted to improve my teaching so students will have more success in…

Evaluating and Improving a Learning Trajectory for Linear Measurement in Elementary Grades 2 and 3: A Longitudinal Study

Science.gov (United States)

Barrett, Jeffrey E.; Sarama, Julie; Clements, Douglas H.; Cullen, Craig; McCool, Jenni; Witkowski-Rumsey, Chepina; Klanderman, David

2012-01-01

We examined children's development of strategic and conceptual knowledge for linear measurement. We conducted teaching experiments with eight students in grades 2 and 3, based on our hypothetical learning trajectory for length to check its coherence and to strengthen the domain-specific model for learning and teaching. We checked the hierarchical…

Research on the intermediate process of a free-piston linear generator from cold start-up to stable operation: Numerical model and experimental results

International Nuclear Information System (INIS)

Feng, Huihua; Guo, Chendong; Jia, Boru; Zuo, Zhengxing; Guo, Yuyao; Roskilly, Tony

2016-01-01

Highlights: • The intermediate process of free-piston linear generator is investigated for the first time. • “Gradually switching strategy” is the best strategy in the intermediate process. • Switching at the top dead center position timing has the least influences on free-piston linear generator. • After the intermediate process, the operation parameters value is smaller than those before the intermediate process. - Abstract: The free-piston linear generator (FPLG) has more merits than the traditional reciprocating engines (TRE), and has been under extensive investigation. Researchers mainly investigated on the starting process and the stable generating process of FPLG, while there has not been any report on the intermediate process from the engine cold start-up to stable operation process. Therefore, this paper investigated the intermediate process of the FPLG in terms of switching strategy and switching position based on simulation results and test results. Results showed that when the motor force of the linear electric machine (LEM) declined gradually from 100% to 0% with an interval of 50%, and then to a resistance force in the opposite direction of piston velocity (generator mode), the operation parameters of the FPLG showed minimal changes. Meanwhile, the engine operated more smoothly when the LEM switched its working mode from a motor to a generator at the piston dead center, compared with that at the middle stroke or a random switching time. More importantly, after the intermediate process, the operation parameters of FPLG were smaller than that before the intermediate process. As a result, a gradual motor/generator switching strategy was recommended and the LEM was suggested to switch its working mode when the piston arrived its dead center in order to achieve smooth engine operation.

Towards stable acceleration in LINACS

CERN Document Server

Dubrovskiy, A D

2014-01-01

Ultra-stable and -reproducible high-energy particle beams with short bunches are needed in novel linear accelerators and, in particular, in the Compact Linear Collider CLIC. A passive beam phase stabilization system based on a bunch compression with a negative transfer matrix element R56 and acceleration at a positive off-crest phase is proposed. The motivation and expected advantages of the proposed scheme are outlined.

Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning.

Science.gov (United States)

Cho, Sun-Joo; Goodwin, Amanda P

2016-04-01

When word learning is supported by instruction in experimental studies for adolescents, word knowledge outcomes tend to be collected from complex data structure, such as multiple aspects of word knowledge, multilevel reader data, multilevel item data, longitudinal design, and multiple groups. This study illustrates how generalized linear mixed models can be used to measure and explain word learning for data having such complexity. Results from this application provide deeper understanding of word knowledge than could be attained from simpler models and show that word knowledge is multidimensional and depends on word characteristics and instructional contexts.

Recipes for stable linear embeddings from Hilbert spaces to R^m

OpenAIRE

Puy, Gilles; Davies, Michael; Gribonval, Remi

2017-01-01

We consider the problem of constructing a linear map from a Hilbert space H (possibly infinite dimensional) to Rm that satisfies a restricted isometry property (RIP) on an arbitrary signal model, i.e., a subset of H. We present a generic framework that handles a large class of low-dimensional subsets but also unstructured and structured linear maps. We provide a simple recipe to prove that a random linear map satisfies a general RIP with high probability. We also describe a generic technique ...

Recipes for stable linear embeddings from Hilbert spaces to R^m

OpenAIRE

Puy, Gilles; Davies, Mike; Gribonval, Rémi

2015-01-01

We consider the problem of constructing a linear map from a Hilbert space $\\mathcal{H}$ (possibly infinite dimensional) to $\\mathbb{R}^m$ that satisfies a restricted isometry property (RIP) on an arbitrary signal model $\\mathcal{S} \\subset \\mathcal{H}$. We present a generic framework that handles a large class of low-dimensional subsets but also unstructured and structured linear maps. We provide a simple recipe to prove that a random linear map satisfies a general RIP on $\\mathcal{S}$ with h...

Imitation learning of Non-Linear Point-to-Point Robot Motions using Dirichlet Processes

DEFF Research Database (Denmark)

Krüger, Volker; Tikhanoff, Vadim; Natale, Lorenzo

2012-01-01

In this paper we discuss the use of the infinite Gaussian mixture model and Dirichlet processes for learning robot movements from demonstrations. Starting point of this work is an earlier paper where the authors learn a non-linear dynamic robot movement model from a small number of observations....... The model in that work is learned using a classical finite Gaussian mixture model (FGMM) where the Gaussian mixtures are appropriately constrained. The problem with this approach is that one needs to make a good guess for how many mixtures the FGMM should use. In this work, we generalize this approach...... our algorithm on the same data that was used in [5], where the authors use motion capture devices to record the demonstrations. As further validation we test our approach on novel data acquired on our iCub in a different demonstration scenario in which the robot is physically driven by the human...

Stable schizophrenia patients learn equally well as age-matched controls and better than elderly controls in two sensorimotor Rotary Pursuit tasks

Directory of Open Access Journals (Sweden)

Livia J. De Picker

2014-11-01

Full Text Available Objective: To compare sensorimotor performance and learning in stable schizophrenia patients, healthy age- and sex-matched controls and elderly controls on two variations of the Rotary Pursuit: Circle Pursuit (true motor learning and Figure Pursuit (motor and sequence learning.Method: In the Circle Pursuit a target circle, rotating with increasing speed along a predictable circular path on the computer screen, must be followed by a cursor controlled by a pen on a writing tablet. In the eight-trial Figure Pursuit, subjects learn to draw a complex figure by pursuing the target circle that moves along an invisible trajectory between and around several goals. Tasks were administered thrice (day 1, day 2, day 7 to 30 patients with stable schizophrenia (S, 30 healthy age- and sex-matched controls (C and 30 elderly participants (>65y; E and recorded with a digitizing tablet and pressure-sensitive pen. The outcome measure accuracy (% of time that cursor is within the target was used to assess performance.Results: We observed significant group differences in accuracy, both in Circle and Figure Pursuit tasks (Elearning effects were found in each group. Learning curves were similar in Circle Pursuit but differed between groups in Figure Pursuit. When corrected for group differences in starting level, the learning gains over the three sessions of schizophrenia patients and age-matched controls were equal and both were larger than those of the elderly controls. Conclusion: Despite the reduced sensorimotor performance that was found in the schizophrenia patients their sensorimotor learning seems to be preserved. The relevance of this finding for the evaluation of procedural learning in schizophrenia is discussed. The better performance and learning rate of the patients compared to the elderly controls was unexpected and deserves further study.

Flexible learning intinerary vs. linear learning itinerary

OpenAIRE

Martín San José, Juan Fernando; Juan Lizandra, María Carmen; Gil Gómez, Jose Antonio; Rando, Noemí

2014-01-01

The latest video game and entertainment technology and other technologies are facilitating the development of new and powerful e-Learning systems. In this paper, we present a computer-based game for learning about five historical ages. The objective of the game is to reinforce the events that mark the transition from one historical age to another and the order of the historical ages. Our game incorporates natural human-computer interaction based on video game technology, Frontal Projection, a...

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

Science.gov (United States)

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

Rectified-Linear-Unit-Based Deep Learning for Biomedical Multi-label Data.

Science.gov (United States)

Wang, Pu; Ge, Ruiquan; Xiao, Xuan; Cai, Yunpeng; Wang, Guoqing; Zhou, Fengfeng

2017-09-01

Disease diagnosis is one of the major data mining questions by the clinicians. The current diagnosis models usually have a strong assumption that one patient has only one disease, i.e. a single-label data mining problem. But the patients, especially when at the late stages, may have more than one disease and require a multi-label diagnosis. The multi-label data mining is much more difficult than a single-label one, and very few algorithms have been developed for this situation. Deep learning is a data mining algorithm with highly dense inner structure and has achieved many successful applications in the other areas. We propose a hypothesis that rectified-linear-unit-based deep learning algorithm may also be good at the clinical questions, by revising the last layer as a multi-label output. The proof-of-concept experimental data support the hypothesis, and the community may be interested in trying more applications.

Supportive Learning: Linear Learning and Collaborative Learning

Science.gov (United States)

Lee, Bih Ni; Abdullah, Sopiah; Kiu, Su Na

2016-01-01

This is a conceptual paper which is trying to look at the educational technology is not limited to high technology. However, electronic educational technology, also known as e-learning, has become an important part of today's society, which consists of a wide variety of approaches to digitization, components and methods of delivery. In the…

Linear and integer programming made easy

CERN Document Server

Hu, T C

2016-01-01

Linear and integer programming are fundamental toolkits for data and information science and technology, particularly in the context of today’s megatrends toward statistical optimization, machine learning, and big data analytics. Drawn from over 30 years of classroom teaching and applied research experience, this textbook provides a crisp and practical introduction to the basics of linear and integer programming. The authors’ approach is accessible to students from all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification, and computer vision. Readers will learn to cast hard combinatorial problems as mathematical programming optimizations, understand how to achieve formulations where the objective and constraints are linear, choose appropriate solution methods, and interpret results appropriately. •Provides a concise introduction to linear and integer programming, appropriate for undergraduates, graduates, a short cours...

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

Science.gov (United States)

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Research on the Combustion Characteristics of a Free-Piston Gasoline Engine Linear Generator during the Stable Generating Process

Directory of Open Access Journals (Sweden)

Yuxi Miao

2016-08-01

Full Text Available The free-piston gasoline engine linear generator (FPGLG is a new kind of power plant consisting of free-piston gasoline engines and a linear generator. Due to the elimination of the crankshaft mechanism, the piston motion process and the combustion heat release process affect each other significantly. In this paper, the combustion characteristics during the stable generating process of a FPGLG were presented using a numerical iteration method, which coupled a zero-dimensional piston dynamic model and a three-dimensional scavenging model with the combustion process simulation. The results indicated that, compared to the conventional engine (CE, the heat release process of the FPGLG lasted longer with a lower peak heat release rate. The indicated thermal efficiency of the engine was lower because less heat was released around the piston top dead centre (TDC. Very minimal difference was observed on the ignition delay duration between the FPGLG and the CE, while the post-combustion period of the FPGLG was significantly longer than that of the CE. Meanwhile, the FPGLG was found to operate more moderately due to lower peak in-cylinder gas pressure and a lower pressure rising rate. The potential advantage of the FPGLG in lower NOx emission was also proven with the simulation results presented in this paper.

New robust stable MPC using linear matrix inequalities

Directory of Open Access Journals (Sweden)

M.A. Rodrigues

2000-03-01

Full Text Available This paper addresses the stability of Model Predictive Control (MPC with output feedback. The proposed controller uses a new state-space formulation of the system, and the control problem is presented as an LMI optimization problem. The stability condition for the closed loop is included as a Lyapunov inequality. The resulting optimization problem becomes nonlinear with the inclusion of the stabilizing condition. A suboptimal solution is developed and the problem reduces to a pair of coupled LMI problems. An iterative solution that converges to a stable output feedback gain is proposed. A polytopic set of process models can be considered. A simulation example is included in the paper and shows that the proposed strategy eliminates the usual practice of enforcing robustness by detuning the MP controller.

Design for simultaneous acceleration of stable and unstable beams in a superconducting heavy-ion linear accelerator for RISP

Science.gov (United States)

Kim, Jongwon; Son, Hyock-Jun; Park, Young-Ho

2017-11-01

The post-accelerator of isotope separation on-line (ISOL) system for rare isotope science project (RISP) is a superconducting linear accelerator (SC-linac) with a DC equivalent voltage of around 160 MV. An isotope beam extracted from the ISOL is in a charge state of 1+ and its charge state is increased to n+ by charge breeding with an electron beam ion source (EBIS). The charge breeding takes tens of ms and the pulse width of extracted beam from the EBIS is tens of μs, which operates at up to 30 Hz. Consequently a large portion of radio frequency (rf) time of the post SC-linac is unused. The post-linac is equipped also with an electron cyclotron resonance (ECR) ion source for stable ion acceleration. Thanks to the large phase acceptance of SC-linac, it is possible to accelerate simultaneously both stable and radioisotope ions with a similar charge to mass ratio by sharing rf time. This operation scheme is implemented for RISP with the addition of an electric chopper and magnetic kickers. The facility will be capable of providing the users of the ISOL and in-flight fragmentation (IF) systems with different beams simultaneously, which would help nuclear science users in obtaining a beam time as high-precision measurements often need long hours.

Verbal learning changes in older adults across 18 months.

Science.gov (United States)

Zimprich, Daniel; Rast, Philippe

2009-07-01

The major aim of this study was to investigate individual changes in verbal learning across a period of 18 months. Individual differences in verbal learning have largely been neglected in the last years and, even more so, individual differences in change in verbal learning. The sample for this study comes from the Zurich Longitudinal Study on Cognitive Aging (ZULU; Zimprich et al., 2008a) and comprised 336 older adults in the age range of 65-80 years at first measurement occasion. In order to address change in verbal learning we used a latent change model of structured latent growth curves to account for the non-linearity of the verbal learning data. The individual learning trajectories were captured by a hyperbolic function which yielded three psychologically distinct parameters: initial performance, learning rate, and asymptotic performance. We found that average performance increased with respect to initial performance, but not in learning rate or in asymptotic performance. Further, variances and covariances remained stable across both measurement occasions, indicating that the amount of individual differences in the three parameters remained stable, as did the relationships among them. Moreover, older adults differed reliably in their amount of change in initial performance and asymptotic performance. Eventually, changes in asymptotic performance and learning rate were strongly negatively correlated. It thus appears as if change in verbal learning in old age is a constrained process: an increase in total learning capacity implies that it takes longer to learn. Together, these results point to the significance of individual differences in change of verbal learning in the elderly.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri Vocational School students

Science.gov (United States)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-03-01

This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri vocational school students

Science.gov (United States)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-05-01

This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

Deep Learning Methods for Improved Decoding of Linear Codes

Science.gov (United States)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

Linear hypergeneralization of learned dynamics across movement speeds reveals anisotropic, gain-encoding primitives for motor adaptation.

Science.gov (United States)

Joiner, Wilsaan M; Ajayi, Obafunso; Sing, Gary C; Smith, Maurice A

2011-01-01

The ability to generalize learned motor actions to new contexts is a key feature of the motor system. For example, the ability to ride a bicycle or swing a racket is often first developed at lower speeds and later applied to faster velocities. A number of previous studies have examined the generalization of motor adaptation across movement directions and found that the learned adaptation decays in a pattern consistent with the existence of motor primitives that display narrow Gaussian tuning. However, few studies have examined the generalization of motor adaptation across movement speeds. Following adaptation to linear velocity-dependent dynamics during point-to-point reaching arm movements at one speed, we tested the ability of subjects to transfer this adaptation to short-duration higher-speed movements aimed at the same target. We found near-perfect linear extrapolation of the trained adaptation with respect to both the magnitude and the time course of the velocity profiles associated with the high-speed movements: a 69% increase in movement speed corresponded to a 74% extrapolation of the trained adaptation. The close match between the increase in movement speed and the corresponding increase in adaptation beyond what was trained indicates linear hypergeneralization. Computational modeling shows that this pattern of linear hypergeneralization across movement speeds is not compatible with previous models of adaptation in which motor primitives display isotropic Gaussian tuning of motor output around their preferred velocities. Instead, we show that this generalization pattern indicates that the primitives involved in the adaptation to viscous dynamics display anisotropic tuning in velocity space and encode the gain between motor output and motion state rather than motor output itself.

Multilevel linear modelling of the response-contingent learning of young children with significant developmental delays.

Science.gov (United States)

Raab, Melinda; Dunst, Carl J; Hamby, Deborah W

2018-02-27

The purpose of the study was to isolate the sources of variations in the rates of response-contingent learning among young children with multiple disabilities and significant developmental delays randomly assigned to contrasting types of early childhood intervention. Multilevel, hierarchical linear growth curve modelling was used to analyze four different measures of child response-contingent learning where repeated child learning measures were nested within individual children (Level-1), children were nested within practitioners (Level-2), and practitioners were nested within the contrasting types of intervention (Level-3). Findings showed that sources of variations in rates of child response-contingent learning were associated almost entirely with type of intervention after the variance associated with differences in practitioners nested within groups were accounted for. Rates of child learning were greater among children whose existing behaviour were used as the building blocks for promoting child competence (asset-based practices) compared to children for whom the focus of intervention was promoting child acquisition of missing skills (needs-based practices). The methods of analysis illustrate a practical approach to clustered data analysis and the presentation of results in ways that highlight sources of variations in the rates of response-contingent learning among young children with multiple developmental disabilities and significant developmental delays. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Linear models with R

CERN Document Server

Faraway, Julian J

2014-01-01

A Hands-On Way to Learning Data AnalysisPart of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with R, Second Edition explains how to use linear models in physical science, engineering, social science, and business applications. The book incorporates several improvements that reflect how the world of R has greatly expanded since the publication of the first edition.New to the Second EditionReorganiz

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

Science.gov (United States)

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

Science.gov (United States)

Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

2017-05-01

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

Ultra-Low-Dropout Linear Regulator

Science.gov (United States)

Thornton, Trevor; Lepkowski, William; Wilk, Seth

2011-01-01

A radiation-tolerant, ultra-low-dropout linear regulator can operate between -150 and 150 C. Prototype components were demonstrated to be performing well after a total ionizing dose of 1 Mrad (Si). Unlike existing components, the linear regulator developed during this activity is unconditionally stable over all operating regimes without the need for an external compensation capacitor. The absence of an external capacitor reduces overall system mass/volume, increases reliability, and lowers cost. Linear regulators generate a precisely controlled voltage for electronic circuits regardless of fluctuations in the load current that the circuit draws from the regulator.

Using Example Generation to Explore Students' Understanding of the Concepts of Linear Dependence/Independence in Linear Algebra

Science.gov (United States)

Aydin, Sinan

2014-01-01

Linear algebra is a basic mathematical subject taught in mathematics and science depar-tments of universities. The teaching and learning of this course has always been difficult. This study aims to contribute to the research in linear algebra education, focusing on linear dependence and independence concepts. This was done by introducing…

Non-linear learning in online tutorial to enhance students’ knowledge on normal distribution application topic

Science.gov (United States)

Kartono; Suryadi, D.; Herman, T.

2018-01-01

This study aimed to analyze the enhancement of non-linear learning (NLL) in the online tutorial (OT) content to students’ knowledge of normal distribution application (KONDA). KONDA is a competence expected to be achieved after students studied the topic of normal distribution application in the course named Education Statistics. The analysis was performed by quasi-experiment study design. The subject of the study was divided into an experimental class that was given OT content in NLL model and a control class which was given OT content in conventional learning (CL) model. Data used in this study were the results of online objective tests to measure students’ statistical prior knowledge (SPK) and students’ pre- and post-test of KONDA. The statistical analysis test of a gain score of KONDA of students who had low and moderate SPK’s scores showed students’ KONDA who learn OT content with NLL model was better than students’ KONDA who learn OT content with CL model. Meanwhile, for students who had high SPK’s scores, the gain score of students who learn OT content with NLL model had relatively similar with the gain score of students who learn OT content with CL model. Based on those findings it could be concluded that the NLL model applied to OT content could enhance KONDA of students in low and moderate SPK’s levels. Extra and more challenging didactical situation was needed for students in high SPK’s level to achieve the significant gain score.

Controlling attribute effect in linear regression

KAUST Repository

Calders, Toon; Karim, Asim A.; Kamiran, Faisal; Ali, Wasif Mohammad; Zhang, Xiangliang

2013-01-01

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.

Controlling attribute effect in linear regression

KAUST Repository

Calders, Toon

2013-12-01

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models. © 2013 IEEE.

Linear System Control Using Stochastic Learning Automata

Science.gov (United States)

Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

1998-01-01

This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

Science.gov (United States)

Lu, Zhao; Sun, Jing; Butts, Kenneth

2014-05-01

Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

A compensated multi-pole linear ion trap mercury frequency standard for ultra-stable timekeeping.

Science.gov (United States)

Burt, Eric A; Diener, William A; Tjoelker, Robert L

2008-12-01

The multi-pole linear ion trap frequency standard (LITS) being developed at the Jet Propulsion Laboratory (JPL) has demonstrated excellent short- and long-term stability. The technology has now demonstrated long-term field operation providing a new capability for timekeeping standards. Recently implemented enhancements have resulted in a record line Q of 5 x 10(12) for a room temperature microwave atomic transition and a short-term fractional frequency stability of 5 x 10(-14)/tau(1/2). A scheme for compensating the second order Doppler shift has led to a reduction of the combined sensitivity to the primary LITS systematic effects below 5 x 10(-17) fractional frequency. Initial comparisons to JPL's cesium fountain clock show a systematic floor of less than 2 x 10(-16). The compensated multi-pole LITS at JPL was operated continuously and unattended for a 9-mo period from October 2006 to July 2007. During that time it was used as the frequency reference for the JPL geodetic receiver known as JPLT, enabling comparisons to any clock used as a reference for an International GNSS Service (IGS) site. Comparisons with the laser-cooled primary frequency standards that reported to the Bureau International des Poids et Mesures (BIPM) over this period show a frequency deviation less than 2.7 x 10(-17)/day. In the capacity of a stand-alone ultra-stable flywheel, such a standard could be invaluable for long-term timekeeping applications in metrology labs while its methodology and robustness make it ideal for space applications as well.

Overview of ten-year operation of the superconducting linear accelerator at the Spallation Neutron Source

Science.gov (United States)

Kim, S.-H.; Afanador, R.; Barnhart, D. L.; Crofford, M.; Degraff, B. D.; Doleans, M.; Galambos, J.; Gold, S. W.; Howell, M. P.; Mammosser, J.; McMahan, C. J.; Neustadt, T. S.; Peters, C.; Saunders, J. W.; Strong, W. H.; Vandygriff, D. J.; Vandygriff, D. M.

2017-04-01

The Spallation Neutron Source (SNS) has acquired extensive operational experience of a pulsed proton superconducting linear accelerator (SCL) as a user facility. Numerous lessons have been learned in its first 10 years operation to achieve a stable and reliable operation of the SCL. In this paper, an overview of the SNS SCL design, qualification of superconducting radio frequency (SRF) cavities and ancillary subsystems, an overview of the SNS cryogenic system, the SCL operation including SCL output energy history and downtime statistics, performance stability of the SRF cavities, efforts for SRF cavity performance recovery and improvement at the SNS, and maintenance activities for cryomodules are introduced.

Overview of ten-year operation of the superconducting linear accelerator at the Spallation Neutron Source

International Nuclear Information System (INIS)

Kim, Sang-Ho; Afanador, Ralph; Barnhart, Debra L.; Crofford, Mark T.; Degraff, Brian D.

2017-01-01

The Spallation Neutron Source (SNS) has acquired extensive operational experience of a pulsed proton superconducting linear accelerator (SCL) as a user facility. Numerous lessons have been learned in its first 10 years operation to achieve a stable and reliable operation of the SCL. In this paper, an overview of the SNS SCL design, qualification of superconducting radio frequency (SRF) cavities and ancillary subsystems, an overview of the SNS cryogenic system, the SCL operation including SCL output energy history and downtime statistics, performance stability of the SRF cavities, efforts for SRF cavity performance recovery and improvement at the SNS, and maintenance activities for cryomodules are introduced.

Tempered stable distributions stochastic models for multiscale processes

CERN Document Server

Grabchak, Michael

2015-01-01

This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions.  A tempered stable distribution is one which takes a stable distribution and modifies its tails to make them lighter. The motivation for this class comes from the fact that infinite variance stable distributions appear to provide a good fit to data in a variety of situations, but the extremely heavy tails of these models are not realistic for most real world applications. The idea of using distributions that modify the tails of stable models to make them lighter seems to have originated in the influential paper of Mantegna and Stanley (1994). Since then, these distributions have been extended and generalized in a variety of ways. They have been applied to a wide variety of areas including mathematical finance, biostatistics,computer science, and physics.

Principles of linear algebra with Mathematica

CERN Document Server

Shiskowski, Kenneth M

2013-01-01

A hands-on introduction to the theoretical and computational aspects of linear algebra using Mathematica® Many topics in linear algebra are simple, yet computationally intensive, and computer algebra systems such as Mathematica® are essential not only for learning to apply the concepts to computationally challenging problems, but also for visualizing many of the geometric aspects within this field of study. Principles of Linear Algebra with Mathematica uniquely bridges the gap between beginning linear algebra and computational linear algebra that is often encountered in applied settings,

Stable isotope views on ecosystem function: challenging or challenged?

Science.gov (United States)

Resco, Víctor; Querejeta, José I; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A; Torres-Cañabate, Patricia; Valladares, Fernando

2010-06-23

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Ubeda, 18-22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes.

Relative null controllability of linear systems with multiple delays in ...

African Journals Online (AJOL)

varying multiple delays in state and control are developed. If the uncontrolled system is uniformly asymptotically stable, and if the linear system is controllable, then the linear system is null controllable. Journal of the Nigerian Association of ...

Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients.

Science.gov (United States)

Cangelosi, Davide; Blengio, Fabiola; Versteeg, Rogier; Eggert, Angelika; Garaventa, Alberto; Gambini, Claudio; Conte, Massimo; Eva, Alessandra; Muselli, Marco; Varesio, Luigi

2013-01-01

Neuroblastoma is the most common pediatric solid tumor. About fifty percent of high risk patients die despite treatment making the exploration of new and more effective strategies for improving stratification mandatory. Hypoxia is a condition of low oxygen tension occurring in poorly vascularized areas of the tumor associated with poor prognosis. We had previously defined a robust gene expression signature measuring the hypoxic component of neuroblastoma tumors (NB-hypo) which is a molecular risk factor. We wanted to develop a prognostic classifier of neuroblastoma patients' outcome blending existing knowledge on clinical and molecular risk factors with the prognostic NB-hypo signature. Furthermore, we were interested in classifiers outputting explicit rules that could be easily translated into the clinical setting. Shadow Clustering (SC) technique, which leads to final models called Logic Learning Machine (LLM), exhibits a good accuracy and promises to fulfill the aims of the work. We utilized this algorithm to classify NB-patients on the bases of the following risk factors: Age at diagnosis, INSS stage, MYCN amplification and NB-hypo. The algorithm generated explicit classification rules in good agreement with existing clinical knowledge. Through an iterative procedure we identified and removed from the dataset those examples which caused instability in the rules. This workflow generated a stable classifier very accurate in predicting good and poor outcome patients. The good performance of the classifier was validated in an independent dataset. NB-hypo was an important component of the rules with a strength similar to that of tumor staging. The novelty of our work is to identify stability, explicit rules and blending of molecular and clinical risk factors as the key features to generate classification rules for NB patients to be conveyed to the clinic and to be used to design new therapies. We derived, through LLM, a set of four stable rules identifying a new

Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patients

Science.gov (United States)

2013-01-01

Background Neuroblastoma is the most common pediatric solid tumor. About fifty percent of high risk patients die despite treatment making the exploration of new and more effective strategies for improving stratification mandatory. Hypoxia is a condition of low oxygen tension occurring in poorly vascularized areas of the tumor associated with poor prognosis. We had previously defined a robust gene expression signature measuring the hypoxic component of neuroblastoma tumors (NB-hypo) which is a molecular risk factor. We wanted to develop a prognostic classifier of neuroblastoma patients' outcome blending existing knowledge on clinical and molecular risk factors with the prognostic NB-hypo signature. Furthermore, we were interested in classifiers outputting explicit rules that could be easily translated into the clinical setting. Results Shadow Clustering (SC) technique, which leads to final models called Logic Learning Machine (LLM), exhibits a good accuracy and promises to fulfill the aims of the work. We utilized this algorithm to classify NB-patients on the bases of the following risk factors: Age at diagnosis, INSS stage, MYCN amplification and NB-hypo. The algorithm generated explicit classification rules in good agreement with existing clinical knowledge. Through an iterative procedure we identified and removed from the dataset those examples which caused instability in the rules. This workflow generated a stable classifier very accurate in predicting good and poor outcome patients. The good performance of the classifier was validated in an independent dataset. NB-hypo was an important component of the rules with a strength similar to that of tumor staging. Conclusions The novelty of our work is to identify stability, explicit rules and blending of molecular and clinical risk factors as the key features to generate classification rules for NB patients to be conveyed to the clinic and to be used to design new therapies. We derived, through LLM, a set of four

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

KAUST Repository

Jaleel, Hassan

2018-04-08

Stochastic stability is a popular solution concept for stochastic learning dynamics in games. However, a critical limitation of this solution concept is its inability to distinguish between different learning rules that lead to the same steady-state behavior. We address this limitation for the first time and develop a framework for the comparative analysis of stochastic learning dynamics with different update rules but same steady-state behavior. We present the framework in the context of two learning dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through an example setup of sensor coverage game that for each of these dynamics, the paths to stochastically stable states exhibit distinctive behaviors. Therefore, we propose multiple criteria to analyze and quantify the differences in the short and medium run behavior of stochastic learning dynamics. We derive and compare upper bounds on the expected hitting time to the set of Nash equilibria for both LLL and ML. For the medium to long-run behavior, we identify a set of tools from the theory of perturbed Markov chains that result in a hierarchical decomposition of the state space into collections of states called cycles. We compare LLL and ML based on the proposed criteria and develop invaluable insights into the comparative behavior of the two dynamics.

Stable Structures for Distributed Applications

OpenAIRE

Eugen DUMITRASCU; Ion IVAN

2008-01-01

For distributed applications, we define the linear, tree and graph structure types with different variants and modalities to aggregate them. The distributed applications have assigned structures that through their characteristics influence the costs of stages for developing cycle and the costs for exploitation, transferred to each user. We also present the quality characteristics of a structure for a stable application, which is focused on stability characteristic. For that characteristic we ...

Stable isotope views on ecosystem function: challenging or challenged?

Science.gov (United States)

Resco, Víctor; Querejeta, José I.; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C.; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A.; Torres-Cañabate, Patricia; Valladares, Fernando

2010-01-01

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Úbeda, 18–22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes. PMID:20015858

Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease

Directory of Open Access Journals (Sweden)

Xiaoli Liu

2018-01-01

Full Text Available Alzheimer’s disease (AD has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer’s disease. Recently, the multitask learning (MTL methods with sparsity-inducing norm (e.g., l2,1-norm have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures. However, these previous works formulate the prediction tasks as a linear regression problem. The major limitation is that they assumed a linear relationship between the MRI features and the cognitive outcomes. Some multikernel-based MTL methods have been proposed and shown better generalization ability due to the nonlinear advantage. We quantify the power of existing linear and nonlinear MTL methods by evaluating their performance on cognitive score prediction of Alzheimer’s disease. Moreover, we extend the traditional l2,1-norm to a more general lql1-norm (q≥1. Experiments on the Alzheimer’s Disease Neuroimaging Initiative database showed that the nonlinear l2,1lq-MKMTL method not only achieved better prediction performance than the state-of-the-art competitive methods but also effectively fused the multimodality data.

Intelligent measurement and compensation of linear motor force ripple: a projection-based learning approach in the presence of noise

Science.gov (United States)

Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin

2018-06-01

Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.

An Inquiry-Based Linear Algebra Class

Science.gov (United States)

Wang, Haohao; Posey, Lisa

2011-01-01

Linear algebra is a standard undergraduate mathematics course. This paper presents an overview of the design and implementation of an inquiry-based teaching material for the linear algebra course which emphasizes discovery learning, analytical thinking and individual creativity. The inquiry-based teaching material is designed to fit the needs of a…

Biodosimetry for medical diagnostic X-ray workers using stable chromosome aberration

International Nuclear Information System (INIS)

Wang Zhiquan; Liu Xuping; Li Jin

1996-01-01

The stable chromosome aberrations of medical diagnostic X-ray workers were analyzed using G-banding and their accumulative doses were evaluated. The results showed that the frequencies of reciprocal translocation, stable aberration and total aberration among the 4417 metaphase spread from 44 cases of medical diagnostic X-ray workers were distinctly higher than control values (P<0.05∼0.005). The stable aberration predominated strikingly in total aberration and reciprocal translocation was 57% in the stable aberrations. The medical diagnostic X-ray workers were divided into 3 groups according to calendar year of entry. The data showed that the frequencies of total aberration, stable aberration and reciprocal translocation increased with working years, especially in two groups who started working before 1970, there are statistically significant differences between the calendar year of entry before 1960 and 1960∼1969 in X-ray workers and control group. According to the equation recommended by Straume, linear coefficient (α) in linear quadratic model recommended by Schmid and the transformation coefficient by Lucas, the accumulative doses calculated are 0.58, 0.37 and 0.07 Gy for calendar year of entry before 1960, 1960∼1969 and after 1970 in X-ray workers, respectively

Feedback systems for linear colliders

CERN Document Server

Hendrickson, L; Himel, Thomas M; Minty, Michiko G; Phinney, N; Raimondi, Pantaleo; Raubenheimer, T O; Shoaee, H; Tenenbaum, P G

1999-01-01

Feedback systems are essential for stable operation of a linear collider, providing a cost-effective method for relaxing tight tolerances. In the Stanford Linear Collider (SLC), feedback controls beam parameters such as trajectory, energy, and intensity throughout the accelerator. A novel dithering optimization system which adjusts final focus parameters to maximize luminosity contributed to achieving record performance in the 1997-98 run. Performance limitations of the steering feedback have been investigated, and improvements have been made. For the Next Linear Collider (NLC), extensive feedback systems are planned as an intregal part of the design. Feedback requiremetns for JLC (the Japanese Linear Collider) are essentially identical to NLC; some of the TESLA requirements are similar but there are significant differences. For NLC, algorithms which incorporate improvements upon the SLC implementation are being prototyped. Specialized systems for the damping rings, rf and interaction point will operate at hi...

Constructive Learning in Undergraduate Linear Algebra

Science.gov (United States)

Chandler, Farrah Jackson; Taylor, Dewey T.

2008-01-01

In this article we describe a project that we used in our undergraduate linear algebra courses to help our students successfully master fundamental concepts and definitions and generate interest in the course. We describe our philosophy and discuss the projects overall success.

Handelman's hierarchy for the maximum stable set problem

NARCIS (Netherlands)

Laurent, M.; Sun, Z.

2014-01-01

The maximum stable set problem is a well-known NP-hard problem in combinatorial optimization, which can be formulated as the maximization of a quadratic square-free polynomial over the (Boolean) hypercube. We investigate a hierarchy of linear programming relaxations for this problem, based on a

Fourier imaging of non-linear structure formation

Energy Technology Data Exchange (ETDEWEB)

Brandbyge, Jacob; Hannestad, Steen, E-mail: jacobb@phys.au.dk, E-mail: sth@phys.au.dk [Department of Physics and Astronomy, University of Aarhus, Ny Munkegade 120, DK-8000 Aarhus C (Denmark)

2017-04-01

We perform a Fourier space decomposition of the dynamics of non-linear cosmological structure formation in ΛCDM models. From N -body simulations involving only cold dark matter we calculate 3-dimensional non-linear density, velocity divergence and vorticity Fourier realizations, and use these to calculate the fully non-linear mode coupling integrals in the corresponding fluid equations. Our approach allows for a reconstruction of the amount of mode coupling between any two wavenumbers as a function of redshift. With our Fourier decomposition method we identify the transfer of power from larger to smaller scales, the stable clustering regime, the scale where vorticity becomes important, and the suppression of the non-linear divergence power spectrum as compared to linear theory. Our results can be used to improve and calibrate semi-analytical structure formation models.

Fourier imaging of non-linear structure formation

International Nuclear Information System (INIS)

Brandbyge, Jacob; Hannestad, Steen

2017-01-01

We perform a Fourier space decomposition of the dynamics of non-linear cosmological structure formation in ΛCDM models. From N -body simulations involving only cold dark matter we calculate 3-dimensional non-linear density, velocity divergence and vorticity Fourier realizations, and use these to calculate the fully non-linear mode coupling integrals in the corresponding fluid equations. Our approach allows for a reconstruction of the amount of mode coupling between any two wavenumbers as a function of redshift. With our Fourier decomposition method we identify the transfer of power from larger to smaller scales, the stable clustering regime, the scale where vorticity becomes important, and the suppression of the non-linear divergence power spectrum as compared to linear theory. Our results can be used to improve and calibrate semi-analytical structure formation models.

Wideband quin-stable energy harvesting via combined nonlinearity

Directory of Open Access Journals (Sweden)

Chen Wang

2017-04-01

Full Text Available In this work, we propose a wideband quintuple-well potential piezoelectric-based vibration energy harvester using a combined nonlinearity: the magnetic nonlinearity induced by magnetic force and the piecewise-linearity produced by mechanical impact. With extra stable states compared to other multi-stable harvesters, the quin-stable harvester can distribute its potential energy more uniformly, which provides shallower potential wells and results in lower excitation threshold for interwell motion. The mathematical model of this quin-stable harvester is derived and its equivalent piecewise-nonlinear restoring force is measured in the experiment and identified as piecewise polynomials. Numerical simulations and experimental verifications are performed in different levels of sinusoid excitation ranging from 1 to 25 Hz. The results demonstrate that, with lower potential barriers compared with tri-stable counterpart, the quin-stable arrangement can escape potential wells more easily for doing high-energy interwell motion over a wider band of frequencies. Moreover, by utilizing the mechanical stoppers, this harvester can produce significant output voltage under small tip deflections, which results in a high power density and is especially suitable for a compact MEMS approach.

An Instructional Note on Linear Programming--A Pedagogically Sound Approach.

Science.gov (United States)

Mitchell, Richard

1998-01-01

Discusses the place of linear programming in college curricula and the advantages of using linear-programming software. Lists important characteristics of computer software used in linear programming for more effective teaching and learning. (ASK)

A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

Science.gov (United States)

Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

2016-04-01

Existing evidence suggests that ambient ultrafine particles (UFPs) (regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Towards a new classification of stable phase schizophrenia into major and simple neuro-cognitive psychosis: Results of unsupervised machine learning analysis.

Science.gov (United States)

Kanchanatawan, Buranee; Sriswasdi, Sira; Thika, Supaksorn; Stoyanov, Drozdstoy; Sirivichayakul, Sunee; Carvalho, André F; Geffard, Michel; Maes, Michael

2018-05-23

Deficit schizophrenia, as defined by the Schedule for Deficit Syndrome, may represent a distinct diagnostic class defined by neurocognitive impairments coupled with changes in IgA/IgM responses to tryptophan catabolites (TRYCATs). Adequate classifications should be based on supervised and unsupervised learning rather than on consensus criteria. This study used machine learning as means to provide a more accurate classification of patients with stable phase schizophrenia. We found that using negative symptoms as discriminatory variables, schizophrenia patients may be divided into two distinct classes modelled by (A) impairments in IgA/IgM responses to noxious and generally more protective tryptophan catabolites, (B) impairments in episodic and semantic memory, paired associative learning and false memory creation, and (C) psychotic, excitation, hostility, mannerism, negative, and affective symptoms. The first cluster shows increased negative, psychotic, excitation, hostility, mannerism, depression and anxiety symptoms, and more neuroimmune and cognitive disorders and is therefore called "major neurocognitive psychosis" (MNP). The second cluster, called "simple neurocognitive psychosis" (SNP) is discriminated from normal controls by the same features although the impairments are less well developed than in MNP. The latter is additionally externally validated by lowered quality of life, body mass (reflecting a leptosome body type), and education (reflecting lower cognitive reserve). Previous distinctions including "type 1" (positive)/"type 2" (negative) and DSM-IV-TR (eg, paranoid) schizophrenia could not be validated using machine learning techniques. Previous names of the illness, including schizophrenia, are not very adequate because they do not describe the features of the illness, namely, interrelated neuroimmune, cognitive, and clinical features. Stable-phase schizophrenia consists of 2 relevant qualitatively distinct categories or nosological entities with SNP

Student Learning of Basis, Span and Linear Independence in Linear Algebra

Science.gov (United States)

Stewart, Sepideh; Thomas, Michael O. J.

2010-01-01

One of the earlier, more challenging concepts in linear algebra at university is that of basis. Students are often taught procedurally how to find a basis for a subspace using matrix manipulation, but may struggle with understanding the construct of basis, making further progress harder. We believe one reason for this is because students have…

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-01-15

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

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

International Nuclear Information System (INIS)

Kabashima, Y

2008-01-01

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

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

Science.gov (United States)

Kabashima, Y.

2008-01-01

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

Global analysis of all linear stable settings of a storage ring lattice

Directory of Open Access Journals (Sweden)

David S Robin

2008-02-01

Full Text Available The traditional process of designing and tuning the magnetic lattice of a particle storage ring lattice to produce certain desired properties is not straightforward. Often solutions are found through trial and error and it is not clear that the solutions are close to optimal. This can be a very unsatisfying process. In this paper we take a step back and look at the general stability limits of the lattice. We employ a technique we call GLASS (GLobal scan of All Stable Settings that allows us to rapidly scan and find all possible stable modes and then characterize their associated properties. In this paper we illustrate how the GLASS technique gives a global and comprehensive vision of the capabilities of the lattice. In a sense, GLASS functions as a lattice observatory clearly displaying all possibilities. The power of the GLASS technique is that it is fast and comprehensive. There is no fitting involved. It gives the lattice designer clear guidance as to where to look for interesting operational points. We demonstrate the technique by applying it to two existing storage ring lattices—the triple bend achromat of the Advanced Light Source and the double bend achromat of CAMD. We show that, using GLASS, we have uncovered many interesting and in some cases previously unknown stability regions.

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

Science.gov (United States)

Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

2016-06-02

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Non-linearity consideration when analyzing reactor noise statistical characteristics. [BWR

Energy Technology Data Exchange (ETDEWEB)

Kebadze, B V; Adamovski, L A

1975-06-01

Statistical characteristics of boiling water reactor noise in the vicinity of stability threshold are studied. The reactor is considered as a non-linear system affected by random perturbations. To solve a non-linear problem the principle of statistical linearization is used. It is shown that the halfwidth of resonance peak in neutron power noise spectrum density as well as the reciprocal of noise dispersion, which are used in predicting a stable operation theshold, are different from zero both within and beyond the stability boundary the determination of which was based on linear criteria.

A stable wavelength-tunable single frequency and single polarization linear cavity erbium-doped fiber laser

International Nuclear Information System (INIS)

Feng, T; Yan, F P; Li, Q; Peng, W J; Tan, S Y; Feng, S C; Wen, X D; Liu, P

2013-01-01

We report the configuration and operation of a wavelength-tunable single frequency and single polarization erbium-doped fiber laser (EDFL) with a stable and high optical signal to noise ratio (OSNR) laser output. A narrow-band fiber Bragg grating (NBFBG), a FBG-based Fabry–Perot (FP) filter, a polarization controller (PC) and an unpumped erbium-doped fiber (EDF) as a saturable absorber (SA) are employed to realize stable single frequency lasing operation. An all-fiber polarizer (AFP) is introduced to suppress mode hopping and ensure the single polarization mode operation. By adjusting the length of the NBFBG using a stress adjustment module (SAM), four stable single frequency and single polarization laser outputs at wavelengths of 1544.946, 1545.038, 1545.118 and 1545.182 nm are obtained. At room temperature, performance with an OSNR of larger than 60 dB, power fluctuation of less than 0.04 dB, wavelength variation of less than 0.01 nm for about 5 h measurement, and degree of polarization (DOP) of close to 100% has been experimentally demonstrated for the fiber laser operating at these four wavelengths. (paper)

Spatial-Frequency Azimuthally Stable Cartography of Biological Polycrystalline Networks

Directory of Open Access Journals (Sweden)

V. A. Ushenko

2013-01-01

Full Text Available A new azimuthally stable polarimetric technique processing microscopic images of optically anisotropic structures of biological tissues histological sections is proposed. It has been used as a generalized model of phase anisotropy definition of biological tissues by using superposition of Mueller matrices of linear birefringence and optical activity. The matrix element M44 has been chosen as the main information parameter, whose value is independent of the rotation angle of both sample and probing beam polarization plane. For the first time, the technique of concerted spatial-frequency filtration has been used in order to separate the manifestation of linear birefringence and optical activity. Thereupon, the method of azimuthally stable spatial-frequency cartography of biological tissues histological sections has been elaborated. As the analyzing tool, complex statistic, correlation, and fractal analysis of coordinate distributions of M44 element has been performed. The possibility of using the biopsy of the uterine wall tissue in order to differentiate benign (fibromyoma and malignant (adenocarcinoma conditions has been estimated.

Direct search for pair production of heavy stable charged particles in Z decays

International Nuclear Information System (INIS)

Soderstrom, E.; McKenna, J.A.; Abrams, G.S.; Adolphsen, C.E.; Averill, D.; Ballam, J.; Barish, B.C.; Barklow, T.; Barnett, B.A.; Bartelt, J.; Bethke, S.; Blockus, D.; Bonvicini, G.; Boyarski, A.; Brabson, B.; Breakstone, A.; Bulos, F.; Burchat, P.R.; Burke, D.L.; Cence, R.J.; Chapman, J.; Chmeissani, M.; Cords, D.; Coupal, D.P.; Dauncey, P.; DeStaebler, H.C.; Dorfan, D.E.; Dorfan, J.M.; Drewer, D.C.; Elia, R.; Feldman, G.J.; Fernandes, D.; Field, R.C.; Ford, W.T.; Fordham, C.; Frey, R.; Fujino, D.; Gan, K.K.; Gero, E.; Gidal, G.; Glanzman, T.; Goldhaber, G.; Gomez Cadenas, J.J.; Gratta, G.; Grindhammer, G.; Grosse-Wiesmann, P.; Hanson, G.; Harr, R.; Harral, B.; Harris, F.A.; Hawkes, C.M.; Hayes, K.; Hearty, C.; Heusch, C.A.; Hildreth, M.D.; Himel, T.; Hinshaw, D.A.; Hong, S.J.; Hutchinson, D.; Hylen, J.; Innes, W.R.; Jacobsen, R.G.; Jaros, J.A.; Jung, C.K.; Kadyk, J.A.; Kent, J.; King, M.; Koetke, D.S.; Komamiya, S.; Koska, W.; Kowalski, L.A.; Kozanecki, W.; Kral, J.F.; Kuhlen, M.; Labarga, L.; Lankford, A.J.; Larsen, R.R.; Le Diberder, F.; Levi, M.E.; Litke, A.M.; Lou, X.C.; Lueth, V.; Matthews, J.A.J.; Mattison, T.; Milliken, B.D.; Moffeit, K.C.; Munger, C.T.; Murray, W.N.; Nash, J.; Ogren, H.; O'Shaughnessy, K.F.; Parker, S.I.; Peck, C.; Perl, M.L.; Petradza, M.; Pitthan, R.; Porter, F.C.; Rankin, P.; Riles, K.; Rouse, F.R.; Rust, D.R.; Sadrozinski, H.F.W.; Schaad, M.W.; Schumm, B.A.; Seiden, A.; Smith, J.G.; Snyder, A.; Stoker, D.P.; Stroynowski, R.; Swartz, M.; Thun, R.; Trilling, G.H.; Van Kooten, R.; Voruganti, P.; Wagner, S.R.; Watson, S.; Weber, P.; Weinstein, A.J.; Weir, A.J.; Wicklund, E.; Woods, M.; Wu, D.Y.; Yurko, M.; Zaccardelli, C.; von Zanthie, C.

1990-01-01

A search for pair production of stable charged particles from Z decay has been performed with the Mark II detector at the SLAC Linear Collider. Particle masses are determined from momentum, ionization energy loss, and time-of-flight measurements. A limit excluding pair production of stable fourth-generation charged leptons and stable mirror fermions with masses between the muon mass and 36.3 GeV/c 2 is set at the 95% confidence level. Pair production of stable supersymmetric scalar leptons with masses between the muon mass and 32.6 GeV/c 2 is also excluded

Perturbed asymptotically linear problems

OpenAIRE

Bartolo, R.; Candela, A. M.; Salvatore, A.

2012-01-01

The aim of this paper is investigating the existence of solutions of some semilinear elliptic problems on open bounded domains when the nonlinearity is subcritical and asymptotically linear at infinity and there is a perturbation term which is just continuous. Also in the case when the problem has not a variational structure, suitable procedures and estimates allow us to prove that the number of distinct crtitical levels of the functional associated to the unperturbed problem is "stable" unde...

The effect of incremental changes in phonotactic probability and neighborhood density on word learning by preschool children

Science.gov (United States)

Storkel, Holly L.; Bontempo, Daniel E.; Aschenbrenner, Andrew J.; Maekawa, Junko; Lee, Su-Yeon

2013-01-01

Purpose Phonotactic probability or neighborhood density have predominately been defined using gross distinctions (i.e., low vs. high). The current studies examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning. Method The full range of probability or density was examined by sampling five nonwords from each of four quartiles. Three- and 5-year-old children received training on nonword-nonobject pairs. Learning was measured in a picture-naming task immediately following training and 1-week after training. Results were analyzed using multi-level modeling. Results A linear spline model best captured nonlinearities in phonotactic probability. Specifically word learning improved as probability increased in the lowest quartile, worsened as probability increased in the midlow quartile, and then remained stable and poor in the two highest quartiles. An ordinary linear model sufficiently described neighborhood density. Here, word learning improved as density increased across all quartiles. Conclusion Given these different patterns, phonotactic probability and neighborhood density appear to influence different word learning processes. Specifically, phonotactic probability may affect recognition that a sound sequence is an acceptable word in the language and is a novel word for the child, whereas neighborhood density may influence creation of a new representation in long-term memory. PMID:23882005

Measurement of organic carbon stable isotope composition of different soil types by EA-IRMS system

International Nuclear Information System (INIS)

Qi Biao; Ding Lingling; Cui Jiehua; Wang Yanhong

2009-01-01

Element analyzer-isotope ratio mass spectrometers (EA-IRMS) is a rapid and precise method for measuring stable carbon isotope. Pure CO 2 reference gas was calibrated via international standard-Urea, and the δ 13 C us PDB value of pure CO 2 is (-29.523 ± 0.0181)%. Stability and linearity of the EA-IRMS system, precision of δ 13 C measurement for samples were tested through experimental comparison. Moreover, determination method of organic carbon stable isotope in soil was based on the system. The EA-IRMS system had well linearity when ion intensity ranged from 1.0 to 7.0V, and it excelled the total linearity when the ion intensity was from 1.5 to 5.0V, and the accurate result of δ 13 C for sample analysis could be obtained with precision of 0.015%. If carbon content in sample is more than 5μg, the requirement for analyzing accurate result of δ 13 C could be achieved. The organic carbon stable isotope was measured in 18 different types soil samples, the average natural abundance of 13 C was 1.082%, and the organic carbon stable isotope composition was significantly different among different type soils. (authors)

Structure Learning in Stochastic Non-linear Dynamical Systems

Science.gov (United States)

Morris, R. D.; Smelyanskiy, V. N.; Luchinsky, D. G.

2005-12-01

A great many systems can be modeled in the non-linear dynamical systems framework, as x˙ = f(x) + ξ(t), where f(x) is the potential function for the system, and ξ(t) is the driving noise. Modeling the potential using a set of basis functions, we derive the posterior for the basis coefficients. A more challenging problem is to determine the set of basis functions that are required to model a particular system. We show that using the Bayesian Information Criteria (BIC) to rank models, and the beam search technique, that we can accurately determine the structure of simple non-linear dynamical system models, and the structure of the coupling between non-linear dynamical systems where the individual systems are known. This last case has important ecological applications, for example in predator-prey systems, where the very structure of the coupling between predator-prey pairs can have great ecological significance.

On the Linear Stability of the Fifth-Order WENO Discretization

KAUST Repository

Motamed, Mohammad

2010-10-03

We study the linear stability of the fifth-order Weighted Essentially Non-Oscillatory spatial discretization (WENO5) combined with explicit time stepping applied to the one-dimensional advection equation. We show that it is not necessary for the stability domain of the time integrator to include a part of the imaginary axis. In particular, we show that the combination of WENO5 with either the forward Euler method or a two-stage, second-order Runge-Kutta method is linearly stable provided very small time step-sizes are taken. We also consider fifth-order multistep time discretizations whose stability domains do not include the imaginary axis. These are found to be linearly stable with moderate time steps when combined with WENO5. In particular, the fifth-order extrapolated BDF scheme gave superior results in practice to high-order Runge-Kutta methods whose stability domain includes the imaginary axis. Numerical tests are presented which confirm the analysis. © Springer Science+Business Media, LLC 2010.

Input-to-State Stabilizing MPC for Neutrally Stable Linear Systems subject to Input Constraints

NARCIS (Netherlands)

Kim, Jung-Su; Yoon, Tae-Woong; Jadbabaie, Ali; Persis, Claudio De

2004-01-01

MPC(Model Predictive Control) is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed

Differentiability of Palmer's linearization Theorem and converse result for density functions

OpenAIRE

Castañeda, Alvaro; Robledo, Gonzalo

2014-01-01

We study differentiability properties in a particular case of the Palmer's linearization Theorem, which states the existence of an homeomorphism $H$ between the solutions of a linear ODE system having exponential dichotomy and a quasilinear system. Indeed, if the linear system is uniformly asymptotically stable, sufficient conditions ensuring that $H$ is a $C^{2}$ preserving orientation diffeomorphism are given. As an application, we generalize a converse result of density functions for a non...

Toward Practical Secure Stable Matching

Directory of Open Access Journals (Sweden)

Riazi M. Sadegh

2017-01-01

Full Text Available The Stable Matching (SM algorithm has been deployed in many real-world scenarios including the National Residency Matching Program (NRMP and financial applications such as matching of suppliers and consumers in capital markets. Since these applications typically involve highly sensitive information such as the underlying preference lists, their current implementations rely on trusted third parties. This paper introduces the first provably secure and scalable implementation of SM based on Yao’s garbled circuit protocol and Oblivious RAM (ORAM. Our scheme can securely compute a stable match for 8k pairs four orders of magnitude faster than the previously best known method. We achieve this by introducing a compact and efficient sub-linear size circuit. We even further decrease the computation cost by three orders of magnitude by proposing a novel technique to avoid unnecessary iterations in the SM algorithm. We evaluate our implementation for several problem sizes and plan to publish it as open-source.

Robust chaos synchronization using input-to-state stable control

Indian Academy of Sciences (India)

In this paper, we propose a new input-to-state stable (ISS) synchronization method for a general class of chaotic systems with disturbances. Based on Lyapunov theory and linear matrix inequality (LMI) approach, for the first time, the ISS synchronization controller is presented not only to guarantee the asymptotic ...

Supervised Learning for Dynamical System Learning.

Science.gov (United States)

Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

2015-01-01

Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

On the classification of the spectrally stable standing waves of the Hartree problem

Science.gov (United States)

Georgiev, Vladimir; Stefanov, Atanas

2018-05-01

We consider the fractional Hartree model, with general power non-linearity and arbitrary spatial dimension. We construct variationally the "normalized" solutions for the corresponding Choquard-Pekar model-in particular a number of key properties, like smoothness and bell-shapedness are established. As a consequence of the construction, we show that these solitons are spectrally stable as solutions to the time-dependent Hartree model. In addition, we analyze the spectral stability of the Moroz-Van Schaftingen solitons of the classical Hartree problem, in any dimensions and power non-linearity. A full classification is obtained, the main conclusion of which is that only and exactly the "normalized" solutions (which exist only in a portion of the range) are spectrally stable.

Breaking of ensembles of linear and nonlinear oscillators

International Nuclear Information System (INIS)

Buts, V.A.

2016-01-01

Some results concerning the study of the dynamics of ensembles of linear and nonlinear oscillators are stated. It is shown that, in general, a stable ensemble of linear oscillator has a limited number of oscillators. This number has been defined for some simple models. It is shown that the features of the dynamics of linear oscillators can be used for conversion of the low-frequency energy oscillations into high frequency oscillations. The dynamics of coupled nonlinear oscillators in most cases is chaotic. For such a case, it is shown that the statistical characteristics (moments) of chaotic motion can significantly reduce potential barriers that keep the particles in the capture region

Introduction to computational linear algebra

CERN Document Server

Nassif, Nabil; Erhel, Jocelyne

2015-01-01

Introduction to Computational Linear Algebra introduces the reader with a background in basic mathematics and computer programming to the fundamentals of dense and sparse matrix computations with illustrating examples. The textbook is a synthesis of conceptual and practical topics in ""Matrix Computations."" The book's learning outcomes are twofold: to understand state-of-the-art computational tools to solve matrix computations problems (BLAS primitives, MATLAB® programming) as well as essential mathematical concepts needed to master the topics of numerical linear algebra. It is suitable for s

Linearly decoupled energy-stable numerical methods for multi-component two-phase compressible flow

KAUST Repository

Kou, Jisheng; Sun, Shuyu; Wang, Xiuhua

2017-01-01

involved in the discrete momentum equation to ensure a consistency relationship with the mass balance equations. Moreover, we propose a component-wise SAV approach for a multi-component fluid, which requires solving a sequence of linear, separate mass

SUPPORTING STUDENTS’ UNDERSTANDING OF LINEAR EQUATIONS WITH ONE VARIABLE USING ALGEBRA TILES

Directory of Open Access Journals (Sweden)

Sari Saraswati

2016-01-01

Full Text Available This research aimed to describe how algebra tiles can support students’ understanding of linear equations with one variable. This article is a part of a larger research on learning design of linear equations with one variable using algebra tiles combined with balancing method. Therefore, it will merely discuss one activity focused on how students use the algebra tiles to find a method to solve linear equations with one variable. Design research was used as an approach in this study. It consists of three phases, namely preliminary design, teaching experiment and retrospective analysis. Video registrations, students’ written works, pre-test, post-test, field notes, and interview are technic to collect data. The data were analyzed by comparing the hypothetical learning trajectory (HLT and the actual learning process. The result shows that algebra tiles could supports students’ understanding to find the formal solution of linear equation with one variable.

A stable high-order perturbation of surfaces method for numerical simulation of diffraction problems in triply layered media

Energy Technology Data Exchange (ETDEWEB)

Hong, Youngjoon, E-mail: hongy@uic.edu; Nicholls, David P., E-mail: davidn@uic.edu

2017-02-01

The accurate numerical simulation of linear waves interacting with periodic layered media is a crucial capability in engineering applications. In this contribution we study the stable and high-order accurate numerical simulation of the interaction of linear, time-harmonic waves with a periodic, triply layered medium with irregular interfaces. In contrast with volumetric approaches, High-Order Perturbation of Surfaces (HOPS) algorithms are inexpensive interfacial methods which rapidly and recursively estimate scattering returns by perturbation of the interface shape. In comparison with Boundary Integral/Element Methods, the stable HOPS algorithm we describe here does not require specialized quadrature rules, periodization strategies, or the solution of dense non-symmetric positive definite linear systems. In addition, the algorithm is provably stable as opposed to other classical HOPS approaches. With numerical experiments we show the remarkable efficiency, fidelity, and accuracy one can achieve with an implementation of this algorithm.

Sparse Linear Identifiable Multivariate Modeling

DEFF Research Database (Denmark)

Henao, Ricardo; Winther, Ole

2011-01-01

and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...

Emittance control in linear colliders

International Nuclear Information System (INIS)

Ruth, R.D.

1991-01-01

Before completing a realistic design of a next-generation linear collider, the authors must first learn the lessons taught by the first generation, the SLC. Given that, they must make designs fault tolerant by including correction and compensation in the basic design. They must also try to eliminate these faults by improved alignment and stability of components. When these two efforts cross, they have a realistic design. The techniques of generation and control of emittance reviewed here provide a foundation for a design which can obtain the necessary luminosity in a next-generation linear collider

Difficulties faced by eighth grade students in the learning of linear equation problems at a high school in Heredia

Directory of Open Access Journals (Sweden)

Gilberto Chavarría Arroyo

2014-06-01

Full Text Available The current article presents the results of a study that aimed to analyze the difficulties faced by eighth grade students when learning to solve algebraic problems based on linear equations with one unknown variable. The participants were learners with low average performance in mathematics at a high school in Heredia. The research followed a naturalistic paradigm and the case study method with a qualitative approach. Different techniques like class observations, questionnaires to students, non-structured interviews to teachers and interviews to the learners were applied. The research helped to identify the main causes of difficulty when learning to solve algebraic problems. Some of the causes that were identified are affective aspects, lack of previous knowledge, poor relational understanding, fatigue, diversion, reading deficiencies and misunderstanding of terminology.

Stochastic systems driven by alpha-stable noises

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager; Ditlevsen, P.

1998-01-01

with observed data. In particular the tailsof the observed response distributions may even for linear systems be more fat than the tails obtained for Gaussianwhite noise input. Also the excitation may show jumps that cannot be modeled by Gaussian white noise. The paper supports the possibility of using...... the larger class of so-calledalpha-stable white noises to provide a better fit. A geophysical application concerning ice age climate variations is described....

Distributed Extreme Learning Machine for Nonlinear Learning over Network

Directory of Open Access Journals (Sweden)

Songyan Huang

2015-02-01

Full Text Available Distributed data collection and analysis over a network are ubiquitous, especially over a wireless sensor network (WSN. To our knowledge, the data model used in most of the distributed algorithms is linear. However, in real applications, the linearity of systems is not always guaranteed. In nonlinear cases, the single hidden layer feedforward neural network (SLFN with radial basis function (RBF hidden neurons has the ability to approximate any continuous functions and, thus, may be used as the nonlinear learning system. However, confined by the communication cost, using the distributed version of the conventional algorithms to train the neural network directly is usually prohibited. Fortunately, based on the theorems provided in the extreme learning machine (ELM literature, we only need to compute the output weights of the SLFN. Computing the output weights itself is a linear learning problem, although the input-output mapping of the overall SLFN is still nonlinear. Using the distributed algorithmto cooperatively compute the output weights of the SLFN, we obtain a distributed extreme learning machine (dELM for nonlinear learning in this paper. This dELM is applied to the regression problem and classification problem to demonstrate its effectiveness and advantages.

Entropy Stable Wall Boundary Conditions for the Compressible Navier-Stokes Equations

Science.gov (United States)

Parsani, Matteo; Carpenter, Mark H.; Nielsen, Eric J.

2014-01-01

Non-linear entropy stability and a summation-by-parts framework are used to derive entropy stable wall boundary conditions for the compressible Navier-Stokes equations. A semi-discrete entropy estimate for the entire domain is achieved when the new boundary conditions are coupled with an entropy stable discrete interior operator. The data at the boundary are weakly imposed using a penalty flux approach and a simultaneous-approximation-term penalty technique. Although discontinuous spectral collocation operators are used herein for the purpose of demonstrating their robustness and efficacy, the new boundary conditions are compatible with any diagonal norm summation-by-parts spatial operator, including finite element, finite volume, finite difference, discontinuous Galerkin, and flux reconstruction schemes. The proposed boundary treatment is tested for three-dimensional subsonic and supersonic flows. The numerical computations corroborate the non-linear stability (entropy stability) and accuracy of the boundary conditions.

Multipole surface solitons supported by the interface between linear media and nonlocal nonlinear media

International Nuclear Information System (INIS)

Shi, Zhiwei; Li, Huagang; Guo, Qi

2012-01-01

We address multipole surface solitons occurring at the interface between a linear medium and a nonlocal nonlinear medium. We show the impact of nonlocality, the propagation constant, and the linear index difference of two media on the properties of the surface solitons. We find that there exist a threshold value of the degree of the nonlocality at the same linear index difference of two media, only when the degree of the nonlocality goes beyond the value, the multipole surface solitons can be stable. -- Highlights: ► We show the impact of nonlocality and the linear index difference of two media on the properties of the surface solitons. ► For the surface solitons, only when the degree of the nonlocality goes beyond a threshold value, they can be stable. ► The number of poles and the index difference of two media can all influence the threshold value.

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

Science.gov (United States)

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

Linear Plasma Oscillation Described by Superposition of Normal Modes

DEFF Research Database (Denmark)

Pécseli, Hans

1974-01-01

The existence of steady‐state solutions to the linearized ion and electron Vlasov equation is demonstrated for longitudinal waves in an initially stable plasma. The evolution of an arbitrary initial perturbation can be described by superposition of these solutions. Some common approximations...

Stability of numerical method for semi-linear stochastic pantograph differential equations

Directory of Open Access Journals (Sweden)

Yu Zhang

2016-01-01

Full Text Available Abstract As a particular expression of stochastic delay differential equations, stochastic pantograph differential equations have been widely used in nonlinear dynamics, quantum mechanics, and electrodynamics. In this paper, we mainly study the stability of analytical solutions and numerical solutions of semi-linear stochastic pantograph differential equations. Some suitable conditions for the mean-square stability of an analytical solution are obtained. Then we proved the general mean-square stability of the exponential Euler method for a numerical solution of semi-linear stochastic pantograph differential equations, that is, if an analytical solution is stable, then the exponential Euler method applied to the system is mean-square stable for arbitrary step-size h > 0 $h>0$ . Numerical examples further illustrate the obtained theoretical results.

Stable Kernel Representations and the Youla Parameterization for Nonlinear Systems

NARCIS (Netherlands)

Paice, A.D.B.; Schaft, A.J. van der

1994-01-01

In this paper a general approach is taken to yield a characterization of the class of stable plant controller pairs, which is a generalization of the Youla parameterization for linear systems. This is based on the idea of representing the input-output pairs of the plant and controller as elements of

The Effects of the Concrete-Representational-Abstract Integration Strategy on the Ability of Students with Learning Disabilities to Multiply Linear Expressions within Area Problems

Science.gov (United States)

Strickland, Tricia K.; Maccini, Paula

2013-01-01

We examined the effects of the Concrete-Representational-Abstract Integration strategy on the ability of secondary students with learning disabilities to multiply linear algebraic expressions embedded within contextualized area problems. A multiple-probe design across three participants was used. Results indicated that the integration of the…

Integration of differential equations by the pseudo-linear (PL) approximation

International Nuclear Information System (INIS)

Bonalumi, Riccardo A.

1998-01-01

A new method of integrating differential equations was originated with the technique of approximately calculating the integrals called the pseudo-linear (PL) procedure: this method is A-stable. This article contains the following examples: 1st order ordinary differential equations (ODEs), 2nd order linear ODEs, stiff system of ODEs (neutron kinetics), one-dimensional parabolic (diffusion) partial differential equations. In this latter case, this PL method coincides with the Crank-Nicholson method

Dynamically stable associative learning: a neurobiologically based ANN and its applications

Science.gov (United States)

Vogl, Thomas P.; Blackwell, Kim L.; Barbour, Garth; Alkon, Daniel L.

1992-07-01

Most currently popular artificial neural networks (ANN) are based on conceptions of neuronal properties that date back to the 1940s and 50s, i.e., to the ideas of McCullough, Pitts, and Hebb. Dystal is an ANN based on current knowledge of neurobiology at the cellular and subcellular level. Networks based on these neurobiological insights exhibit the following advantageous properties: (1) A theoretical storage capacity of bN non-orthogonal memories, where N is the number of output neurons sharing common inputs and b is the number of distinguishable (gray shade) levels. (2) The ability to learn, store, and recall associations among noisy, arbitrary patterns. (3) A local synaptic learning rule (learning depends neither on the output of the post-synaptic neuron nor on a global error term), some of whose consequences are: (4) Feed-forward, lateral, and feed-back connections (as well as time-sensitive connections) are possible without alteration of the learning algorithm; (5) Storage allocation (patch creation) proceeds dynamically as associations are learned (self- organizing); (6) The number of training set presentations required for learning is small (different expressions and/or corrupted by noise, and on reading hand-written digits (98% accuracy) and hand-printed Japanese Kanji (90% accuracy) is demonstrated.

SUPPORTING STUDENTS’ UNDERSTANDING OF LINEAR EQUATIONS WITH ONE VARIABLE USING ALGEBRA TILES

Directory of Open Access Journals (Sweden)

Sari Saraswati

2016-01-01

Full Text Available This research aimed to describe how algebra tiles can support students’ understanding of linear equations with one variable. This article is a part of a larger research on learning design of linear equations with one variable using algebra tiles combined with balancing method. Therefore, it will merely discuss one activity focused on how students use the algebra tiles to find a method to solve linear equations with one variable. Design research was used as an approach in this study. It consists of three phases, namely preliminary design, teaching experiment and retrospective analysis. Video registrations, students’ written works, pre-test, post-test, field notes, and interview are technic to collect data. The data were analyzed by comparing the hypothetical learning trajectory (HLT and the actual learning process. The result shows that algebra tiles could supports students’ understanding to find the formal solution of linear equation with one variable.Keywords: linear equation with one variable, algebra tiles, design research, balancing method, HLT DOI: http://dx.doi.org/10.22342/jme.7.1.2814.19-30

Formation of stable radicals during perfluoroalkane radiolysis

International Nuclear Information System (INIS)

Allayarov, S.R.; Demidov, S.V.; Kiryukhin, D.P.; Mikhajlov, A.I.; Barkalov, I.M.

1984-01-01

Accumulation and stabilization kinetics of perfluoroalkyls during α-radiolysis ( 60 Co) of perfluoralkanes (PFA) in a wide temperature range for different PFA fractions differing in the average molecular weight, is investigated. It is noted that low temperature (PFA) radiolysis (77 K) is of a linear nature of accumulation of stabilized radicals up to doses of approximately 700 KGy. In the case of PFA radiolysis at 300 K radiation yields of stable radicals are somewhat lower than at 47 K and at doses of 200-300 KGy, their accumulation ceases. It is shown that kinetics of formation and accumulation of stable radicals does not depend on molecular mass and PFA fraction viscosity. Perfluoroalkyl stability is explained by intra molecular conformation spheric insulation of the free valency. Perfluoroalkyl stability in different PFA fractions in a wide time range in different media is investigated

An algebraic method for constructing stable and consistent autoregressive filters

International Nuclear Information System (INIS)

Harlim, John; Hong, Hoon; Robbins, Jacob L.

2015-01-01

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides a discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern

Focal spot motion of linear accelerators and its effect on portal image analysis

NARCIS (Netherlands)

Sonke, Jan-Jakob; Brand, Bob; van Herk, Marcel

2003-01-01

The focal spot of a linear accelerator is often considered to have a fully stable position. In practice, however, the beam control loop of a linear accelerator needs to stabilize after the beam is turned on. As a result, some motion of the focal spot might occur during the start-up phase of

Linear network theory

CERN Document Server

Sander, K F

1964-01-01

Linear Network Theory covers the significant algebraic aspect of network theory, with minimal reference to practical circuits. The book begins the presentation of network analysis with the exposition of networks containing resistances only, and follows it up with a discussion of networks involving inductance and capacity by way of the differential equations. Classification and description of certain networks, equivalent networks, filter circuits, and network functions are also covered. Electrical engineers, technicians, electronics engineers, electricians, and students learning the intricacies

Trade-off between learning and exploitation: the Pareto-optimal versus evolutionarily stable learning schedule in cumulative cultural evolution.

Science.gov (United States)

Wakano, Joe Yuichiro; Miura, Chiaki

2014-02-01

Inheritance of culture is achieved by social learning and improvement is achieved by individual learning. To realize cumulative cultural evolution, social and individual learning should be performed in this order in one's life. However, it is not clear whether such a learning schedule can evolve by the maximization of individual fitness. Here we study optimal allocation of lifetime to learning and exploitation in a two-stage life history model under a constant environment. We show that the learning schedule by which high cultural level is achieved through cumulative cultural evolution is unlikely to evolve as a result of the maximization of individual fitness, if there exists a trade-off between the time spent in learning and the time spent in exploiting the knowledge that has been learned in earlier stages of one's life. Collapse of a fully developed culture is predicted by a game-theoretical analysis where individuals behave selfishly, e.g., less learning and more exploiting. The present study suggests that such factors as group selection, the ability of learning-while-working ("on the job training"), or environmental fluctuation might be important in the realization of rapid and cumulative cultural evolution that is observed in humans. Copyright © 2013 Elsevier Inc. All rights reserved.

Dark energy cosmology with generalized linear equation of state

International Nuclear Information System (INIS)

Babichev, E; Dokuchaev, V; Eroshenko, Yu

2005-01-01

Dark energy with the usually used equation of state p = wρ, where w const 0 ), where the constants α and ρ 0 are free parameters. This non-homogeneous linear equation of state provides the description of both hydrodynamically stable (α > 0) and unstable (α < 0) fluids. In particular, the considered cosmological model describes the hydrodynamically stable dark (and phantom) energy. The possible types of cosmological scenarios in this model are determined and classified in terms of attractors and unstable points by using phase trajectories analysis. For the dark energy case, some distinctive types of cosmological scenarios are possible: (i) the universe with the de Sitter attractor at late times, (ii) the bouncing universe, (iii) the universe with the big rip and with the anti-big rip. In the framework of a linear equation of state the universe filled with a phantom energy, w < -1, may have either the de Sitter attractor or the big rip

Stable Alfven-wave dynamo action in the reversed-field pinch

International Nuclear Information System (INIS)

Werley, K.A.

1984-01-01

Previous theoretical work has suggested that Alfven waves may be related to the anomalous toroidal magnetic flux generation and extended (over classical expectations) discharge times observed in the reversed-field pinch. This thesis examines the dynamo action of stable Alfven waves as a means of generating toroidal flux. Recent advances in linear resistive MHD stability analysis are used to calculate the quasi-linear dynamo mean electromotive force of Alfven waves. This emf is incorporated into a one-dimensional transport and mean-field evolution code. The changing equilibrium is then fed back to the stability code to complete a computational framework that self-consistently evaluates a dynamic plasma dynamo. This technique is readily extendable to other plasmas in which dynamic stable model action is of interest. Such plasmas include Alfven wave current-drive and plasma heating for fusion devices, as well as astrophysical and geophysical dynamo systems. This study also contains extensive studies of resistive Alfven wave properties. This includes behavior versus spectral location, magnetic Reynolds number and wave number

Feedback Systems for Linear Colliders

International Nuclear Information System (INIS)

1999-01-01

Feedback systems are essential for stable operation of a linear collider, providing a cost-effective method for relaxing tight tolerances. In the Stanford Linear Collider (SLC), feedback controls beam parameters such as trajectory, energy, and intensity throughout the accelerator. A novel dithering optimization system which adjusts final focus parameters to maximize luminosity contributed to achieving record performance in the 1997-98 run. Performance limitations of the steering feedback have been investigated, and improvements have been made. For the Next Linear Collider (NLC), extensive feedback systems are planned as an integral part of the design. Feedback requirements for JLC (the Japanese Linear Collider) are essentially identical to NLC; some of the TESLA requirements are similar but there are significant differences. For NLC, algorithms which incorporate improvements upon the SLC implementation are being prototyped. Specialized systems for the damping rings, rf and interaction point will operate at high bandwidth and fast response. To correct for the motion of individual bunches within a train, both feedforward and feedback systems are planned. SLC experience has shown that feedback systems are an invaluable operational tool for decoupling systems, allowing precision tuning, and providing pulse-to-pulse diagnostics. Feedback systems for the NLC will incorporate the key SLC features and the benefits of advancing technologies

Successive substitution one-leg hybrid P-stable LMM for initial value ...

African Journals Online (AJOL)

This paper derives P-stable successive substitution one-leg hybrid linear multistep methods for the numerical solution of second order initial value problems in ordinary differential equations without explicit first order derivative. The methods are demonstrated by a numerical example also considered by Fatunla, et al (1997) ...

Frequency domain performance analysis of marginally stable LTI systems with saturation

NARCIS (Netherlands)

Berg, van den R.A.; Pogromski, A.Y.; Rooda, J.E.; Leonov, G.; Nijmeijer, H.; Pogromsky, A.; Fradkov, A.

2009-01-01

In this paper we discuss the frequency domain performance analysis of a marginally stable linear time-invariant (LTI) system with saturation in the feedback loop. We present two methods, both based on the notion of convergent systems, that allow to evaluate the performance of this type of systems in

STABLE STATIONARY STATES OF NON-LOCAL INTERACTION EQUATIONS

KAUST Repository

FELLNER, KLEMENS

2010-12-01

In this paper, we are interested in the large-time behaviour of a solution to a non-local interaction equation, where a density of particles/individuals evolves subject to an interaction potential and an external potential. It is known that for regular interaction potentials, stable stationary states of these equations are generically finite sums of Dirac masses. For a finite sum of Dirac masses, we give (i) a condition to be a stationary state, (ii) two necessary conditions of linear stability w.r.t. shifts and reallocations of individual Dirac masses, and (iii) show that these linear stability conditions imply local non-linear stability. Finally, we show that for regular repulsive interaction potential Wε converging to a singular repulsive interaction potential W, the Dirac-type stationary states ρ̄ ε approximate weakly a unique stationary state ρ̄ ∈ L∞. We illustrate our results with numerical examples. © 2010 World Scientific Publishing Company.

Retrospective Dose Reconstruction for Medical Diagnostic X Ray Workers in China using Stable Chromosome Aberrations

International Nuclear Information System (INIS)

Wang, Q.; Liu, P.; Li, J.; Wang, Q.; Tang, S.; Sun, M.; Wang, L.; Aoyama, T.; Sugahara, T.

1998-01-01

The chromosome rearrangements in medical diagnostic X ray workers were analysed using the G-banding technique and evaluated collectively in accumulated doses. A total of 9102 metaphase spreads from 84 medical diagnostic X ray workers and 17 controls were scored. The results showed that: (1) the frequencies of translocation, stable chromosome aberration and total aberration in X ray workers were significantly higher than those of controls (P < 0.05 γ 0.005), unstable chromosome aberrations (including dicentric and acentric aberration) tended upwards; (2) the main aberration in stable aberrations was reciprocal translocation; (3) the stable aberration predominated strikingly in total aberrations. The medical diagnostic X ray workers were divided into three groups according to calendar year of entry. The data showed that the frequencies of translocation, stable aberration and total aberration increased with earlier year of entry, especially in two groups who started working before 1970. According to the equation recommended by Straume et al, linear coefficient (α) in the linear quadratic model provided by Fernandez's experiment, their collective accumulation doses calculated were 0.53, 0.26 and 0.06 Gy for calendar year of entry before 1960, 1960-1969, and after 1970, in X ray workers, respectively. (author)

Stable convergence and stable limit theorems

CERN Document Server

Häusler, Erich

2015-01-01

The authors present a concise but complete exposition of the mathematical theory of stable convergence and give various applications in different areas of probability theory and mathematical statistics to illustrate the usefulness of this concept. Stable convergence holds in many limit theorems of probability theory and statistics – such as the classical central limit theorem – which are usually formulated in terms of convergence in distribution. Originated by Alfred Rényi, the notion of stable convergence is stronger than the classical weak convergence of probability measures. A variety of methods is described which can be used to establish this stronger stable convergence in many limit theorems which were originally formulated only in terms of weak convergence. Naturally, these stronger limit theorems have new and stronger consequences which should not be missed by neglecting the notion of stable convergence. The presentation will be accessible to researchers and advanced students at the master's level...

Unconditionally stable diffusion-acceleration of the transport equation

International Nuclear Information System (INIS)

Larsen, E.W.

1982-01-01

The standard iterative procedure for solving fixed-source discrete-ordinates problems converges very slowly for problems in optically large regions with scattering ratios c near unity. The diffusion-synthetic acceleration method has been proposed to make use of the fact that for this class of problems the diffusion equation is often an accurate approximation to the transport equation. However, stability difficulties have historically hampered the implementation of this method for general transport differencing schemes. In this article we discuss a recently developed procedure for obtaining unconditionally stable diffusion-synthetic acceleration methods for various transport differencing schemes. We motivate the analysis by first discussing the exact transport equation; then we illustrate the procedure by deriving a new stable acceleration method for the linear discontinuous transport differencing scheme. We also provide some numerical results

Unconditionally stable diffusion-acceleration of the transport equation

International Nuclear Information System (INIS)

Larson, E.W.

1982-01-01

The standard iterative procedure for solving fixed-source discrete-ordinates problems converges very slowly for problems in optically thick regions with scattering ratios c near unity. The diffusion-synthetic acceleration method has been proposed to make use of the fact that for this class of problems, the diffusion equation is often an accurate approximation to the transport equation. However, stability difficulties have historically hampered the implementation of this method for general transport differencing schemes. In this article we discuss a recently developed procedure for obtaining unconditionally stable diffusion-synthetic acceleration methods for various transport differencing schemes. We motivate the analysis by first discussing the exact transport equation; then we illustrate the procedure by deriving a new stable acceleration method for the linear discontinuous transport differencing scheme. We also provide some numerical results

From the SLAC linear collider to the next linear collider: A status report and road map

International Nuclear Information System (INIS)

Richter, B.

1992-02-01

In this presentation, I will review what we have learned about linear colliders, the problems that have been uncovered, and the technology-development program aimed at realizing the next high energy machine. I will then close with a few comments on how to get on with the job of building it

A Zero-One Dichotomy Theorem for r-Semi-Stable Laws on Infinite Dimensional Linear Spaces.

Science.gov (United States)

1978-10-01

SEMISTABLE LAWS - LIKE STABLE ONES - ARE CONTINUOUS: i.e. THEY ASSIGN’ ZERO MASS TO SIIMGLETONS.. DD 172 1 1473 sov’ow as, IMail , 62 i 1 SOee..S $.M 0 102 LfP.Of 4 6601 1ECIuatY CLASSI’PICA1 130N 00 1 100 0449 (W%4 Dma rwer

Supporting second grade lower secondary school students’ understanding of linear equation system in two variables using ethnomathematics

Science.gov (United States)

Nursyahidah, F.; Saputro, B. A.; Rubowo, M. R.

2018-03-01

The aim of this research is to know the students’ understanding of linear equation system in two variables using Ethnomathematics and to acquire learning trajectory of linear equation system in two variables for the second grade of lower secondary school students. This research used methodology of design research that consists of three phases, there are preliminary design, teaching experiment, and retrospective analysis. Subject of this study is 28 second grade students of Sekolah Menengah Pertama (SMP) 37 Semarang. The result of this research shows that the students’ understanding in linear equation system in two variables can be stimulated by using Ethnomathematics in selling buying tradition in Peterongan traditional market in Central Java as a context. All of strategies and model that was applied by students and also their result discussion shows how construction and contribution of students can help them to understand concept of linear equation system in two variables. All the activities that were done by students produce learning trajectory to gain the goal of learning. Each steps of learning trajectory of students have an important role in understanding the concept from informal to the formal level. Learning trajectory using Ethnomathematics that is produced consist of watching video of selling buying activity in Peterongan traditional market to construct linear equation in two variables, determine the solution of linear equation in two variables, construct model of linear equation system in two variables from contextual problem, and solving a contextual problem related to linear equation system in two variables.

Observer-based linear parameter varying H∞ tracking control for hypersonic vehicles

Directory of Open Access Journals (Sweden)

Yiqing Huang

2016-11-01

Full Text Available This article aims to develop observer-based linear parameter varying output feedback H∞ tracking controller for hypersonic vehicles. Due to the complexity of an original nonlinear model of the hypersonic vehicle dynamics, a slow–fast loop linear parameter varying polytopic model is introduced for system stability analysis and controller design. Then, a state observer is developed by linear parameter varying technique in order to estimate the unmeasured attitude angular for slow loop system. Also, based on the designed linear parameter varying state observer, a kind of attitude tracking controller is presented to reduce tracking errors for all bounded reference attitude angular inputs. The closed-loop linear parameter varying system is proved to be quadratically stable by Lypapunov function technique. Finally, simulation results show that the developed linear parameter varying H∞ controller has good tracking capability for reference commands.

Stable isogeometric analysis of trimmed geometries

Science.gov (United States)

Marussig, Benjamin; Zechner, Jürgen; Beer, Gernot; Fries, Thomas-Peter

2017-04-01

We explore extended B-splines as a stable basis for isogeometric analysis with trimmed parameter spaces. The stabilization is accomplished by an appropriate substitution of B-splines that may lead to ill-conditioned system matrices. The construction for non-uniform knot vectors is presented. The properties of extended B-splines are examined in the context of interpolation, potential, and linear elasticity problems and excellent results are attained. The analysis is performed by an isogeometric boundary element formulation using collocation. It is argued that extended B-splines provide a flexible and simple stabilization scheme which ideally suits the isogeometric paradigm.

Time-optimal feedback control for linear systems

International Nuclear Information System (INIS)

Mirica, S.

1976-01-01

The paper deals with the results of qualitative investigations of the time-optimal feedback control for linear systems with constant coefficients. In the first section, after some definitions and notations, two examples are given and it is shown that even the time-optimal control problem for linear systems with constant coefficients which looked like ''completely solved'' requires a further qualitative investigation of the stability to ''permanent perturbations'' of optimal feedback control. In the second section some basic results of the linear time-optimal control problem are reviewed. The third section deals with the definition of Boltyanskii's ''regular synthesis'' and its connection to Filippov's theory of right-hand side discontinuous differential equations. In the fourth section a theorem is proved concerning the stability to perturbations of time-optimal feedback control for linear systems with scalar control. In the last two sections it is proved that, if the matrix which defines the system has only real eigenvalues or is three-dimensional, the time-optimal feedback control defines a regular synthesis and therefore is stable to perturbations. (author)

Generalization in adaptation to stable and unstable dynamics.

Directory of Open Access Journals (Sweden)

Abdelhamid Kadiallah

Full Text Available Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization.

Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

Science.gov (United States)

Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

2014-01-01

The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations

Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement

Directory of Open Access Journals (Sweden)

Georg eLayher

2014-12-01

Full Text Available The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, but both belong to the category of felines. In other words, tigers and leopards are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in the computational neurosciences. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of (sub- category representations. We demonstrate the temporal evolution of such learning and show how the approach successully establishes category and subcategory

Non-linear shape functions over time in the space-time finite element method

Directory of Open Access Journals (Sweden)

Kacprzyk Zbigniew

2017-01-01

Full Text Available This work presents a generalisation of the space-time finite element method proposed by Kączkowski in his seminal of 1970’s and early 1980’s works. Kączkowski used linear shape functions in time. The recurrence formula obtained by Kączkowski was conditionally stable. In this paper, non-linear shape functions in time are proposed.

Blended Learning Approach for Enhancing Students' Learning Experiences in a Knowledge Society

Science.gov (United States)

Suprabha, K.; Subramonian, G.

2015-01-01

Blended learning which, its name suggests, blends online learning with traditional methods of learning and development. It is a new instructional strategy, based on the non-linear and interactive features of the digital learning and instruction through the web. Exploring the literature review, the purpose of the study was to get a deeper…

Optimized multiple linear mappings for single image super-resolution

Science.gov (United States)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Euclidean null controllability of linear systems with delays in state ...

African Journals Online (AJOL)

Sufficient conditions are developed for the Euclidean controllability of linear systems with delay in state and in control. Namely, if the uncontrolled system is uniformly asymptotically stable and the control equation proper, then the control system is Euclidean null controllable. Journal of the Nigerian Association of ...

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Science.gov (United States)

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

Directory of Open Access Journals (Sweden)

Guan Yu

Full Text Available Accurately identifying mild cognitive impairment (MCI individuals who will progress to Alzheimer's disease (AD is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI and fluorodeoxyglucose positron emission tomography (FDG-PET. However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI subjects and 226 stable MCI (sMCI subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images and also the single-task classification method (using only MRI or only subjects with both MRI and

Voltage-regulating constant-current sources in a linear induction accelerator

International Nuclear Information System (INIS)

Zhao Juan; Cao Kefeng; Deng Jianjun; Zhu Lijun; Yang Jia; Ye Chao; Huang Bin; Cao Ningxiang; Dong Jinxuan; Zhang Jichang; Yu Zhiguo; Chen Min

2002-01-01

Constant-current Sources are one of key units in a linear induction accelerator. The requirements for the sources are to supply stable direct current of high power for the induction coil, be easy to computer-control and highly stable and reliable. Applying the technique of linear current source regulating in series, the primary voltage of the power transformer is regulated through an MJYS-JL-350A type three-phase alterative voltage-regulating module. The output current variation is 300-500 A when the load variation is 0.06-0.1 Ω and the voltage drop of the regulator tube is controlled within 8 V±2V when the variation of mains voltage is in ±10%. Both the current ripple and stability meet the technical requirements. The constant-current sources are controlled through an industrial controller. For each of the constant-current sources has a smallest system comprised of 8051 which is communication-controlled through a RS-485 interface, the sources can be controlled remotely

ORACLS: A system for linear-quadratic-Gaussian control law design

Science.gov (United States)

Armstrong, E. S.

1978-01-01

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.

A Parametric Learning and Identification Based Robust Iterative Learning Control for Time Varying Delay Systems

Directory of Open Access Journals (Sweden)

Lun Zhai

2014-01-01

Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.

Students’ difficulties in solving linear equation problems

Science.gov (United States)

Wati, S.; Fitriana, L.; Mardiyana

2018-03-01

A linear equation is an algebra material that exists in junior high school to university. It is a very important material for students in order to learn more advanced mathematics topics. Therefore, linear equation material is essential to be mastered. However, the result of 2016 national examination in Indonesia showed that students’ achievement in solving linear equation problem was low. This fact became a background to investigate students’ difficulties in solving linear equation problems. This study used qualitative descriptive method. An individual written test on linear equation tasks was administered, followed by interviews. Twenty-one sample students of grade VIII of SMPIT Insan Kamil Karanganyar did the written test, and 6 of them were interviewed afterward. The result showed that students with high mathematics achievement donot have difficulties, students with medium mathematics achievement have factual difficulties, and students with low mathematics achievement have factual, conceptual, operational, and principle difficulties. Based on the result there is a need of meaningfulness teaching strategy to help students to overcome difficulties in solving linear equation problems.

Controlling chaos in RCL-shunted Josephson junction by delayed linear feedback

International Nuclear Information System (INIS)

Feng Yuling; Shen Ke

2008-01-01

The resistively-capacitively-inductively-shunted (RCL-shunted) Josephson junction (RCLSJJ) shows chaotic behaviour under some parameter conditions. Here a scheme for controlling chaos in the RCLSJJ is presented based on the linear feedback theory. Numerical simulations show that this scheme can be effectively used to control chaotic states in this junction into stable periodic states. Moreover, the different stable period states with different period numbers can be obtained by appropriately adjusting the feedback intensity and delay time without any pre-knowledge of this system required

Linearization instability for generic gravity in AdS spacetime

Science.gov (United States)

Altas, Emel; Tekin, Bayram

2018-01-01

In general relativity, perturbation theory about a background solution fails if the background spacetime has a Killing symmetry and a compact spacelike Cauchy surface. This failure, dubbed as linearization instability, shows itself as non-integrability of the perturbative infinitesimal deformation to a finite deformation of the background. Namely, the linearized field equations have spurious solutions which cannot be obtained from the linearization of exact solutions. In practice, one can show the failure of the linear perturbation theory by showing that a certain quadratic (integral) constraint on the linearized solutions is not satisfied. For non-compact Cauchy surfaces, the situation is different and for example, Minkowski space having a non-compact Cauchy surface, is linearization stable. Here we study, the linearization instability in generic metric theories of gravity where Einstein's theory is modified with additional curvature terms. We show that, unlike the case of general relativity, for modified theories even in the non-compact Cauchy surface cases, there are some theories which show linearization instability about their anti-de Sitter backgrounds. Recent D dimensional critical and three dimensional chiral gravity theories are two such examples. This observation sheds light on the paradoxical behavior of vanishing conserved charges (mass, angular momenta) for non-vacuum solutions, such as black holes, in these theories.

Bartlett correction in the stable AR(1) model with intercept and trend

NARCIS (Netherlands)

van Giersbergen, N.P.A.

2004-01-01

The Bartlett correction is derived for testing hypotheses about the autoregressive parameter ρ in the stable: (i) AR(1) model; (ii) AR(1) model with intercept; (iii) AR(1) model with intercept and linear trend. The correction is found explicitly as a function of ρ. In the models with deterministic

Non-linear Dynamics of Speech in Schizophrenia

DEFF Research Database (Denmark)

Fusaroli, Riccardo; Simonsen, Arndis; Weed, Ethan

(regularity and complexity) of speech. Our aims are (1) to achieve a more fine-grained understanding of the speech patterns in schizophrenia than has previously been achieved using traditional, linear measures of prosody and fluency, and (2) to employ the results in a supervised machine-learning process......-effects inference. SANS and SAPS scores were predicted using a 10-fold cross-validated multiple linear regression. Both analyses were iterated 1000 to test for stability of results. Results: Voice dynamics allowed discrimination of patients with schizophrenia from healthy controls with a balanced accuracy of 85...

A stable penalty method for the compressible Navier-Stokes equations: I. Open boundary conditions

DEFF Research Database (Denmark)

Hesthaven, Jan; Gottlieb, D.

1996-01-01

The purpose of this paper is to present asymptotically stable open boundary conditions for the numerical approximation of the compressible Navier-Stokes equations in three spatial dimensions. The treatment uses the conservation form of the Navier-Stokes equations and utilizes linearization...

High Order A-stable Continuous General Linear Methods for Solution of Systems of Initial Value Problems in ODEs

Directory of Open Access Journals (Sweden)

Dauda GuliburYAKUBU

2012-12-01

Full Text Available Accurate solutions to initial value systems of ordinary differential equations may be approximated efficiently by Runge-Kutta methods or linear multistep methods. Each of these has limitations of one sort or another. In this paper we consider, as a middle ground, the derivation of continuous general linear methods for solution of stiff systems of initial value problems in ordinary differential equations. These methods are designed to combine the advantages of both Runge-Kutta and linear multistep methods. Particularly, methods possessing the property of A-stability are identified as promising methods within this large class of general linear methods. We show that the continuous general linear methods are self-starting and have more ability to solve the stiff systems of ordinary differential equations, than the discrete ones. The initial value systems of ordinary differential equations are solved, for instance, without looking for any other method to start the integration process. This desirable feature of the proposed approach leads to obtaining very high accuracy of the solution of the given problem. Illustrative examples are given to demonstrate the novelty and reliability of the methods.

Entropy Stable Wall Boundary Conditions for the Three-Dimensional Compressible Navier-Stokes Equations

Science.gov (United States)

Parsani, Matteo; Carpenter, Mark H.; Nielsen, Eric J.

2015-01-01

Non-linear entropy stability and a summation-by-parts framework are used to derive entropy stable wall boundary conditions for the three-dimensional compressible Navier-Stokes equations. A semi-discrete entropy estimate for the entire domain is achieved when the new boundary conditions are coupled with an entropy stable discrete interior operator. The data at the boundary are weakly imposed using a penalty flux approach and a simultaneous-approximation-term penalty technique. Although discontinuous spectral collocation operators on unstructured grids are used herein for the purpose of demonstrating their robustness and efficacy, the new boundary conditions are compatible with any diagonal norm summation-by-parts spatial operator, including finite element, finite difference, finite volume, discontinuous Galerkin, and flux reconstruction/correction procedure via reconstruction schemes. The proposed boundary treatment is tested for three-dimensional subsonic and supersonic flows. The numerical computations corroborate the non-linear stability (entropy stability) and accuracy of the boundary conditions.

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data.

Science.gov (United States)

Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A

2017-02-01

This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r  =  0.71-0.88, RMSE: 1.11-1.61 METs; p  >  0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r  =  0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r  =  0.88, RMSE: 1.10-1.11 METs; p  >  0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r  =  0.88, RMSE: 1.12 METs. Linear models-correlations: r  =  0.86, RMSE: 1.18-1.19 METs; p  linear models for the wrist-worn accelerometers (ANN-correlations: r  =  0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r  =  0.71-0.73, RMSE: 1.55-1.61 METs; p  models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh

Analysis of stable isotope assisted metabolomics data acquired by GC-MS

International Nuclear Information System (INIS)

Wei, Xiaoli; Shi, Biyun; Koo, Imhoi; Yin, Xinmin; Lorkiewicz, Pawel; Suhail, Hamid; Rattan, Ramandeep; Giri, Shailendra; McClain, Craig J.

2017-01-01

Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., 13 C, 18 O and/or 15 N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 13 C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform 13 C-glucose and 13 C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples. - Highlights: • A signature ion approach is developed for analysis of stable isotope GC-MS data. • GC-MS data of compound standards are used for selection of the signature ion. • Linear regression model is used to deconvolute the overlapping isotopologue peaks. • The developed method was tested by known compounds and biological samples.

Exponentially Stable Stationary Solutions for Stochastic Evolution Equations and Their Perturbation

International Nuclear Information System (INIS)

Caraballo, Tomas; Kloeden, Peter E.; Schmalfuss, Bjoern

2004-01-01

We consider the exponential stability of stochastic evolution equations with Lipschitz continuous non-linearities when zero is not a solution for these equations. We prove the existence of anon-trivial stationary solution which is exponentially stable, where the stationary solution is generated by the composition of a random variable and the Wiener shift. We also construct stationary solutions with the stronger property of attracting bounded sets uniformly. The existence of these stationary solutions follows from the theory of random dynamical systems and their attractors. In addition, we prove some perturbation results and formulate conditions for the existence of stationary solutions for semilinear stochastic partial differential equations with Lipschitz continuous non-linearities

Student Accountability in Team-Based Learning Classes

Science.gov (United States)

Stein, Rachel E.; Colyer, Corey J.; Manning, Jason

2016-01-01

Team-based learning (TBL) is a form of small-group learning that assumes stable teams promote accountability. Teamwork promotes communication among members; application exercises promote active learning. Students must prepare for each class; failure to do so harms their team's performance. Therefore, TBL promotes accountability. As part of the…

Machine learning techniques applied to system characterization and equalization

DEFF Research Database (Denmark)

Zibar, Darko; Thrane, Jakob; Wass, Jesper

2016-01-01

Linear signal processing algorithms are effective in combating linear fibre channel impairments. We demonstrate the ability of machine learning algorithms to combat nonlinear fibre channel impairments and perform parameter extraction from directly detected signals.......Linear signal processing algorithms are effective in combating linear fibre channel impairments. We demonstrate the ability of machine learning algorithms to combat nonlinear fibre channel impairments and perform parameter extraction from directly detected signals....

Penerapan Pendekatan Reciprocal Teaching dalam Setting Pembelajaran Kooperatif Materi Sistem Persamaan Linear Tiga Variabel

OpenAIRE

Dewi, Wahyu Tiara

2017-01-01

This research aims to determine the effectiveness of mathematics learning with reciprocal teaching approach in the setting of cooperative learning. The subject matter is system of linear equations of three variables grade X IPS-1 MAN 2 Pontianak. Three aspects of learning effectiveness used are the teacher's ability to manage learning, the student activity learning, and the student learning outcomes. The research method used is descriptive method. The form of research used is pre-experiment w...

Study of Environmental Data Complexity using Extreme Learning Machine

Science.gov (United States)

Leuenberger, Michael; Kanevski, Mikhail

2017-04-01

The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

Rapid Associative Learning and Stable Long-Term Memory in the Squid Euprymna scolopes.

Science.gov (United States)

Zepeda, Emily A; Veline, Robert J; Crook, Robyn J

2017-06-01

Learning and memory in cephalopod molluscs have received intensive study because of cephalopods' complex behavioral repertoire and relatively accessible nervous systems. While most of this research has been conducted using octopus and cuttlefish species, there has been relatively little work on squid. Euprymna scolopes Berry, 1913, a sepiolid squid, is a promising model for further exploration of cephalopod cognition. These small squid have been studied in detail for their symbiotic relationship with bioluminescent bacteria, and their short generation time and successful captive breeding through multiple generations make them appealing models for neurobiological research. However, little is known about their behavior or cognitive ability. Using the well-established "prawn-in-the-tube" assay of learning and memory, we show that within a single 10-min trial E. scolopes learns to inhibit its predatory behavior, and after three trials it can retain this memory for at least 12 d. Rapid learning and very long-term retention were apparent under two different training schedules. To our knowledge, this study is the first demonstration of learning and memory in this species as well as the first demonstration of associative learning in any squid.

Development of new S-band RF window for stable high-power operation in linear accelerator RF system

Science.gov (United States)

Joo, Youngdo; Lee, Byung-Joon; Kim, Seung-Hwan; Kong, Hyung-Sup; Hwang, Woonha; Roh, Sungjoo; Ryu, Jiwan

2017-09-01

For stable high-power operation, a new RF window is developed in the S-band linear accelerator (Linac) RF systems of the Pohang Light Source-II (PLS-II) and the Pohang Accelerator Laboratory X-ray Free-Electron Laser (PAL-XFEL). The new RF window is designed to mitigate the strength of the electric field at the ceramic disk and also at the waveguide-cavity coupling structure of the conventional RF window. By replacing the pill-box type cavity in the conventional RF window with an overmoded cavity, the electric field component perpendicular to the ceramic disk that caused most of the multipacting breakdowns in the ceramic disk was reduced by an order of magnitude. The reduced electric field at the ceramic disk eliminated the Ti-N coating process on the ceramic surface in the fabrication procedure of the new RF window, preventing the incomplete coating from spoiling the RF transmission and lowering the fabrication cost. The overmoded cavity was coupled with input and output waveguides through dual side-wall coupling irises to reduce the electric field strength at the waveguide-cavity coupling structure and the possibility of mode competitions in the overmoded cavity. A prototype of the new RF window was fabricated and fully tested with the Klystron peak input power, pulse duration and pulse repetition rate of 75 MW, 4.5 μs and 10 Hz, respectively, at the high-power test stand. The first mass-produced new RF window installed in the PLS-II Linac is running in normal operation mode. No fault is reported to date. Plans are being made to install the new RF window to all S-band accelerator RF modules of the PLS-II and PAL-XFEL Linacs. This new RF window may be applied to the output windows of S-band power sources like Klystron as wells as the waveguide windows of accelerator facilities which operate in S-band.

Inhomogeneous quantum diffusion and decay of a meta-stable state

Energy Technology Data Exchange (ETDEWEB)

Ghosh, Pulak Kumar [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India); Barik, Debashis [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India); Ray, Deb Shankar [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India)

2007-01-29

We consider the quantum stochastic dynamics of a system whose interaction with the reservoir is considered to be linear in bath co-ordinates but nonlinear in system co-ordinates. The role of the space-dependent friction and diffusion has been examined in the decay rate of a particle from a meta-stable well. We show how the decay rate can be hindered by inhomogeneous dissipation due to nonlinear system-bath coupling strength.

Inhomogeneous quantum diffusion and decay of a meta-stable state

International Nuclear Information System (INIS)

Ghosh, Pulak Kumar; Barik, Debashis; Ray, Deb Shankar

2007-01-01

We consider the quantum stochastic dynamics of a system whose interaction with the reservoir is considered to be linear in bath co-ordinates but nonlinear in system co-ordinates. The role of the space-dependent friction and diffusion has been examined in the decay rate of a particle from a meta-stable well. We show how the decay rate can be hindered by inhomogeneous dissipation due to nonlinear system-bath coupling strength

Inhomogeneous quantum diffusion and decay of a meta-stable state

Energy Technology Data Exchange (ETDEWEB)

Ghosh, Pulak Kumar [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India); Barik, Debashis [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India); Ray, Deb Shankar [Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700 032 (India)

2006-12-18

We consider the quantum stochastic dynamics of a system whose interaction with the reservoir is considered to be linear in bath co-ordinates but nonlinear in system co-ordinates. The role of the space-dependent friction and diffusion has been examined in the decay rate of a particle from a meta-stable well. We show how the decay rate can be hindered by inhomogeneous dissipation due to nonlinear system-bath coupling strength.

Inhomogeneous quantum diffusion and decay of a meta-stable state

International Nuclear Information System (INIS)

Ghosh, Pulak Kumar; Barik, Debashis; Ray, Deb Shankar

2006-01-01

We consider the quantum stochastic dynamics of a system whose interaction with the reservoir is considered to be linear in bath co-ordinates but nonlinear in system co-ordinates. The role of the space-dependent friction and diffusion has been examined in the decay rate of a particle from a meta-stable well. We show how the decay rate can be hindered by inhomogeneous dissipation due to nonlinear system-bath coupling strength

Linear and support vector regressions based on geometrical correlation of data

Directory of Open Access Journals (Sweden)

Kaijun Wang

2007-10-01

Full Text Available Linear regression (LR and support vector regression (SVR are widely used in data analysis. Geometrical correlation learning (GcLearn was proposed recently to improve the predictive ability of LR and SVR through mining and using correlations between data of a variable (inner correlation. This paper theoretically analyzes prediction performance of the GcLearn method and proves that GcLearn LR and SVR will have better prediction performance than traditional LR and SVR for prediction tasks when good inner correlations are obtained and predictions by traditional LR and SVR are far away from their neighbor training data under inner correlation. This gives the applicable condition of GcLearn method.

Tried and True: Springing into Linear Models

Science.gov (United States)

Darling, Gerald

2012-01-01

In eighth grade, students usually learn about forces in science class and linear relationships in math class, crucial topics that form the foundation for further study in science and engineering. An activity that links these two fundamental concepts involves measuring the distance a spring stretches as a function of how much weight is suspended…

The classical Pierce diode: Using particle simulations on linear and nonlinear behavior and final states

International Nuclear Information System (INIS)

Crystal, T.L.; Kuhn, S.; Birdsall, C.K.

1984-01-01

The classical Pierce diode is a simple 1-d system of two shorted metal plates, a cold beam of electrons injected from one side and a neutralizing background of rigid ions. While the plasma medium is technically stable, the finiteness of the Pierce system allows stable and unstable operation. It is usefully studied as an archetypical bounded plasma system, related e.g., to Q-machines, particle accelerators, thermionic converters. New particle simulations of the Pierce diode have successfully recovered many novel linear phenomena including the dominant linear eigenmodes (seen in the internal electrostatic fields), and the dominant and subdominant eigenfrequencies, (seen both in the internal electrostatics and in the external circuit current, J/sub ext/(t)). These simulation results conform very well to detailed predictions of a new linear analysis. The final (nonlinear) state recovered can show critical dependence on initial (linear perturbation) conditions, and can be made steady-state (d.c.) or periodic-oscillatory by simply changing the initial conditions by a factor of 10/sup -4/ or less. A third class of final state is also possible which has oscillations which seem to be nonperiodic

Robust stabilization of nonlinear systems via stable kernel representations with L2-gain bounded uncertainty

NARCIS (Netherlands)

van der Schaft, Arjan

1995-01-01

The approach to robust stabilization of linear systems using normalized left coprime factorizations with H∞ bounded uncertainty is generalized to nonlinear systems. A nonlinear perturbation model is derived, based on the concept of a stable kernel representation of nonlinear systems. The robust

Fuzzy self-learning control for magnetic servo system

Science.gov (United States)

Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

1994-01-01

It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

Identification of the dynamic operating envelope of HCCI engines using class imbalance learning.

Science.gov (United States)

Janakiraman, Vijay Manikandan; Nguyen, XuanLong; Sterniak, Jeff; Assanis, Dennis

2015-01-01

Homogeneous charge compression ignition (HCCI) is a futuristic automotive engine technology that can significantly improve fuel economy and reduce emissions. HCCI engine operation is constrained by combustion instabilities, such as knock, ringing, misfires, high-variability combustion, and so on, and it becomes important to identify the operating envelope defined by these constraints for use in engine diagnostics and controller design. HCCI combustion is dominated by complex nonlinear dynamics, and a first-principle-based dynamic modeling of the operating envelope becomes intractable. In this paper, a machine learning approach is presented to identify the stable operating envelope of HCCI combustion, by learning directly from the experimental data. Stability is defined using thresholds on combustion features obtained from engine in-cylinder pressure measurements. This paper considers instabilities arising from engine misfire and high-variability combustion. A gasoline HCCI engine is used for generating stable and unstable data observations. Owing to an imbalance in class proportions in the data set, the models are developed both based on resampling the data set (by undersampling and oversampling) and based on a cost-sensitive learning method (by overweighting the minority class relative to the majority class observations). Support vector machines (SVMs) and recently developed extreme learning machines (ELM) are utilized for developing dynamic classifiers. The results compared against linear classification methods show that cost-sensitive nonlinear ELM and SVM classification algorithms are well suited for the problem. However, the SVM envelope model requires about 80% more parameters for an accuracy improvement of 3% compared with the ELM envelope model indicating that ELM models may be computationally suitable for the engine application. The proposed modeling approach shows that HCCI engine misfires and high-variability combustion can be predicted ahead of time

Temperature and sowing date affect the linear increase of sunflower harvest index

International Nuclear Information System (INIS)

Bange, M.P.; Hammer, G.L.; Rickert, K.G.

1998-01-01

The linearity of daily linear harvest index (HI) increase can provide a simple means to predict grain growth and yield in field crops. However, the stability of the rate of increase across genotypes and environments is uncertain. Data from three field experiments were collated to investigate the phase of linear HI increase of sunflower (Helianthus annuus L.) across environments by changing genotypes, sowing time, N level, and solar irradiation level. Linear increase in HI was similar among different genotypes, N levels, and radiation treatments (mean 0.0125 d-1), but significant differences occurred between sowings. The linear increase in HI was not stable at very low temperatures (down to 9 degrees C) during grain filling, due to possible limitations to biomass accumulation and translocation (mean 0.0091 d-1). Using the linear increase in HI to predict grain yield requires predictions of the duration from an thesis to the onset of linear HI increase (lag phase) and the cessation of linear HI increase. These studies showed that the lag phase differed, and the linear HI increase ceased when 91% of the anthesis to physiological maturity period had been completed

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Directory of Open Access Journals (Sweden)

Chandra Nagasuma R

2009-02-01

Full Text Available Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting problem and solved finally by formulating a Linear Program (LP. A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known

Supporting Students' Understanding of Linear Equations with One Variable Using Algebra Tiles

Science.gov (United States)

Saraswati, Sari; Putri, Ratu Ilma Indra; Somakim

2016-01-01

This research aimed to describe how algebra tiles can support students' understanding of linear equations with one variable. This article is a part of a larger research on learning design of linear equations with one variable using algebra tiles combined with balancing method. Therefore, it will merely discuss one activity focused on how students…

Stable long-time semiclassical description of zero-point energy in high-dimensional molecular systems.

Science.gov (United States)

Garashchuk, Sophya; Rassolov, Vitaly A

2008-07-14

Semiclassical implementation of the quantum trajectory formalism [J. Chem. Phys. 120, 1181 (2004)] is further developed to give a stable long-time description of zero-point energy in anharmonic systems of high dimensionality. The method is based on a numerically cheap linearized quantum force approach; stabilizing terms compensating for the linearization errors are added into the time-evolution equations for the classical and nonclassical components of the momentum operator. The wave function normalization and energy are rigorously conserved. Numerical tests are performed for model systems of up to 40 degrees of freedom.

Stable isotopes

International Nuclear Information System (INIS)

Evans, D.K.

1986-01-01

Seventy-five percent of the world's stable isotope supply comes from one producer, Oak Ridge Nuclear Laboratory (ORNL) in the US. Canadian concern is that foreign needs will be met only after domestic needs, thus creating a shortage of stable isotopes in Canada. This article describes the present situation in Canada (availability and cost) of stable isotopes, the isotope enrichment techniques, and related research programs at Chalk River Nuclear Laboratories (CRNL)

Stable long-term chronic brain mapping at the single-neuron level.

Science.gov (United States)

Fu, Tian-Ming; Hong, Guosong; Zhou, Tao; Schuhmann, Thomas G; Viveros, Robert D; Lieber, Charles M

2016-10-01

Stable in vivo mapping and modulation of the same neurons and brain circuits over extended periods is critical to both neuroscience and medicine. Current electrical implants offer single-neuron spatiotemporal resolution but are limited by such factors as relative shear motion and chronic immune responses during long-term recording. To overcome these limitations, we developed a chronic in vivo recording and stimulation platform based on flexible mesh electronics, and we demonstrated stable multiplexed local field potentials and single-unit recordings in mouse brains for at least 8 months without probe repositioning. Properties of acquired signals suggest robust tracking of the same neurons over this period. This recording and stimulation platform allowed us to evoke stable single-neuron responses to chronic electrical stimulation and to carry out longitudinal studies of brain aging in freely behaving mice. Such advantages could open up future studies in mapping and modulating changes associated with learning, aging and neurodegenerative diseases.

LINEAR2007, Linear-Linear Interpolation of ENDF Format Cross-Sections

International Nuclear Information System (INIS)

2007-01-01

1 - Description of program or function: LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form. Codes used subsequently need thus to consider only linear-linear data. IAEA1311/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. Modifications from previous versions: - Linear VERS. 2007-1 (JAN. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 600,000 points 2 - Method of solution: Each section of data is considered separately. Each section of File 3, 23, and 27 data consists of a table of cross section versus energy with any of five interpolation laws. LINEAR will replace each section with a new table of energy versus cross section data in which the interpolation law is always linear in energy and cross section. The histogram (constant cross section between two energies) interpolation law is converted to linear-linear by substituting two points for each initial point. The linear-linear is not altered. For the log-linear, linear-log and log- log laws, the cross section data are converted to linear by an interval halving algorithm. Each interval is divided in half until the value at the middle of the interval can be approximated by linear-linear interpolation to within a given accuracy. The LINEAR program uses a multipoint fractional error thinning algorithm to minimize the size of each cross section table

A semigroup approach to the strong ergodic theorem of the multistate stable population process.

Science.gov (United States)

Inaba, H

1988-01-01

"In this paper we first formulate the dynamics of multistate stable population processes as a partial differential equation. Next, we rewrite this equation as an abstract differential equation in a Banach space, and solve it by using the theory of strongly continuous semigroups of bounded linear operators. Subsequently, we investigate the asymptotic behavior of this semigroup to show the strong ergodic theorem which states that there exists a stable distribution independent of the initial distribution. Finally, we introduce the dual problem in order to obtain a logical definition for the reproductive value and we discuss its applications." (SUMMARY IN FRE) excerpt

Linear electrostatic waves in a three-component electron-positron-ion plasma

Energy Technology Data Exchange (ETDEWEB)

Mugemana, A., E-mail: mugemanaa@gmail.com; Moolla, S. [School of Chemistry and Physics, University of KwaZulu-Natal, Durban 4000 (South Africa); Lazarus, I. J. [Department of Mathematics, Statistics and Physics, Durban University of Technology, Durban 4000 (South Africa)

2014-12-15

Analytical linear electrostatic waves in a magnetized three-component electron-positron-ion plasma are studied in the low-frequency limit. By using the continuity and momentum equations with Poisson's equation, the dispersion relation for the electron-positron-ion plasma consisting of cool ions, and hot Boltzmann electrons and positrons is derived. In the linear regime, the propagation of two possible modes and their evolution are studied. In the cases of parallel and perpendicular propagation, it is shown that these two possible modes are always stable. The present investigation contributes to nonlinear propagation of electrostatic waves in space and the laboratory.

Stable Isotope Data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Tissue samples (skin, bone, blood, muscle) are analyzed for stable carbon, stable nitrogen, and stable sulfur analysis. Many samples are used in their entirety for...

stableGP

Data.gov (United States)

National Aeronautics and Space Administration — The code in the stableGP package implements Gaussian process calculations using efficient and numerically stable algorithms. Description of the algorithms is in the...

The Effects of Differential Learning and Traditional Learning Trainings on Technical Development of Football Players

Science.gov (United States)

Bozkurt, Sinan

2018-01-01

There are several different methods of learning motor skills, like traditional (linear) and differential (nonlinear) learning training. The traditional motor learning approach proposes that learners improve a skill just by repeating it. According to the teaching principles, exercises are selected along continua from easy to hard and from simple to…

Study of the critical behavior of the O(N) linear and nonlinear sigma models

International Nuclear Information System (INIS)

Graziani, F.R.

1983-01-01

A study of the large N behavior of both the O(N) linear and nonlinear sigma models is presented. The purpose is to investigate the relationship between the disordered (ordered) phase of the linear and nonlinear sigma models. Utilizing operator product expansions and stability analyses, it is shown that for 2 - (lambda/sub R/(M) is the dimensionless renormalized quartic coupling and lambda* is the IR fixed point) limit of the linear sigma model which yields the nonlinear sigma model. It is also shown that stable large N linear sigma models with lambda 0) and nonlinear models are trivial. This result (i.e., triviality) is well known but only for one and two component models. Interestingly enough, the lambda< d = 4 linear sigma model remains nontrivial and tachyonic free

Simplified neural networks for solving linear least squares and total least squares problems in real time.

Science.gov (United States)

Cichocki, A; Unbehauen, R

1994-01-01

In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known algorithms: the row-action projection-Kaczmarz algorithm and/or the LMS (Adaline) Widrow-Hoff algorithms. The algorithms can be applied to any problem which can be formulated as a linear regression problem. The correctness and high performance of the proposed neural networks are illustrated by extensive computer simulation results.

Optimal physiological structure of small neurons to guarantee stable information processing

Science.gov (United States)

Zeng, S. Y.; Zhang, Z. Z.; Wei, D. Q.; Luo, X. S.; Tang, W. Y.; Zeng, S. W.; Wang, R. F.

2013-02-01

Spike is the basic element for neuronal information processing and the spontaneous spiking frequency should be less than 1 Hz for stable information processing. If the neuronal membrane area is small, the frequency of neuronal spontaneous spiking caused by ion channel noise may be high. Therefore, it is important to suppress the deleterious spontaneous spiking of the small neurons. We find by simulation of stochastic neurons with Hodgkin-Huxley-type channels that the leakage system is critical and extremely efficient to suppress the spontaneous spiking and guarantee stable information processing of the small neurons. However, within the physiological limit the potassium system cannot do so. The suppression effect of the leakage system is super-exponential, but that of the potassium system is quasi-linear. With the minor physiological cost and the minimal consumption of metabolic energy, a slightly lower reversal potential and a relatively larger conductance of the leakage system give the optimal physiological structure to suppress the deleterious spontaneous spiking and guarantee stable information processing of small neurons, dendrites and axons.

Localization of Stable and Chaotic Nonpropagating Structures in Nonlinear Mesoscopic Lattices.

Science.gov (United States)

Greenfield, Alan Barry

Recent developments in the study of non-linear localized states, especially non-propagating ones, are outlined. Theoretical models of linear and nonlinear states in a lattice of coupled pendulums and related systems are reviewed. Particular attention is paid to those states which can be described by the Nonlinear Schrodinger equation as well as states where two modes can coexist and states exhibiting chaos. Measurement of localized stable and chaotic states in a 35 site physical pendulum lattice is reported. Various measurement techniques that were used are explained. States that were measured include the tanh profile or kink soliton, and the corresponding uniform state in the wavelength 2 mode, a similar soliton and uniform state in the wavelength 4 mode, a domain wall between the wavelength 2 and 4 modes and a domain wall between a chaotic state and the wavelength 2 mode. Amplitude profiles were measured for the stable kink and domain wall states and smooth curves were obtained by dividing the kink states by the corresponding uniform states. Return maps were measured for two sites in the chaotic domain wall. Simulation of a chaotic domain wall in a 50 site numerical lattice is reported. This system has the advantage that its parameters can be modified much more easily than those of the physical lattice. An attempt is made at quantifying the level of chaos as a function of lattice site with fractal dimension calculations on return maps embedded in a three dimensional space. The drive plane of the chaotic domain wall is mapped out in the drive amplitude - drive frequency plane. Transitions to various stable and quasiperiodic domain walls are noted.

Solution to reinforcement learning problems with artificial potential field

Institute of Scientific and Technical Information of China (English)

XIE Li-juan; XIE Guang-rong; CHEN Huan-wen; LI Xiao-li

2008-01-01

A novel method was designed to solve reinforcement learning problems with artificial potential field. Firstly a reinforcement learning problem was transferred to a path planning problem by using artificial potential field(APF), which was a very appropriate method to model a reinforcement learning problem. Secondly, a new APF algorithm was proposed to overcome the local minimum problem in the potential field methods with a virtual water-flow concept. The performance of this new method was tested by a gridworld problem named as key and door maze. The experimental results show that within 45 trials, good and deterministic policies are found in almost all simulations. In comparison with WIERING's HQ-learning system which needs 20 000 trials for stable solution, the proposed new method can obtain optimal and stable policy far more quickly than HQ-learning. Therefore, the new method is simple and effective to give an optimal solution to the reinforcement learning problem.

Force production during squats performed with a rotational resistance device under stable versus unstable conditions.

Science.gov (United States)

Moras, Gerard; Vázquez-Guerrero, Jairo

2015-11-01

[Purpose] Force production during a squat action on a rotational resistance device (RRD) under stable and unstable conditions. [Subjects and Methods] Twenty-one healthy males were asked to perform six sets of six repetitions of squats on an RRD on either stable or unstable surfaces. The stable and unstable sets were performed on different days. Muscular outputs were obtained from a linear encoder and a strain gauge fixed to a vest. [Results] Overall, the results showed no significant differences for any of the dependent variables across exercise modes. Forcemean outputs were higher in the concentric phase than in the eccentric phase for each condition, but there were no differences in velocity, time or displacement. The forcepeak was similar in the eccentric and concentric phases of movement under both stable and unstable conditions. There were no significant differences in forcemean between sets per condition or between conditions. [Conclusion] These results suggest that performing squats with a RRD achieves similar forcemean and forcepeak under stable and unstable conditions. The forcepeak produced is also similar in concentric and eccentric phases.

Linearization Method and Linear Complexity

Science.gov (United States)

Tanaka, Hidema

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

Uncertainty principle and the stable interpretation of spectrometric experiment results

International Nuclear Information System (INIS)

Zhukovskij, E.L.

1984-01-01

Two stable forms for recording least-swuare method used for evaluation of parameters durmng automated processing and interpretation of various type spectra were derived on the basis of the Kramer-Rao inequality. Spectra described by linear equations are considered for which parameter evaluations are recorded in a final form. It is shown that the suggested form of the interpreting functional is maintained for the spectra of different nature (NMR-, IR-, UV-, RS- and mass-spectra), their parameters depending nonlinearly on the wave number

Transformative Learning in Postapartheid South Africa: Disruption, Dilemma, and Direction

Science.gov (United States)

Cox, Amanda J.; John, Vaughn M.

2016-01-01

The catalyst for learning and change in transformative learning theory has mostly been explained in terms of a disorientation in a relatively stable life. This article explores a South African, nonformal adult learning program, as a source of "orienting dilemmas," which catalyze learning and change in lives that are regularly and…

[Study on retention and stability of linear occlusal complete dentures].

Science.gov (United States)

Zhang, Ping; Xu, Jun

2003-01-01

To learn retention and stability of linear occlusal complete dentures by investigating the subjective feelings of patient and the value of retention force. Static retention forces of maxillary and mandibular dentures were measured for 25 patients wearing linear occlusal dentures by using Hz-1 retention dynamometer. The subjective feelings of patients in functional state were gained simultaneously through questionnaire. Linear occlusal dentures demonstrate good retention in static and dynamic state. Among patients with severe resorption of residual ridge (RRR), mandibular linear occlusal dentures (shown good retentive subjective feelings) demonstrate significantly smaller retention force than those with slight or medium degree of RRR. There is no correlation between the subjective feelings and the values of retention forces of mandibular dentures. The subjective feelings of patients wearing new linear occlusal dentures are much better than that of old anatomic occlusal dentures. Linear occlusal dentures improve the performances of dentures by enhancing their stability during mastication movement.

Evidence for weak or linear conformity but not for hyper-conformity in an everyday social learning context.

Science.gov (United States)

Claidière, Nicolas; Bowler, Mark; Whiten, Andrew

2012-01-01

Conformity is thought to be an important force in cultural evolution because it has the potential to stabilize cooperation in large groups, potentiate group selection and thus explain uniquely human behaviors. However, the effects of such conformity on cultural and biological evolution will depend much on the way individuals are influenced by the frequency of alternative behavioral options witnessed. Theoretical modeling has suggested that only what we refer to as 'hyper-conformity', an exaggerated tendency to perform the most frequent behavior witnessed in other individuals, is able to increase within-group homogeneity and between-group diversity, for instance. Empirically however, few experiments have addressed how the frequency of behavior witnessed affects behavior. Accordingly we performed an experiment to test for the presence of conformity in a natural situation with humans. Visitors to a Zoo exhibit were invited to write or draw answers to questions on A5 cards and potentially win a small prize. We manipulated the proportion of existing writings versus drawings visible to visitors and measured the proportion of written cards submitted. We found a strong and significant effect of the proportion of text displayed on the proportion of text in the answers, thus demonstrating social learning. We show that this effect is approximately linear, with potentially a small, weak-conformist component but no hyper-conformist one. The present experiment therefore provides evidence for linear conformity in humans in a very natural context.

Non linear stability analysis of parallel channels with natural circulation

Energy Technology Data Exchange (ETDEWEB)

Mishra, Ashish Mani; Singh, Suneet, E-mail: suneet.singh@iitb.ac.in

2016-12-01

Highlights: • Nonlinear instabilities in natural circulation loop are studied. • Generalized Hopf points, Sub and Supercritical Hopf bifurcations are identified. • Bogdanov–Taken Point (BT Point) is observed by nonlinear stability analysis. • Effect of parameters on stability of system is studied. - Abstract: Linear stability analysis of two-phase flow in natural circulation loop is quite extensively studied by many researchers in past few years. It can be noted that linear stability analysis is limited to the small perturbations only. It is pointed out that such systems typically undergo Hopf bifurcation. If the Hopf bifurcation is subcritical, then for relatively large perturbation, the system has unstable limit cycles in the (linearly) stable region in the parameter space. Hence, linear stability analysis capturing only infinitesimally small perturbations is not sufficient. In this paper, bifurcation analysis is carried out to capture the non-linear instability of the dynamical system and both subcritical and supercritical bifurcations are observed. The regions in the parameter space for which subcritical and supercritical bifurcations exist are identified. These regions are verified by numerical simulation of the time-dependent, nonlinear ODEs for the selected points in the operating parameter space using MATLAB ODE solver.

Linear-to-λ-Shape P-O-P Bond Transmutation in Polyphosphates with Infinite (PO3)∞ Chain.

Science.gov (United States)

Wang, Ying; Li, Lin; Han, Shujuan; Lei, Bing-Hua; Abudoureheman, Maierhaba; Yang, Zhihua; Pan, Shilie

2017-09-05

A new metal polyphosphate, α-CsBa 2 (PO 3 ) 5 , exhibiting the first example of a linear P-O-P bond angle in a one-dimensional (PO 3 ) ∞ chain has been reported. Interestingly, α → β phase transition occurs in CsBa 2 (PO 3 ) 5 along with the P-O-P bonds varying from linear to λ-shape, suggesting that α-CsBa 2 (PO 3 ) 5 with unfavorable linear P-O-P bonds is more stable at ambient temperature.

Learning Statistics - in a WEB-based and non-linear way

DEFF Research Database (Denmark)

Rootzen, Helle

2007-01-01

different from one another. They have different prior knowledge and different learning styles so it is a challenging task to teach them all in the same way. Furthermore the world of statistics has become so huge that it is impossible to cover everything. The structure imposed by the Bologna agreement gives...... can design the course – or a part of the course – so that it fits their individual learning style and their prior knowledge. Some prefer to look at examples first and afterwards look at which theories it is based on. Others want to do it the opposite way. Some wants to work with the problem themselves...

Variables Predicting Foreign Language Reading Comprehension and Vocabulary Acquisition in a Linear Hypermedia Environment

Science.gov (United States)

Akbulut, Yavuz

2007-01-01

Factors predicting vocabulary learning and reading comprehension of advanced language learners of English in a linear multimedia text were investigated in the current study. Predictor variables of interest were multimedia type, reading proficiency, learning styles, topic interest and background knowledge about the topic. The outcome variables of…

Stable Trapping of Multielectron Helium Bubbles in a Paul Trap

Science.gov (United States)

Joseph, E. M.; Vadakkumbatt, V.; Pal, A.; Ghosh, A.

2017-06-01

In a recent experiment, we have used a linear Paul trap to store and study multielectron bubbles (MEBs) in liquid helium. MEBs have a charge-to-mass ratio (between 10^{-4} and 10^{-2} C/kg) which is several orders of magnitude smaller than ions (between 10^6 and 10^8 C/kg) studied in traditional ion traps. In addition, MEBs experience significant drag force while moving through the liquid. As a result, the experimental parameters for stable trapping of MEBs, such as magnitude and frequency of the applied electric fields, are very different from those used in typical ion trap experiments. The purpose of this paper is to model the motion of MEBs inside a linear Paul trap in liquid helium, determine the range of working parameters of the trap, and compare the results with experiments.

Separate groups of dopamine neurons innervate caudate head and tail encoding flexible and stable value memories

Directory of Open Access Journals (Sweden)

Hyoung F Kim

2014-10-01

Full Text Available Dopamine neurons are thought to be critical for reward value-based learning by modifying synaptic transmissions in the striatum. Yet, different regions of the striatum seem to guide different kinds of learning. Do dopamine neurons contribute to the regional differences of the striatum in learning? As a first step to answer this question, we examined whether the head and tail of the caudate nucleus of the monkey (Macaca mulatta receive inputs from the same or different dopamine neurons. We chose these caudate regions because we previously showed that caudate head neurons learn values of visual objects quickly and flexibly, whereas caudate tail neurons learn object values slowly but retain them stably. Here we confirmed the functional difference by recording single neuronal activity while the monkey performed the flexible and stable value tasks, and then injected retrograde tracers in the functional domains of caudate head and tail. The projecting dopaminergic neurons were identified using tyrosine hydroxylase immunohistochemistry. We found that two groups of dopamine neurons in the substantia nigra pars compacta project largely separately to the caudate head and tail. These groups of dopamine neurons were mostly separated topographically: head-projecting neurons were located in the rostral-ventral-medial region, while tail-projecting neurons were located in the caudal-dorsal-lateral regions of the substantia nigra. Furthermore, they showed different morphological features: tail-projecting neurons were larger and less circular than head-projecting neurons. Our data raise the possibility that different groups of dopamine neurons selectively guide learning of flexible (short-term and stable (long-term memories of object values.

Learning and memory

Directory of Open Access Journals (Sweden)

P. A. J. Ryke

1989-03-01

Full Text Available Under various circumstances and in different species the outward expression of learning varies considerably, and this has led to the classification of different categories of learning. Just as there is no generally agreed on definition of learning, there is no one system of classification. Types of learning commonly recognized are: Habituation, sensitization, classical conditioning, operant conditioning, trial and error, taste aversion, latent learning, cultural learning, imprinting, insight learning, learning-set learning and instinct. The term memory must include at least two separate processes. It must involve, on the one hand, that of learning something and on the other, at some later date, recalling that thing. What lies between the learning and (he remembering must be some permanent record — a memory trace — within the brain. Memory exists in at least two forms: memory for very recent events (short-term which is relatively labile and easily disruptable; and long-term memory, which is much more stable. Not everything that gets into short-term memory becomes fixed in the long-term store; a filtering mechanism selects things that might be important and discards the rest.

Stable measures of number sense accuracy in math learning disability: Is it time to proceed from basic science to clinical application?

Science.gov (United States)

Júlio-Costa, Annelise; Starling-Alves, Isabella; Lopes-Silva, Júlia Beatriz; Wood, Guilherme; Haase, Vitor Geraldi

2015-12-01

Math learning disability (MLD) or developmental dyscalculia is a highly prevalent and persistent difficulty in learning arithmetic that may be explained by different cognitive mechanisms. The accuracy of the number sense has been implicated by some evidence as a core deficit in MLD. However, research on this topic has been mainly conducted in demographically selected samples, using arbitrary cut-off scores to characterize MLD. The clinical relevance of the association between number sense and MLD remains to be investigated. In this study, we aimed at assessing the stability of a number sense accuracy measure (w) across five experimental sessions, in two clinically defined cases of MLD. Stable measures of number sense accuracy estimate are required to clinically characterize subtypes of MLD and to make theoretical inferences regarding the underlying cognitive mechanisms. G. A. was a 10-year-old boy with MLD in the context of dyslexia and phonological processing impairment and his performance remained steadily in the typical scores range. The performance of H. V., a 9-year-old girl with MLD associated with number sense inaccuracy, remained consistently impaired across measurements, with a nonsignificant tendency to worsen. Qualitatively, H. V.'s performance was also characterized by greater variability across sessions. Concomitant clinical observations suggested that H. V.'s difficulties could be aggravated by developing symptoms of mathematics anxiety. Results in these two cases are in line with the hypotheses that at least two reliable patterns of cognitive impairment may underlie math learning difficulties in MLD, one related to number sense inaccuracy and the other to phonological processing impairment. Additionally, it indicates the need for more translational research in order to examine the usefulness and validity of theoretical advances in numerical cognition to the clinical neuropsychological practice with MLD. © 2015 The Institute of Psychology, Chinese

[Social learning as an uncertainty-reduction strategy: an adaptationist approach].

Science.gov (United States)

Nakanishi, Daisuke; Kameda, Tatsuya; Shinada, Mizuho

2003-04-01

Social learning is an effective mechanism to reduce uncertainty about environmental knowledge, helping individuals adopt an adaptive behavior in the environment at small cost. Although this is evident for learning about temporally stable targets (e.g., acquiring avoidance of toxic foods culturally), the functional value of social learning in a temporally unstable environment is less clear; knowledge acquired by social learning may be outdated. This paper addressed adaptive values of social learning in a non-stationary environment empirically. When individual learning about the non-stationary environment is costly, a hawk-dove-game-like equilibrium is expected to emerge in the population, where members who engage in costly individual learning and members who skip the information search and free-ride on other members' search efforts coexist at a stable ratio. Such a "producer-scrounger" structure should qualify effectiveness of social/cultural learning severely, especially "conformity bias" when using social information (Boyd & Richerson, 1985). We tested these predictions by an experiment implementing a non-stationary uncertain environment in a laboratory. The results supported our thesis. Implications of these findings and some future directions were discussed.

Deep learning

CERN Document Server

Goodfellow, Ian; Courville, Aaron

2016-01-01

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

Comparative Analysis of Kernel Methods for Statistical Shape Learning

National Research Council Canada - National Science Library

Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

2006-01-01

.... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...

Linear Algebra and the Experiences of a "Flipper"

Science.gov (United States)

Wright, Sarah E.

2015-01-01

This paper describes the linear algebra class I taught during Spring 2014 semester at Adelphi University. I discuss the details of how I flipped the class and incorporated elements of inquiry-based learning as well as the reasoning behind specific decisions I made. I give feedback from the students on the success of the course and provide my own…

Study of loading by beam of dual-resonator structure of linear electron accelerator

International Nuclear Information System (INIS)

Milovanov, O.S.; Smirnov, I.A.

1988-01-01

Loading by the beam of the accelerating structure of an Argus dual-resonator linear electron accelerator with a kinetic energy of ∼ 1 MeV and a pulsed beam current of up to 0.5 A is studied experimentally. It is shown that the conditions for stable single-frequency operation of the magnetron are disrupted and the acceleration process is cut off at certain electron-beam currents. Experimental curves of the maximum beam current and maximum electron efficiency of the Argus linear electron accelerator as functions of rf power are given

PENGEMBANGAN BAHAN AJAR MATA KULIAH ALJABAR LINEAR BERBASIS OPEN ENDED

Directory of Open Access Journals (Sweden)

Nurul Farida

2017-01-01

Full Text Available Teaching materials is one important component in learning because teaching materials can be used for independent study. On the other hand, the lack of teaching materials are on open-ended problems leads to an underdevelopment of creativity in learning. With the open-ended problems, students are expected to have more than one solution to solve problems in everyday life, especially in mathematical problem solving. The purpose of this study is to develop teaching materials based on open-ended valildly, practically and effectively in the subject of linear algebra. This research is the development by using Plomp models which consists of three stages: preliminary research, prototyping, and assessment. Data collection technique through observation, questionnaires and tests. The instruments used were observation sheet, questionnaire sheet and a test sheet. Based on result of the research that has been done shows that the teaching materials is based on open-ended in the subject linear algebra that have been developed otherwise valid with a value of 3.43, practice with a value 3,11 or in the percentage reached 77,75%, and effective with value of learning outcomes experiment class (use teaching materials developed higher than control class.

Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning

Directory of Open Access Journals (Sweden)

Shandilya Sharad

2012-10-01

Full Text Available Abstract Background Ventricular Fibrillation (VF is a common presenting dysrhythmia in the setting of cardiac arrest whose main treatment is defibrillation through direct current countershock to achieve return of spontaneous circulation. However, often defibrillation is unsuccessful and may even lead to the transition of VF to more nefarious rhythms such as asystole or pulseless electrical activity. Multiple methods have been proposed for predicting defibrillation success based on examination of the VF waveform. To date, however, no analytical technique has been widely accepted. We developed a unique approach of computational VF waveform analysis, with and without addition of the signal of end-tidal carbon dioxide (PetCO2, using advanced machine learning algorithms. We compare these results with those obtained using the Amplitude Spectral Area (AMSA technique. Methods A total of 90 pre-countershock ECG signals were analyzed form an accessible preshosptial cardiac arrest database. A unified predictive model, based on signal processing and machine learning, was developed with time-series and dual-tree complex wavelet transform features. Upon selection of correlated variables, a parametrically optimized support vector machine (SVM model was trained for predicting outcomes on the test sets. Training and testing was performed with nested 10-fold cross validation and 6–10 features for each test fold. Results The integrative model performs real-time, short-term (7.8 second analysis of the Electrocardiogram (ECG. For a total of 90 signals, 34 successful and 56 unsuccessful defibrillations were classified with an average Accuracy and Receiver Operator Characteristic (ROC Area Under the Curve (AUC of 82.2% and 85%, respectively. Incorporation of the end-tidal carbon dioxide signal boosted Accuracy and ROC AUC to 83.3% and 93.8%, respectively, for a smaller dataset containing 48 signals. VF analysis using AMSA resulted in accuracy and ROC AUC of 64

APPLICATION OF NEURAL NETWORK ALGORITHMS FOR BPM LINEARIZATION

Energy Technology Data Exchange (ETDEWEB)

Musson, John C. [JLAB; Seaton, Chad [JLAB; Spata, Mike F. [JLAB; Yan, Jianxun [JLAB

2012-11-01

Stripline BPM sensors contain inherent non-linearities, as a result of field distortions from the pickup elements. Many methods have been devised to facilitate corrections, often employing polynomial fitting. The cost of computation makes real-time correction difficult, particulalry when integer math is utilized. The application of neural-network technology, particularly the multi-layer perceptron algorithm, is proposed as an efficient alternative for electrode linearization. A process of supervised learning is initially used to determine the weighting coefficients, which are subsequently applied to the incoming electrode data. A non-linear layer, known as an activation layer, is responsible for the removal of saturation effects. Implementation of a perceptron in an FPGA-based software-defined radio (SDR) is presented, along with performance comparisons. In addition, efficient calculation of the sigmoidal activation function via the CORDIC algorithm is presented.

Linear and nonlinear stability of a thermally stratified magnetically driven rotating flow in a cylinder.

Science.gov (United States)

Grants, Ilmars; Gerbeth, Gunter

2010-07-01

The stability of a thermally stratified liquid metal flow is considered numerically. The flow is driven by a rotating magnetic field in a cylinder heated from above and cooled from below. The stable thermal stratification turns out to destabilize the flow. This is explained by the fact that a stable stratification suppresses the secondary meridional flow, thus indirectly enhancing the primary rotation. The instability in the form of Taylor-Görtler rolls is consequently promoted. These rolls can only be excited by finite disturbances in the isothermal flow. A sufficiently strong thermal stratification transforms this nonlinear bypass instability into a linear one reducing, thus, the critical value of the magnetic driving force. A weaker temperature gradient delays the linear instability but makes the bypass transition more likely. We quantify the non-normal and nonlinear components of this transition by direct numerical simulation of the flow response to noise. It is observed that the flow sensitivity to finite disturbances increases considerably under the action of a stable thermal stratification. The capabilities of the random forcing approach to identify disconnected coherent states in a general case are discussed.

Improved pedagogy for linear differential equations by reconsidering how we measure the size of solutions

Science.gov (United States)

Tisdell, Christopher C.

2017-11-01

For over 50 years, the learning of teaching of a priori bounds on solutions to linear differential equations has involved a Euclidean approach to measuring the size of a solution. While the Euclidean approach to a priori bounds on solutions is somewhat manageable in the learning and teaching of the proofs involving second-order, linear problems with constant co-efficients, we believe it is not pedagogically optimal. Moreover, the Euclidean method becomes pedagogically unwieldy in the proofs involving higher-order cases. The purpose of this work is to propose a simpler pedagogical approach to establish a priori bounds on solutions by considering a different way of measuring the size of a solution to linear problems, which we refer to as the Uber size. The Uber form enables a simplification of pedagogy from the literature and the ideas are accessible to learners who have an understanding of the Fundamental Theorem of Calculus and the exponential function, both usually seen in a first course in calculus. We believe that this work will be of mathematical and pedagogical interest to those who are learning and teaching in the area of differential equations or in any of the numerous disciplines where linear differential equations are used.

The linear stability of the Schwarzschild solution to gravitational perturbations in the generalised wave gauge

OpenAIRE

Johnson, Thomas

2018-01-01

In a recent seminal paper \\cite{D--H--R} of Dafermos, Holzegel and Rodnianski the linear stability of the Schwarzschild family of black hole solutions to the Einstein vacuum equations was established by imposing a double null gauge. In this paper we shall prove that the Schwarzschild family is linearly stable as solutions to the Einstein vacuum equations by imposing instead a generalised wave gauge: all sufficiently regular solutions to the system of equations that result from linearising the...

Linear zonal atmospheric prediction for adaptive optics

Science.gov (United States)

McGuire, Patrick C.; Rhoadarmer, Troy A.; Coy, Hanna A.; Angel, J. Roger P.; Lloyd-Hart, Michael

2000-07-01

We compare linear zonal predictors of atmospheric turbulence for adaptive optics. Zonal prediction has the possible advantage of being able to interpret and utilize wind-velocity information from the wavefront sensor better than modal prediction. For simulated open-loop atmospheric data for a 2- meter 16-subaperture AO telescope with 5 millisecond prediction and a lookback of 4 slope-vectors, we find that Widrow-Hoff Delta-Rule training of linear nets and Back- Propagation training of non-linear multilayer neural networks is quite slow, getting stuck on plateaus or in local minima. Recursive Least Squares training of linear predictors is two orders of magnitude faster and it also converges to the solution with global minimum error. We have successfully implemented Amari's Adaptive Natural Gradient Learning (ANGL) technique for a linear zonal predictor, which premultiplies the Delta-Rule gradients with a matrix that orthogonalizes the parameter space and speeds up the training by two orders of magnitude, like the Recursive Least Squares predictor. This shows that the simple Widrow-Hoff Delta-Rule's slow convergence is not a fluke. In the case of bright guidestars, the ANGL, RLS, and standard matrix-inversion least-squares (MILS) algorithms all converge to the same global minimum linear total phase error (approximately 0.18 rad2), which is only approximately 5% higher than the spatial phase error (approximately 0.17 rad2), and is approximately 33% lower than the total 'naive' phase error without prediction (approximately 0.27 rad2). ANGL can, in principle, also be extended to make non-linear neural network training feasible for these large networks, with the potential to lower the predictor error below the linear predictor error. We will soon scale our linear work to the approximately 108-subaperture MMT AO system, both with simulations and real wavefront sensor data from prime focus.

Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning

DEFF Research Database (Denmark)

Chakraborty, Rudrasis; Hauberg, Søren; Vemuri, Baba C.

2017-01-01

Principal Component Analysis (PCA) is a fundamental method for estimating a linear subspace approximation to high-dimensional data. Many algorithms exist in literature to achieve a statistically robust version of PCA called RPCA. In this paper, we present a geometric framework for computing the p...

On Stable Wall Boundary Conditions for the Hermite Discretization of the Linearised Boltzmann Equation

Science.gov (United States)

Sarna, Neeraj; Torrilhon, Manuel

2018-01-01

We define certain criteria, using the characteristic decomposition of the boundary conditions and energy estimates, which a set of stable boundary conditions for a linear initial boundary value problem, involving a symmetric hyperbolic system, must satisfy. We first use these stability criteria to show the instability of the Maxwell boundary conditions proposed by Grad (Commun Pure Appl Math 2(4):331-407, 1949). We then recognise a special block structure of the moment equations which arises due to the recursion relations and the orthogonality of the Hermite polynomials; the block structure will help us in formulating stable boundary conditions for an arbitrary order Hermite discretization of the Boltzmann equation. The formulation of stable boundary conditions relies upon an Onsager matrix which will be constructed such that the newly proposed boundary conditions stay close to the Maxwell boundary conditions at least in the lower order moments.

New binary linear codes which are dual transforms of good codes

NARCIS (Netherlands)

Jaffe, D.B.; Simonis, J.

1999-01-01

If C is a binary linear code, one may choose a subset S of C, and form a new code CST which is the row space of the matrix having the elements of S as its columns. One way of picking S is to choose a subgroup H of Aut(C) and let S be some H-stable subset of C. Using (primarily) this method for

A linear dynamic model for rotor-spun composite yarn spinning process

International Nuclear Information System (INIS)

Yang, R H; Wang, S Y

2008-01-01

A linear dynamic model is established for the stable rotor-spun composite yarn spinning process. Approximate oscillating frequencies in the vertical and horizontal directions are obtained. By suitable choice of certain processing parameters, the mixture construction after the convergent point can be optimally matched. The presented study is expected to provide a general pathway to understand the motion of the rotor-spun composite yarn spinning process

Caution on the use of liquid nitrogen traps in stable hydrogen isotope-ratio mass spectrometry

Science.gov (United States)

Coplen, Tyler B.; Qi, Haiping

2010-01-01

An anomalous stable hydrogen isotopic fractionation of 4 ‰ in gaseous hydrogen has been correlated with the process of adding liquid nitrogen (LN2) to top off the dewar of a stainless-steel water trap on a gaseous hydrogen-water platinum equilibration system. Although the cause of this isotopic fractionation is unknown, its effect can be mitigated by (1) increasing the capacity of any dewars so that they do not need to be filled during a daily analytic run, (2) interspersing isotopic reference waters among unknowns, and (3) applying a linear drift correction and linear normalization to isotopic results with a program such as Laboratory Information Management System (LIMS) for Light Stable Isotopes. With adoption of the above guidelines, measurement uncertainty can be substantially improved. For example, the long-term (months to years) δ2H reproducibility (1& sigma; standard deviation) of nine local isotopic reference waters analyzed daily improved substantially from about 1‰ to 0.58 ‰. This isotopically fractionating mechanism might affect other isotope-ratio mass spectrometers in which LN2 is used as a moisture trap for gaseous hydrogen

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

Science.gov (United States)

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

Gauging the likelihood of stable cavitation from ultrasound contrast agents.

Science.gov (United States)

Bader, Kenneth B; Holland, Christy K

2013-01-07

The mechanical index (MI) was formulated to gauge the likelihood of adverse bioeffects from inertial cavitation. However, the MI formulation did not consider bubble activity from stable cavitation. This type of bubble activity can be readily nucleated from ultrasound contrast agents (UCAs) and has the potential to promote beneficial bioeffects. Here, the presence of stable cavitation is determined numerically by tracking the onset of subharmonic oscillations within a population of bubbles for frequencies up to 7 MHz and peak rarefactional pressures up to 3 MPa. In addition, the acoustic pressure rupture threshold of an UCA population was determined using the Marmottant model. The threshold for subharmonic emissions of optimally sized bubbles was found to be lower than the inertial cavitation threshold for all frequencies studied. The rupture thresholds of optimally sized UCAs were found to be lower than the threshold for subharmonic emissions for either single cycle or steady state acoustic excitations. Because the thresholds of both subharmonic emissions and UCA rupture are linearly dependent on frequency, an index of the form I(CAV) = P(r)/f (where P(r) is the peak rarefactional pressure in MPa and f is the frequency in MHz) was derived to gauge the likelihood of subharmonic emissions due to stable cavitation activity nucleated from UCAs.

Visualizing the inner product space ℝm×n in a MATLAB-assisted linear algebra classroom

Science.gov (United States)

Caglayan, Günhan

2018-05-01

This linear algebra note offers teaching and learning ideas in the treatment of the inner product space ? in a technology-supported learning environment. Classroom activities proposed in this note demonstrate creative ways of integrating MATLAB technology into various properties of Frobenius inner product as visualization tools that complement the algebraic approach. As implemented in linear algebra lessons in a university in the Unites States, the article also incorporates algebraic and visual work of students who experienced these activities with MATLAB software. The connection between the Frobenius norm and the Euclidean norm is also emphasized.

Associative Learning Through Acquired Salience.

Science.gov (United States)

Treviño, Mario

2015-01-01

Most associative learning studies describe the salience of stimuli as a fixed learning-rate parameter. Presumptive saliency signals, however, have also been linked to motivational and attentional processes. An interesting possibility, therefore, is that discriminative stimuli could also acquire salience as they become powerful predictors of outcomes. To explore this idea, we first characterized and extracted the learning curves from mice trained with discriminative images offering varying degrees of structural similarity. Next, we fitted a linear model of associative learning coupled to a series of mathematical representations for stimulus salience. We found that the best prediction, from the set of tested models, was one in which the visual salience depended on stimulus similarity and a non-linear function of the associative strength. Therefore, these analytic results support the idea that the net salience of a stimulus depends both on the items' effective salience and the motivational state of the subject that learns about it. Moreover, this dual salience model can explain why learning about a stimulus not only depends on the effective salience during acquisition but also on the specific learning trajectory that was used to reach this state. Our mathematical description could be instrumental for understanding aberrant salience acquisition under stressful situations and in neuropsychiatric disorders like schizophrenia, obsessive-compulsive disorder, and addiction.

Structure and dynamics of ion clusters in linear octupole traps: Phase diagrams, chirality, and melting mechanisms

International Nuclear Information System (INIS)

Yurtsever, E.; Onal, E. D.; Calvo, F.

2011-01-01

The stable structures and melting dynamics of clusters of identical ions bound by linear octupole radiofrequency traps are theoretically investigated by global optimization methods and molecular dynamics simulations. By varying the cluster sizes in the range of 10-1000 ions and the extent of trap anisotropy by more than one order of magnitude, we find a broad variety of stable structures based on multiple rings at small sizes evolving into tubular geometries at large sizes. The binding energy of these clusters is well represented by two contributions arising from isotropic linear and octupolar traps. The structures generally exhibit strong size effects, and chiral arrangements spontaneously emerge in many crystals. Sufficiently large clusters form nested, coaxial tubes with different thermal stabilities. As in isotropic octupolar clusters, the inner tubes melt at temperatures that are lower than the overall melting point.

Effect of linear energy on the properties of an AL alloy in DPMIG welding

Science.gov (United States)

Liao, Tianfa; Jin, Li; Xue, Jiaxiang

2018-01-01

The effect of different linear energy parameters on the DPMIG welding performance of AA1060 aluminium alloy is studied in this paper. The stability of the welding process is verified with a Labview electrical signal acquisition system, and the microstructure and tensile properties of the welded joint are studied via optical microscopy, scanning electron microscopy and electrical tensile tests. The test results show that the welding process for the DPMIG methods stable and that the weld beads appear as scales. Tensile strength results indicate that, with increasing linear energy, the tensile strength first increases and then decreases. The tensile strength of the joint is maximized when the linear energy is 120.5 J / mm-1.

Positivity of linear maps under tensor powers

Energy Technology Data Exchange (ETDEWEB)

Müller-Hermes, Alexander, E-mail: muellerh@ma.tum.de; Wolf, Michael M., E-mail: m.wolf@tum.de [Zentrum Mathematik, Technische Universität München, 85748 Garching (Germany); Reeb, David, E-mail: reeb.qit@gmail.com [Zentrum Mathematik, Technische Universität München, 85748 Garching (Germany); Institute for Theoretical Physics, Leibniz Universität Hannover, 30167 Hannover (Germany)

2016-01-15

We investigate linear maps between matrix algebras that remain positive under tensor powers, i.e., under tensoring with n copies of themselves. Completely positive and completely co-positive maps are trivial examples of this kind. We show that for every n ∈ ℕ, there exist non-trivial maps with this property and that for two-dimensional Hilbert spaces there is no non-trivial map for which this holds for all n. For higher dimensions, we reduce the existence question of such non-trivial “tensor-stable positive maps” to a one-parameter family of maps and show that an affirmative answer would imply the existence of non-positive partial transpose bound entanglement. As an application, we show that any tensor-stable positive map that is not completely positive yields an upper bound on the quantum channel capacity, which for the transposition map gives the well-known cb-norm bound. We, furthermore, show that the latter is an upper bound even for the local operations and classical communications-assisted quantum capacity, and that moreover it is a strong converse rate for this task.

Positivity of linear maps under tensor powers

International Nuclear Information System (INIS)

Müller-Hermes, Alexander; Wolf, Michael M.; Reeb, David

2016-01-01

We investigate linear maps between matrix algebras that remain positive under tensor powers, i.e., under tensoring with n copies of themselves. Completely positive and completely co-positive maps are trivial examples of this kind. We show that for every n ∈ ℕ, there exist non-trivial maps with this property and that for two-dimensional Hilbert spaces there is no non-trivial map for which this holds for all n. For higher dimensions, we reduce the existence question of such non-trivial “tensor-stable positive maps” to a one-parameter family of maps and show that an affirmative answer would imply the existence of non-positive partial transpose bound entanglement. As an application, we show that any tensor-stable positive map that is not completely positive yields an upper bound on the quantum channel capacity, which for the transposition map gives the well-known cb-norm bound. We, furthermore, show that the latter is an upper bound even for the local operations and classical communications-assisted quantum capacity, and that moreover it is a strong converse rate for this task

Non-linear neutron star oscillations viewed as deviations from an equilibrium state

International Nuclear Information System (INIS)

Sperhake, U

2002-01-01

A numerical technique is presented which facilitates the evolution of non-linear neutron star oscillations with a high accuracy essentially independent of the oscillation amplitude. We apply this technique to radial neutron star oscillations in a Lagrangian formulation and demonstrate the superior performance of the new scheme compared with 'conventional' techniques. The key feature of our approach is to describe the evolution in terms of deviations from an equilibrium configuration. In contrast to standard perturbation analysis we keep all higher order terms in the evolution equations and thus obtain a fully non-linear description. The advantage of our scheme lies in the elimination of background terms from the equations and the associated numerical errors. The improvements thus achieved will be particularly significant in the study of mildly non-linear effects where the amplitude of the dynamic signal is small compared with the equilibrium values but large enough to warrant non-linear effects. We apply the new technique to the study of non-linear coupling of Eigenmodes and non-linear effects in the oscillations of marginally stable neutron stars. We find non-linear effects in low amplitude oscillations to be particularly pronounced in the range of modes with vanishing frequency which typically mark the onset of instability. (author)

The response of a linear monostable system and its application in parameters estimation for PSK signals

International Nuclear Information System (INIS)

Duan, Chaowei; Zhan, Yafeng

2016-01-01

The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance. - Highlights: • The response of a linear monostable system driven with a periodic signal and an additive white Gaussian noise is analyzed. • The optimal parameter of this linear monostable system to maximum the output SNR-gain is obtained. • Application of this linear monostable system in parameters estimation algorithm for PSK signals obtains performance improvement.

Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

DEFF Research Database (Denmark)

Thrane, Jakob; Wass, Jesper; Piels, Molly

2017-01-01

Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

Reduced α-stable dynamics for multiple time scale systems forced with correlated additive and multiplicative Gaussian white noise

Science.gov (United States)

Thompson, William F.; Kuske, Rachel A.; Monahan, Adam H.

2017-11-01

Stochastic averaging problems with Gaussian forcing have been the subject of numerous studies, but far less attention has been paid to problems with infinite-variance stochastic forcing, such as an α-stable noise process. It has been shown that simple linear systems driven by correlated additive and multiplicative (CAM) Gaussian noise, which emerge in the context of reduced atmosphere and ocean dynamics, have infinite variance in certain parameter regimes. In this study, we consider the stochastic averaging of systems where a linear CAM noise process in the infinite variance parameter regime drives a comparatively slow process. We use (semi)-analytical approximations combined with numerical illustrations to compare the averaged process to one that is forced by a white α-stable process, demonstrating consistent properties in the case of large time-scale separation. We identify the conditions required for the fast linear CAM process to have such an influence in driving a slower process and then derive an (effectively) equivalent fast, infinite-variance process for which an existing stochastic averaging approximation is readily applied. The results are illustrated using numerical simulations of a set of example systems.

Emergent theory and technology in e-learning

NARCIS (Netherlands)

Browaeys, M.-J.; Wahyudi, S.

2006-01-01

E-learning should be approached via a new paradigm, one where instruction and information are involved in a recursive process, an approach which counters the concept of linearity. New ways of thinking about how people learn and new technologies favour the emergence of principles of e-learning that

A Multidimensional/Non-Linear Teaching and Learning Model: Teaching and Learning Music in an Authentic and Holistic Context

Science.gov (United States)

Crawford, Renée

2014-01-01

This article discusses the conceptual framework that leads to the design of a teaching and learning model as part of a recent ethnographic study that considered the effectiveness of current Victorian government secondary school music teaching and learning practices when engaged with technology. The philosophical and theoretical basis for this…

Active Learning Using Hint Information.

Science.gov (United States)

Li, Chun-Liang; Ferng, Chun-Sung; Lin, Hsuan-Tien

2015-08-01

The abundance of real-world data and limited labeling budget calls for active learning, an important learning paradigm for reducing human labeling efforts. Many recently developed active learning algorithms consider both uncertainty and representativeness when making querying decisions. However, exploiting representativeness with uncertainty concurrently usually requires tackling sophisticated and challenging learning tasks, such as clustering. In this letter, we propose a new active learning framework, called hinted sampling, which takes both uncertainty and representativeness into account in a simpler way. We design a novel active learning algorithm within the hinted sampling framework with an extended support vector machine. Experimental results validate that the novel active learning algorithm can result in a better and more stable performance than that achieved by state-of-the-art algorithms. We also show that the hinted sampling framework allows improving another active learning algorithm designed from the transductive support vector machine.

Adaptive H∞ synchronization of chaotic systems via linear and nonlinear feedback control

International Nuclear Information System (INIS)

Fu Shi-Hui; Lu Qi-Shao; Du Ying

2012-01-01

Adaptive H ∞ synchronization of chaotic systems via linear and nonlinear feedback control is investigated. The chaotic systems are redesigned by using the generalized Hamiltonian systems and observer approach. Based on Lyapunov's stability theory, linear and nonlinear feedback control of adaptive H ∞ synchronization is established in order to not only guarantee stable synchronization of both master and slave systems but also reduce the effect of external disturbance on an H ∞ -norm constraint. Adaptive H ∞ synchronization of chaotic systems via three kinds of control is investigated with applications to Lorenz and Chen systems. Numerical simulations are also given to identify the effectiveness of the theoretical analysis. (general)

Linear Algebra and Smarandache Linear Algebra

OpenAIRE

Vasantha, Kandasamy

2003-01-01

The present book, on Smarandache linear algebra, not only studies the Smarandache analogues of linear algebra and its applications, it also aims to bridge the need for new research topics pertaining to linear algebra, purely in the algebraic sense. We have introduced Smarandache semilinear algebra, Smarandache bilinear algebra and Smarandache anti-linear algebra and their fuzzy equivalents. Moreover, in this book, we have brought out the study of linear algebra and vector spaces over finite p...

Common SAR Derived from Linear and Non-linear QSAR Studies on AChE Inhibitors used in the Treatment of Alzheimer's Disease.

Science.gov (United States)

Pulikkal, Babitha Pallikkara; Marunnan, Sahila Mohammed; Bandaru, Srinivas; Yadav, Mukesh; Nayarisseri, Anuraj; Sureshkumar, Sivanpillai

2017-11-14

Deficits in cholinergic neurotransmission due to the degeneration of cholinergic neurons in the brain are believed to be one of the major causes of the memory impairments associated with AD. Targeting acetyl cholinesterase (AChE) surfaced as a potential therapeutic target in the treatment of Alzheimer's disease. The present study is pursued to develop quantitative structure activity relationship (QSAR) models to determine chemical descriptors responsible for AChE activity. Two different sets of AChE inhibitors, dataset-I (30 compounds) and dataset-II (20 compounds) were investigated through MLR aided linear and SVM aided non-linear QSAR models. The obtained QSAR models were found statistically fit, stable and predictive on validation scales. These QSAR models were further investigated for their common structure-activity relationship in terms of overlapping molecular descriptors selection. Atomic mass weighted 3D Morse descriptors (MATS5m) and Radial Distribution Function (RDF045m) descriptors were found in common SAR for both the datasets. Electronegativity weighted (MATS5e, HATSe, and Mor17e) descriptors have also been identified in regulative roles towards endpoint values of dataset-I and dataset-II. The common SAR identified in these linear and non-linear QSAR models could be utilized to design novel inhibitors of AChE with improved biological activity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Picosecond, single pulse electron linear accelerator

International Nuclear Information System (INIS)

Kikuchi, Riichi; Kawanishi, Masaharu

1979-01-01

The picosecond, single pulse electron linear accelerators, are described, which were installed in the Nuclear Engineering Laboratory of the University of Tokyo and in the Nuclear Radiation Laboratory of the Osaka University. The purpose of the picosecond, single pulse electron linear accelerators is to investigate the very short time reaction of the substances, into which gamma ray or electron beam enters. When the electrons in substances receive radiation energy, the electrons get high kinetic energy, and the energy and the electric charge shift, at last to the quasi-stable state. This transient state can be experimented with these special accelerators very accurately, during picoseconds, raising the accuracy of the time of incidence of radiation and also raising the accuracy of observation time. The outline of these picosecond, single pulse electron linear accelerators of the University of Tokyo and the Osaka University, including the history, the systems and components and the output beam characteristics, are explained. For example, the maximum energy 30 -- 35 MeV, the peak current 1 -- 8 n C, the pulse width 18 -- 40 ps, the pulse repetition rate 200 -- 720 pps, the energy spectrum 1 -- 1.8% and the output beam diameter 2 -- 5 mm are shown as the output beam characteristics of the accelerators in both universities. The investigations utilizing the picosecond single pulse electron linear accelerators, such as the investigation of short life excitation state by pulsed radiation, the dosimetry study of pulsed radiation, and the investigation of the transforming mechanism and the development of the transforming technology from picosecond, single pulse electron beam to X ray, vacuum ultraviolet ray and visual ray, are described. (Nakai, Y.)

The response of a linear monostable system and its application in parameters estimation for PSK signals

Science.gov (United States)

Duan, Chaowei; Zhan, Yafeng

2016-03-01

The output characteristics of a linear monostable system driven with a periodic signal and an additive white Gaussian noise are studied in this paper. Theoretical analysis shows that the output signal-to-noise ratio (SNR) decreases monotonously with the increasing noise intensity but the output SNR-gain is stable. Inspired by this high SNR-gain phenomenon, this paper applies the linear monostable system in the parameters estimation algorithm for phase shift keying (PSK) signals and improves the estimation performance.

Entropy Stable Spectral Collocation Schemes for the Navier-Stokes Equations: Discontinuous Interfaces

Science.gov (United States)

Carpenter, Mark H.; Fisher, Travis C.; Nielsen, Eric J.; Frankel, Steven H.

2013-01-01

Nonlinear entropy stability and a summation-by-parts framework are used to derive provably stable, polynomial-based spectral collocation methods of arbitrary order. The new methods are closely related to discontinuous Galerkin spectral collocation methods commonly known as DGFEM, but exhibit a more general entropy stability property. Although the new schemes are applicable to a broad class of linear and nonlinear conservation laws, emphasis herein is placed on the entropy stability of the compressible Navier-Stokes equations.

A TLBO based gradient descent learning-functional link higher order ANN: An efficient model for learning from non-linear data

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.

On Active Surge Control of Compression Systems via Characteristic Linearization and Model Nonlinearity Cancellation

Directory of Open Access Journals (Sweden)

Yohannes S.M. Simamora

2014-09-01

Full Text Available A simple approach of active surge control of compression systems is presented. Specifically, nonlinear components of the pressure ratio and rotating speed states of the Moore-Greitzer model are transferred into the input vectors. Subsequently, the compressor characteristic is linearized into two modes, which describe the stable region and the unstable region respectively. As a result, the system’s state and input matrices both appear linear, to which linear realization and analysis are applicable. A linear quadratic regulator plus integrator is then chosen as closed-loop controller. By simulation it was shown that the modified model and characteristics can describe surge behavior, while the closed-loop controller can stabilize the system in the unstable operating region. The last-mentioned was achieved when massflow was 5.38 per cent less than the surge point.

Young children make their gestural communication systems more language-like: segmentation and linearization of semantic elements in motion events.

Science.gov (United States)

Clay, Zanna; Pople, Sally; Hood, Bruce; Kita, Sotaro

2014-08-01

Research on Nicaraguan Sign Language, created by deaf children, has suggested that young children use gestures to segment the semantic elements of events and linearize them in ways similar to those used in signed and spoken languages. However, it is unclear whether this is due to children's learning processes or to a more general effect of iterative learning. We investigated whether typically developing children, without iterative learning, segment and linearize information. Gestures produced in the absence of speech to express a motion event were examined in 4-year-olds, 12-year-olds, and adults (all native English speakers). We compared the proportions of gestural expressions that segmented semantic elements into linear sequences and that encoded them simultaneously. Compared with adolescents and adults, children reshaped the holistic stimuli by segmenting and recombining their semantic features into linearized sequences. A control task on recognition memory ruled out the possibility that this was due to different event perception or memory. Young children spontaneously bring fundamental properties of language into their communication system. © The Author(s) 2014.

Optimal approximation of linear systems by artificial immune response

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.

A Practical Approach to Inquiry-Based Learning in Linear Algebra

Science.gov (United States)

Chang, J.-M.

2011-01-01

Linear algebra has become one of the most useful fields of mathematics since last decade, yet students still have trouble seeing the connection between some of the abstract concepts and real-world applications. In this article, we propose the use of thought-provoking questions in lesson designs to allow two-way communications between instructors…

Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

Directory of Open Access Journals (Sweden)

Wenjie Lou

2016-02-01

Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

Incorporation of diet information derived from Bayesian stable isotope mixing models into mass-balanced marine ecosystem models: A case study from the Marennes-Oleron Estuary, France

Science.gov (United States)

We investigated the use of output from Bayesian stable isotope mixing models as constraints for a linear inverse food web model of a temperate intertidal seagrass system in the Marennes-Oléron Bay, France. Linear inverse modeling (LIM) is a technique that estimates a complete net...

INTELLIGENT FRACTIONAL ORDER ITERATIVE LEARNING CONTROL USING FEEDBACK LINEARIZATION FOR A SINGLE-LINK ROBOT

Directory of Open Access Journals (Sweden)

Iman Ghasemi

2017-05-01

Full Text Available In this paper, iterative learning control (ILC is combined with an optimal fractional order derivative (BBO-Da-type ILC and optimal fractional and proportional-derivative (BBO-PDa-type ILC. In the update law of Arimoto's derivative iterative learning control, a first order derivative of tracking error signal is used. In the proposed method, fractional order derivative of the error signal is stated in term of 'sa' where  to update iterative learning control law. Two types of fractional order iterative learning control namely PDa-type ILC and Da-type ILC are gained for different value of a. In order to improve the performance of closed-loop control system, coefficients of both  and  learning law i.e. proportional , derivative  and  are optimized using Biogeography-Based optimization algorithm (BBO. Outcome of the simulation results are compared with those of the conventional fractional order iterative learning control to verify effectiveness of BBO-Da-type ILC and BBO-PDa-type ILC

Magnetic Properties of linear chain compounds formed by lanthanide (III) ions and nitronyl-nitroxide radicals

Energy Technology Data Exchange (ETDEWEB)

Benelli, C.; Caneschi, A.; Gatteschi, D.; Pardi, L. (Florence Univ. (IT)); Rey, P. (CEA Centre d' Etudes Nucleaires de Grenoble, 38 (FR). Dept. de Recherche Fondamentale)

1988-12-01

The magnetic properties of novel linear chain compounds containing lanthanide (III) ions (gadolinium, europium) coupled to stable nitronyl-nitroxide radicals are reported. The metal ions and the radicals are regularly alternating along the chain. The magnetic behaviors appears to be dominated by antiferromagnetic interactions between the radicals.

Magnetic Properties of linear chain compounds formed by lanthanide (III) ions and nitronyl-nitroxide radicals

International Nuclear Information System (INIS)

Benelli, C.; Caneschi, A.; Gatteschi, D.; Pardi, L.; Rey, P.

1988-01-01

The magnetic properties of novel linear chain compounds containing lanthanide (III) ions (gadolinium, europium) coupled to stable nitronyl-nitroxide radicals are reported. The metal ions and the radicals are regularly alternating along the chain. The magnetic behaviors appears to be dominated by antiferromagnetic interactions between the radicals

Normalization Methods and Selection Strategies for Reference Materials in Stable Isotope Analyses - Review

International Nuclear Information System (INIS)

Skrzypek, G.; Sadler, R.; Paul, D.; Forizs, I.

2011-01-01

A stable isotope analyst has to make a number of important decisions regarding how to best determine the 'true' stable isotope composition of analysed samples in reference to an international scale. It has to be decided which reference materials should be used, the number of reference materials and how many repetitions of each standard is most appropriate for a desired level of precision, and what normalization procedure should be selected. In this paper we summarise what is known about propagation of uncertainties associated with normalization procedures and propagation of uncertainties associated with reference materials used as anchors for the determination of 'true' values for δ''1''3C and δ''1''8O. Normalization methods Several normalization methods transforming the 'raw' value obtained from mass spectrometers to one of the internationally recognized scales has been developed. However, as summarised by Paul et al. different normalization transforms alone may lead to inconsistencies between laboratories. The most common normalization procedures are: single-point anchoring (versus working gas and certified reference standard), modified single-point normalization, linear shift between the measured and the true isotopic composition of two certified reference standards, two-point and multipoint linear normalization methods. The accuracy of these various normalization methods has been compared by using analytical laboratory data by Paul et al., with the single-point and normalization versus tank calibrations resulting in the largest normalization errors, and that also exceed the analytical uncertainty recommended for δ 13 C. The normalization error depends greatly on the relative differences between the stable isotope composition of the reference material and the sample. On the other hand, the normalization methods using two or more certified reference standards produces a smaller normalization error, if the reference materials are bracketing the whole range of

Improved Pedagogy for Linear Differential Equations by Reconsidering How We Measure the Size of Solutions

Science.gov (United States)

Tisdell, Christopher C.

2017-01-01

For over 50 years, the learning of teaching of "a priori" bounds on solutions to linear differential equations has involved a Euclidean approach to measuring the size of a solution. While the Euclidean approach to "a priori" bounds on solutions is somewhat manageable in the learning and teaching of the proofs involving…

Non linear dynamics of magnetic islands in fusion plasmas

International Nuclear Information System (INIS)

Meshcheriakov, D.

2012-10-01

In this thesis we investigate the issues of linear stability of the tearing modes in a presence of both curvature and diamagnetic rotation using the non linear full-MHD toroidal code XTOR-2F, which includes anisotropic heat transport, diamagnetic and geometrical effects. This analysis is applied to one of the fully non-inductive discharges on Tore-Supra. Such experiments are crucially important to demonstrate reactor scale steady state operation for the tokamak. The possibility of a full linear stabilization of the tearing modes by diamagnetic rotation in the presence of toroidal curvature is shown. The stabilization threshold does not follow the classical scaling law connecting the growth rate of islands to plasma conductivity, measured here by the Lundquist number (S). However, for numerical reasons, the conductivity used in the simulations is lower than that of the experiment, which raises the question of extrapolation of the obtained results to the experimental situation. The extrapolation of the obtained results requires simulations with several different conductivities. It predicts that the mode at q = 2 surface to be stable at value of diamagnetic frequency consistent with the experimental one at S = S(exp). In the linearly stable domain, the mode is metastable: saturation level depends on the seed island size. In the non linear regime, the saturation of n=1, m=2 mode is found to be strongly reduced by diamagnetic rotation and by Lundquist number. However, the extrapolation to the experimental situation shows that if the island is destabilized, it will saturate at a detectable level for the Tore Supra diagnostic. For a large plasma aspect ratio (i.e. weak curvature effects), the reduction of the saturated width by diamagnetic frequency takes the form of a jump reminiscent of multiple states evidenced in slab geometry case. The question of extrapolation of the obtained results towards future generation of fusion devices is also addressed. In particular, for

A novel Lagrangian approach for the stable numerical simulation of fault and fracture mechanics

Energy Technology Data Exchange (ETDEWEB)

Franceschini, Andrea; Ferronato, Massimiliano, E-mail: massimiliano.ferronato@unipd.it; Janna, Carlo; Teatini, Pietro

2016-06-01

The simulation of the mechanics of geological faults and fractures is of paramount importance in several applications, such as ensuring the safety of the underground storage of wastes and hydrocarbons or predicting the possible seismicity triggered by the production and injection of subsurface fluids. However, the stable numerical modeling of ground ruptures is still an open issue. The present work introduces a novel formulation based on the use of the Lagrange multipliers to prescribe the constraints on the contact surfaces. The variational formulation is modified in order to take into account the frictional work along the activated fault portion according to the principle of maximum plastic dissipation. The numerical model, developed in the framework of the Finite Element method, provides stable solutions with a fast convergence of the non-linear problem. The stabilizing properties of the proposed model are emphasized with the aid of a realistic numerical example dealing with the generation of ground fractures due to groundwater withdrawal in arid regions. - Highlights: • A numerical model is developed for the simulation of fault and fracture mechanics. • The model is implemented in the framework of the Finite Element method and with the aid of Lagrange multipliers. • The proposed formulation introduces a new contribution due to the frictional work on the portion of activated fault. • The resulting algorithm is highly non-linear as the portion of activated fault is itself unknown. • The numerical solution is validated against analytical results and proves to be stable also in realistic applications.

A novel Lagrangian approach for the stable numerical simulation of fault and fracture mechanics

International Nuclear Information System (INIS)

Franceschini, Andrea; Ferronato, Massimiliano; Janna, Carlo; Teatini, Pietro

2016-01-01

The simulation of the mechanics of geological faults and fractures is of paramount importance in several applications, such as ensuring the safety of the underground storage of wastes and hydrocarbons or predicting the possible seismicity triggered by the production and injection of subsurface fluids. However, the stable numerical modeling of ground ruptures is still an open issue. The present work introduces a novel formulation based on the use of the Lagrange multipliers to prescribe the constraints on the contact surfaces. The variational formulation is modified in order to take into account the frictional work along the activated fault portion according to the principle of maximum plastic dissipation. The numerical model, developed in the framework of the Finite Element method, provides stable solutions with a fast convergence of the non-linear problem. The stabilizing properties of the proposed model are emphasized with the aid of a realistic numerical example dealing with the generation of ground fractures due to groundwater withdrawal in arid regions. - Highlights: • A numerical model is developed for the simulation of fault and fracture mechanics. • The model is implemented in the framework of the Finite Element method and with the aid of Lagrange multipliers. • The proposed formulation introduces a new contribution due to the frictional work on the portion of activated fault. • The resulting algorithm is highly non-linear as the portion of activated fault is itself unknown. • The numerical solution is validated against analytical results and proves to be stable also in realistic applications.

Linear Polarization Properties of Parsec-Scale AGN Jets

Directory of Open Access Journals (Sweden)

Alexander B. Pushkarev

2017-12-01

Full Text Available We used 15 GHz multi-epoch Very Long Baseline Array (VLBA polarization sensitive observations of 484 sources within a time interval 1996–2016 from the MOJAVE program, and also from the NRAO data archive. We have analyzed the linear polarization characteristics of the compact core features and regions downstream, and their changes along and across the parsec-scale active galactic nuclei (AGN jets. We detected a significant increase of fractional polarization with distance from the radio core along the jet as well as towards the jet edges. Compared to quasars, BL Lacs have a higher degree of polarization and exhibit more stable electric vector position angles (EVPAs in their core features and a better alignment of the EVPAs with the local jet direction. The latter is accompanied by a higher degree of linear polarization, suggesting that compact bright jet features might be strong transverse shocks, which enhance magnetic field regularity by compression.

Every apple has a voice: using stable isotopes to teach about food sourcing and the water cycle

Science.gov (United States)

Oerter, Erik; Malone, Molly; Putman, Annie; Drits-Esser, Dina; Stark, Louisa; Bowen, Gabriel

2017-07-01

Agricultural crops such as fruits take up irrigation and meteoric water and incorporate it into their tissue (fruit water) during growth, and the geographic origin of a fruit may be traced by comparing the H and O stable isotope composition (δ2H and δ18O values) of fruit water to the global geospatial distribution of H and O stable isotopes in precipitation. This connection between common fruits and the global water cycle provides an access point to connect with a variety of demographic groups to educate about isotope hydrology and the water cycle. Within the context of a 1-day outreach activity designed for a wide spectrum of participants (high school students, undergraduate students, high school science teachers) we developed introductory lecture materials, in-class participatory demonstrations of fruit water isotopic measurement in real time, and a computer lab exercise to couple actual fruit water isotope data with open-source online geospatial analysis software. We assessed learning outcomes with pre- and post-tests tied to learning objectives, as well as participant feedback surveys. Results indicate that this outreach activity provided effective lessons on the basics of stable isotope hydrology and the water cycle. However, the computer lab exercise needs to be more specifically tailored to the abilities of each participant group. This pilot study provides a foundation for further development of outreach materials that can effectively engage a range of participant groups in learning about the water cycle and the ways in which humans modify the water cycle through agricultural activity.

Every apple has a voice: using stable isotopes to teach about food sourcing and the water cycle

Directory of Open Access Journals (Sweden)

E. Oerter

2017-07-01

Full Text Available Agricultural crops such as fruits take up irrigation and meteoric water and incorporate it into their tissue (fruit water during growth, and the geographic origin of a fruit may be traced by comparing the H and O stable isotope composition (δ2H and δ18O values of fruit water to the global geospatial distribution of H and O stable isotopes in precipitation. This connection between common fruits and the global water cycle provides an access point to connect with a variety of demographic groups to educate about isotope hydrology and the water cycle. Within the context of a 1-day outreach activity designed for a wide spectrum of participants (high school students, undergraduate students, high school science teachers we developed introductory lecture materials, in-class participatory demonstrations of fruit water isotopic measurement in real time, and a computer lab exercise to couple actual fruit water isotope data with open-source online geospatial analysis software. We assessed learning outcomes with pre- and post-tests tied to learning objectives, as well as participant feedback surveys. Results indicate that this outreach activity provided effective lessons on the basics of stable isotope hydrology and the water cycle. However, the computer lab exercise needs to be more specifically tailored to the abilities of each participant group. This pilot study provides a foundation for further development of outreach materials that can effectively engage a range of participant groups in learning about the water cycle and the ways in which humans modify the water cycle through agricultural activity.

Class of unconditionally stable second-order implicit schemes for hyperbolic and parabolic equations

International Nuclear Information System (INIS)

Lui, H.C.

The linearized Burgers equation is considered as a model u/sub t/ tau/sub x/ = bu/sub xx/, where the subscripts t and x denote the derivatives of the function u with respect to time t and space x; a and b are constants (b greater than or equal to 0). Numerical schemes for solving the equation are described that are second-order accurate, unconditionally stable, and dissipative of higher order. (U.S.)

Linear Prediction Using Refined Autocorrelation Function

Directory of Open Access Journals (Sweden)

M. Shahidur Rahman

2007-07-01

Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.

Linearized motion estimation for articulated planes.

Science.gov (United States)

Datta, Ankur; Sheikh, Yaser; Kanade, Takeo

2011-04-01

In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of articulated planes. We relate articulations to the relative homography between planes and show that these articulations translate into linearized equality constraints on a linear least-squares system, which can be solved efficiently using a Karush-Kuhn-Tucker system. The articulation constraints can be applied for both gradient-based and feature-based motion estimation algorithms and to illustrate this, we describe a gradient-based motion estimation algorithm for an affine camera and a feature-based motion estimation algorithm for a projective camera that explicitly enforces articulation constraints. We show that explicit application of articulation constraints leads to numerically stable estimates of motion. The simultaneous computation of motion estimates for all of the articulated planes in a scene allows us to handle scene areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the wide applicability of the algorithm in a variety of challenging real-world cases such as human body tracking, motion estimation of rigid, piecewise planar scenes, and motion estimation of triangulated meshes.

An implicit meshless scheme for the solution of transient non-linear Poisson-type equations

KAUST Repository

Bourantas, Georgios

2013-07-01

A meshfree point collocation method is used for the numerical simulation of both transient and steady state non-linear Poisson-type partial differential equations. Particular emphasis is placed on the application of the linearization method with special attention to the lagging of coefficients method and the Newton linearization method. The localized form of the Moving Least Squares (MLS) approximation is employed for the construction of the shape functions, in conjunction with the general framework of the point collocation method. Computations are performed for regular nodal distributions, stressing the positivity conditions that make the resulting system stable and convergent. The accuracy and the stability of the proposed scheme are demonstrated through representative and well-established benchmark problems. © 2013 Elsevier Ltd.

An implicit meshless scheme for the solution of transient non-linear Poisson-type equations

KAUST Repository

Bourantas, Georgios; Burganos, Vasilis N.

2013-01-01

A meshfree point collocation method is used for the numerical simulation of both transient and steady state non-linear Poisson-type partial differential equations. Particular emphasis is placed on the application of the linearization method with special attention to the lagging of coefficients method and the Newton linearization method. The localized form of the Moving Least Squares (MLS) approximation is employed for the construction of the shape functions, in conjunction with the general framework of the point collocation method. Computations are performed for regular nodal distributions, stressing the positivity conditions that make the resulting system stable and convergent. The accuracy and the stability of the proposed scheme are demonstrated through representative and well-established benchmark problems. © 2013 Elsevier Ltd.

Effective Surfactants Blend Concentration Determination for O/W Emulsion Stabilization by Two Nonionic Surfactants by Simple Linear Regression.

Science.gov (United States)

Hassan, A K

2015-01-01

In this work, O/W emulsion sets were prepared by using different concentrations of two nonionic surfactants. The two surfactants, tween 80(HLB=15.0) and span 80(HLB=4.3) were used in a fixed proportions equal to 0.55:0.45 respectively. HLB value of the surfactants blends were fixed at 10.185. The surfactants blend concentration is starting from 3% up to 19%. For each O/W emulsion set the conductivity was measured at room temperature (25±2°), 40, 50, 60, 70 and 80°. Applying the simple linear regression least squares method statistical analysis to the temperature-conductivity obtained data determines the effective surfactants blend concentration required for preparing the most stable O/W emulsion. These results were confirmed by applying the physical stability centrifugation testing and the phase inversion temperature range measurements. The results indicated that, the relation which represents the most stable O/W emulsion has the strongest direct linear relationship between temperature and conductivity. This relationship is linear up to 80°. This work proves that, the most stable O/W emulsion is determined via the determination of the maximum R² value by applying of the simple linear regression least squares method to the temperature-conductivity obtained data up to 80°, in addition to, the true maximum slope is represented by the equation which has the maximum R² value. Because the conditions would be changed in a more complex formulation, the method of the determination of the effective surfactants blend concentration was verified by applying it for more complex formulations of 2% O/W miconazole nitrate cream and the results indicate its reproducibility.

Stable Numerical Approach for Fractional Delay Differential Equations

Science.gov (United States)

Singh, Harendra; Pandey, Rajesh K.; Baleanu, D.

2017-12-01

In this paper, we present a new stable numerical approach based on the operational matrix of integration of Jacobi polynomials for solving fractional delay differential equations (FDDEs). The operational matrix approach converts the FDDE into a system of linear equations, and hence the numerical solution is obtained by solving the linear system. The error analysis of the proposed method is also established. Further, a comparative study of the approximate solutions is provided for the test examples of the FDDE by varying the values of the parameters in the Jacobi polynomials. As in special case, the Jacobi polynomials reduce to the well-known polynomials such as (1) Legendre polynomial, (2) Chebyshev polynomial of second kind, (3) Chebyshev polynomial of third and (4) Chebyshev polynomial of fourth kind respectively. Maximum absolute error and root mean square error are calculated for the illustrated examples and presented in form of tables for the comparison purpose. Numerical stability of the presented method with respect to all four kind of polynomials are discussed. Further, the obtained numerical results are compared with some known methods from the literature and it is observed that obtained results from the proposed method is better than these methods.

Reduction of Linear Programming to Linear Approximation

OpenAIRE

Vaserstein, Leonid N.

2006-01-01

It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.

Structure Learning of Linear Bayesian Networks in High-Dimensions

OpenAIRE

Aragam, Nikhyl Bryon

2015-01-01

Research into graphical models is a rapidly developing enterprise, garnering significant interest from both the statistics and machine learning communities. A parallel thread in both communities has been the study of low-dimensional structures in high-dimensional models where $p\\gg n$. Recently, there has been a surge of interest in connecting these threads in order to understand the behaviour of graphical models in high-dimensions. Due to their relative simplicity, undirected models such as ...

Stable single helical C- and I-chains inside single-walled carbon nanotubes

International Nuclear Information System (INIS)

Yao Z; Li Y; Jing X D; Meng F S; Zhao X; Li J H; Qiu Z Y; Yuan Q; Wang W X; Bi L; Liu H; Zhang Y P; Liu C J; Zheng S P; Liu B B

2016-01-01

The helicity of stable single helical carbon chains and iodine chains inside single-walled carbon nanotubes (SWCNTs) is studied by calculating the systematic van der Waals interaction energy. The results show that the optimal helical radius increases linearly with increasing tube radius, which produces a constant separation between the chain structure and the tube wall. The helical angle exhibits a ladder-like decrease with increasing tube radius, indicating that a large tube can produce a small helicity in the helical structures. (paper)

Linear accelerator radiosurgery in treatment of central neurocytomas

International Nuclear Information System (INIS)

Martin, J.M.; Katati, M.; Arjona, V.; Lopez, E.; Olivares, G.; Hernandez, V.; Bullejos, J.A.; Arregui, G.; Busquier, H.; Minguez, A.

2003-01-01

The purpose of this report was to review our experience with stereotactic radiosurgery in the management of patients with residual neurocytomas after initial surgery. Between October 1996 and December 2001, four patients with central neurocytoma were treated by surgery and subsequently underwent linear accelerator (LINAC) radiosurgery. Two of the patients were cured, one exhibited a significant reduction in tumour size and the fourth remains stable. All four patients are alive and well. In cases of small residual tumours or recurrences radio-surgery allows open surgery to be avoided and is a safe and potentially effective approach. (author)

Bifurcation from stable holes to replicating holes in vibrated dense suspensions.

Science.gov (United States)

Ebata, H; Sano, M

2013-11-01

In vertically vibrated starch suspensions, we observe bifurcations from stable holes to replicating holes. Above a certain acceleration, finite-amplitude deformations of the vibrated surface continue to grow until void penetrates fluid layers, and a hole forms. We studied experimentally and theoretically the parameter dependence of the holes and their stabilities. In suspensions of small dispersed particles, the circular shapes of the holes are stable. However, we find that larger particles or lower surface tension of water destabilize the circular shapes; this indicates the importance of capillary forces acting on the dispersed particles. Around the critical acceleration for bifurcation, holes show intermittent large deformations as a precursor to hole replication. We applied a phenomenological model for deformable domains, which is used in reaction-diffusion systems. The model can explain the basic dynamics of the holes, such as intermittent behavior, probability distribution functions of deformation, and time intervals of replication. Results from the phenomenological model match the linear growth rate below criticality that was estimated from experimental data.

MD1831: Single Bunch Instabilities with Q" and Non-Linear Corrections

CERN Document Server

Carver, Lee Robert; De Maria, Riccardo; Li, Kevin Shing Bruce; Amorim, David; Biancacci, Nicolo; Buffat, Xavier; Maclean, Ewen Hamish; Metral, Elias; Lasocha, Kacper; Lefevre, Thibaut; Levens, Tom; Salvant, Benoit; CERN. Geneva. ATS Department

2017-01-01

During MD1751, it was observed that both a full single beam and 964 non-colliding bunches in Beam 1 (B1) and Beam 2 (B2) were both stable at the End of Squeeze (EOS) for 0A in the Landau Octupoles. At ß* = 40cm there is also a significant Q" arising from the lattice, as well as uncorrected non-linearities in the Insertion Regions (IRs). Each of these effects could be capable of fully stabilising the beam. This MD made first use of a Q" knob through variation of the Main Sextupoles (MS) by stabilising a single bunch at Flat Top, before showing at EOS that the non-linearities were the main contributors to the beam stability.

Electromagnetic linear machines with dual Halbach array design and analysis

CERN Document Server

Yan, Liang; Peng, Juanjuan; Zhang, Lei; Jiao, Zongxia

2017-01-01

This book extends the conventional two-dimensional (2D) magnet arrangement into 3D pattern for permanent magnet linear machines for the first time, and proposes a novel dual Halbach array. It can not only effectively increase the radial component of magnetic flux density and output force of tubular linear machines, but also significantly reduce the axial flux density, radial force and thus system vibrations and noises. The book is also the first to address the fundamentals and provide a summary of conventional arrays, as well as novel concepts for PM pole design in electric linear machines. It covers theoretical study, numerical simulation, design optimization and experimental works systematically. The design concept and analytical approaches can be implemented to other linear and rotary machines with similar structures. The book will be of interest to academics, researchers, R&D engineers and graduate students in electronic engineering and mechanical engineering who wish to learn the core principles, met...

Application of alternating decision trees in selecting sparse linear solvers

KAUST Repository

Bhowmick, Sanjukta; Eijkhout, Victor; Freund, Yoav; Fuentes, Erika; Keyes, David E.

2010-01-01

The solution of sparse linear systems, a fundamental and resource-intensive task in scientific computing, can be approached through multiple algorithms. Using an algorithm well adapted to characteristics of the task can significantly enhance the performance, such as reducing the time required for the operation, without compromising the quality of the result. However, the best solution method can vary even across linear systems generated in course of the same PDE-based simulation, thereby making solver selection a very challenging problem. In this paper, we use a machine learning technique, Alternating Decision Trees (ADT), to select efficient solvers based on the properties of sparse linear systems and runtime-dependent features, such as the stages of simulation. We demonstrate the effectiveness of this method through empirical results over linear systems drawn from computational fluid dynamics and magnetohydrodynamics applications. The results also demonstrate that using ADT can resolve the problem of over-fitting, which occurs when limited amount of data is available. © 2010 Springer Science+Business Media LLC.

Transport properties of a piecewise linear transformation and deterministic Levy flights

International Nuclear Information System (INIS)

Miyaguchi, Tomoshige

2006-01-01

The transport properties of a 1-dimensional piecewise linear dynamical system are investigated through the spectrum of its Frobenius-Perron operator. For a class of initial densities, eigenvalues and eigenfunctions of the Frobenius-Perron operator are obtained explicitly. It is also found that in the long length wave limit, this system exhibits normal diffusion and super diffusion called Levy flight. The diffusion constant and stable index are derived from the eigenvalues. (author)

One-dimensional stable distributions

CERN Document Server

Zolotarev, V M

1986-01-01

This is the first book specifically devoted to a systematic exposition of the essential facts known about the properties of stable distributions. In addition to its main focus on the analytic properties of stable laws, the book also includes examples of the occurrence of stable distributions in applied problems and a chapter on the problem of statistical estimation of the parameters determining stable laws. A valuable feature of the book is the author's use of several formally different ways of expressing characteristic functions corresponding to these laws.

A theorem for non-linear stability to tearing modes

International Nuclear Information System (INIS)

Avinash, K.

1992-12-01

Within the reduced MHD approximation it is shown that dJ z /dΨ≤0 [J z is z component of the current density and Ψ is the helical flux] is a sufficient condition for the equilibrium to be non-linearly stable to tearing mode. It is further shown that this is also a sufficient condition for an equilibrium to be axisymmetric, hence helical equilibrium consistent with this condition cannot be constructed. However a class of axisymmetric equilibrium with hollow current profile is shown to satisfy the stability criterion. (author). 16 refs, 2 figs

Mathematical Modelling in Engineering: An Alternative Way to Teach Linear Algebra

Science.gov (United States)

Domínguez-García, S.; García-Planas, M. I.; Taberna, J.

2016-01-01

Technological advances require that basic science courses for engineering, including Linear Algebra, emphasize the development of mathematical strengths associated with modelling and interpretation of results, which are not limited only to calculus abilities. Based on this consideration, we have proposed a project-based learning, giving a dynamic…

Updating QR factorization procedure for solution of linear least squares problem with equality constraints.

Science.gov (United States)

Zeb, Salman; Yousaf, Muhammad

2017-01-01

In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.

Metric Learning for Hyperspectral Image Segmentation

Science.gov (United States)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Stabilisation and precision pointing quadrupole magnets in the Compact Linear Collider (CLIC)

CERN Document Server

Janssens, Stef; Linde, Frank; van den Brand, Jo; Bertolini, Alessandro; Artoos, Kurt

This thesis describes the research done to provide stabilisation and precision positioning for the main beam quadrupole magnets of the Compact Linear Collider CLIC. The introduction describes why new particle accelerators are needed to further the knowledge of our universe and why they are linear. A proposed future accelerator is the Compact Linear Collider (CLIC) which consists of a novel two beam accelerator concept. Due to its linearity and subsequent single pass at the interaction point, this new accelerator requires a very small beam size at the interaction point, in order to increase collision effectiveness. One of the technological challenges, to obtain these small beam sizes at the interaction point, is to keep the quadrupole magnets aligned and stable to 1.5 nm integrated r.m.s. in vertical and 5 nm integrated root mean square (r.m.s.) in lateral direction. Additionally there is a proposal to create an intentional offset (max. 50 nm every 20 ms with a precision of +/- 1 nm), for several quadrupole ma...

Bi-stable optical actuator

Science.gov (United States)

Holdener, Fred R.; Boyd, Robert D.

2000-01-01

The present invention is a bi-stable optical actuator device that is depowered in both stable positions. A bearing is used to transfer motion and smoothly transition from one state to another. The optical actuator device may be maintained in a stable position either by gravity or a restraining device.

Applying machine learning techniques for forecasting flexibility of virtual power plants

DEFF Research Database (Denmark)

MacDougall, Pamela; Kosek, Anna Magdalena; Bindner, Henrik W.

2016-01-01

network as well as the multi-variant linear regression. It is found that it is possible to estimate the longevity of flexibility with machine learning. The linear regression algorithm is, on average, able to estimate the longevity with a 15% error. However, there was a significant improvement with the ANN...... approach to investigating the longevity of aggregated response of a virtual power plant using historic bidding and aggregated behaviour with machine learning techniques. The two supervised machine learning techniques investigated and compared in this paper are, multivariate linear regression and single...... algorithm achieving, on average, a 5.3% error. This is lowered 2.4% when learning for the same virtual power plant. With this information it would be possible to accurately offer residential VPP flexibility for market operations to safely avoid causing further imbalances and financial penalties....

Fuzzy linear programming based optimal fuel scheduling incorporating blending/transloading facilities

Energy Technology Data Exchange (ETDEWEB)

Djukanovic, M.; Babic, B.; Milosevic, B. [Electrical Engineering Inst. Nikola Tesla, Belgrade (Yugoslavia); Sobajic, D.J. [EPRI, Palo Alto, CA (United States). Power System Control; Pao, Y.H. [Case Western Reserve Univ., Cleveland, OH (United States)]|[AI WARE, Inc., Cleveland, OH (United States)

1996-05-01

In this paper the blending/transloading facilities are modeled using an interactive fuzzy linear programming (FLP), in order to allow the decision-maker to solve the problem of uncertainty of input information within the fuel scheduling optimization. An interactive decision-making process is formulated in which decision-maker can learn to recognize good solutions by considering all possibilities of fuzziness. The application of the fuzzy formulation is accompanied by a careful examination of the definition of fuzziness, appropriateness of the membership function and interpretation of results. The proposed concept provides a decision support system with integration-oriented features, whereby the decision-maker can learn to recognize the relative importance of factors in the specific domain of optimal fuel scheduling (OFS) problem. The formulation of a fuzzy linear programming problem to obtain a reasonable nonfuzzy solution under consideration of the ambiguity of parameters, represented by fuzzy numbers, is introduced. An additional advantage of the FLP formulation is its ability to deal with multi-objective problems.

Berkeley Proton Linear Accelerator

Science.gov (United States)

Alvarez, L. W.; Bradner, H.; Franck, J.; Gordon, H.; Gow, J. D.; Marshall, L. C.; Oppenheimer, F. F.; Panofsky, W. K. H.; Richman, C.; Woodyard, J. R.

1953-10-13

A linear accelerator, which increases the energy of protons from a 4 Mev Van de Graaff injector, to a final energy of 31.5 Mev, has been constructed. The accelerator consists of a cavity 40 feet long and 39 inches in diameter, excited at resonance in a longitudinal electric mode with a radio-frequency power of about 2.2 x 10{sup 6} watts peak at 202.5 mc. Acceleration is made possible by the introduction of 46 axial "drift tubes" into the cavity, which is designed such that the particles traverse the distance between the centers of successive tubes in one cycle of the r.f. power. The protons are longitudinally stable as in the synchrotron, and are stabilized transversely by the action of converging fields produced by focusing grids. The electrical cavity is constructed like an inverted airplane fuselage and is supported in a vacuum tank. Power is supplied by 9 high powered oscillators fed from a pulse generator of the artificial transmission line type.

MATH INSTRUCTIONAL MEDIA DESIGN USING COMPUTER FOR COMPLETION OF TWO-VARIABLES LINEAR EQUATION SYSTEM BY ELIMINATION METHOD

Directory of Open Access Journals (Sweden)

Nurbaiti

2017-03-01

Full Text Available Science and technology have been rapidly evolved in some fields of knowledge, including mathematics. Such development can contribute to improvements on the learning process that encourage students and teachers to enhance their abilities and performances. In delivering the material on the linear equation system with two variables (SPLDV, the conventional teaching method where teachers become the center of the learning process is still well-practiced. This method would cause the students get bored and have difficulties to understand the concepts they are learning. Therefore, in order to the learning of SPLDV easy, an interesting, interactive media that the students and teachers can apply is necessary. This media is designed using GUI MATLAB and named as students’ electronic worksheets (e-LKS. This program is intended to help students in finding and understanding the SPLDV concepts more easily. This program is also expected to improve students’ motivation and creativity in learning the material. Based on the test using the System Usability Scale (SUS, the design of interactive mathematics learning media of the linear equation system with Two Variables (SPLDV gets grade B (excellent, meaning that this learning media is proper to be used for Junior High School students of grade VIII.

Remarks on stable and quasi-stable k-strings at large N

International Nuclear Information System (INIS)

Armoni, A.; Shifman, M.

2003-01-01

We discuss k-strings in the large-N Yang-Mills theory and its supersymmetric extension. Whereas the tension of the bona fide (stable) QCD string is expected to depend only on the N-ality of the representation, tensions that depend on specific representation R are often reported in the lattice literature. In particular, adjoint strings are discussed and found in certain simulations. We clarify this issue by systematically exploiting the notion of the quasi-stable strings which becomes well-defined at large N. The quasi-stable strings with representation-dependent tensions decay, but the decay rate (per unit length per unit time) is suppressed as Λ 2 F(N) where F(N) falls off as a function of N. It can be determined on the case-by-case basis. The quasi-stable strings eventually decay into stable strings whose tension indeed depends only on the N-ality. We also briefly review large-N arguments showing why the Casimir formula for the string tension cannot be correct, and present additional arguments in favor of the sine formula. Finally, we comment on the relevance of our estimates to Euclidean lattice measurements

Resettable binary latch mechanism for use with paraffin linear motors

Science.gov (United States)

Maus, Daryl; Tibbitts, Scott

1991-01-01

A new resettable Binary Latch Mechanism was developed utilizing a paraffin actuator as the motor. This linear actuator alternately latches between extended and retracted positions, maintaining either position with zero power consumption. The design evolution and kinematics of the latch mechanism are presented, as well as the development problems and lessons that were learned.

Evolutionary Stable Strategy

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 21; Issue 9. Evolutionary Stable Strategy: Application of Nash Equilibrium in Biology. General Article Volume 21 Issue 9 September 2016 pp 803- ... Keywords. Evolutionary game theory, evolutionary stable state, conflict, cooperation, biological games.

A linear multiple balance method for discrete ordinates neutron transport equations

International Nuclear Information System (INIS)

Park, Chang Je; Cho, Nam Zin

2000-01-01

A linear multiple balance method (LMB) is developed to provide more accurate and positive solutions for the discrete ordinates neutron transport equations. In this multiple balance approach, one mesh cell is divided into two subcells with quadratic approximation of angular flux distribution. Four multiple balance equations are used to relate center angular flux with average angular flux by Simpson's rule. From the analysis of spatial truncation error, the accuracy of the linear multiple balance scheme is ο(Δ 4 ) whereas that of diamond differencing is ο(Δ 2 ). To accelerate the linear multiple balance method, we also describe a simplified additive angular dependent rebalance factor scheme which combines a modified boundary projection acceleration scheme and the angular dependent rebalance factor acceleration schme. It is demonstrated, via fourier analysis of a simple model problem as well as numerical calculations, that the additive angular dependent rebalance factor acceleration scheme is unconditionally stable with spectral radius < 0.2069c (c being the scattering ration). The numerical results tested so far on slab-geometry discrete ordinates transport problems show that the solution method of linear multiple balance is effective and sufficiently efficient

Overcoming Learning Barriers through Knowledge Management

Science.gov (United States)

Dror, Itiel E.; Makany, Tamas; Kemp, Jonathan

2011-01-01

The ability to learn highly depends on how knowledge is managed. Specifically, different techniques for note-taking utilize different cognitive processes and strategies. In this paper, we compared dyslexic and control participants when using linear and non-linear note-taking. All our participants were professionals working in the banking and…

Stable Structures for Distributed Applications

Directory of Open Access Journals (Sweden)

Eugen DUMITRASCU

2008-01-01

Full Text Available For distributed applications, we define the linear, tree and graph structure types with different variants and modalities to aggregate them. The distributed applications have assigned structures that through their characteristics influence the costs of stages for developing cycle and the costs for exploitation, transferred to each user. We also present the quality characteristics of a structure for a stable application, which is focused on stability characteristic. For that characteristic we define the estimated measure indicators for a level. The influence of the factors of stability and the ways for increasing it are thus identified, and at the same time the costs of development stages, the costs of usage and the costs of maintenance to be keep on between limits that assure the global efficiency of application. It is presented the base aspects for distributed applications: definition, peculiarities and importance. The aspects for the development cycle of distributed application are detailed. In this article, we alongside give the mechanisms for building the defined structures and analyze the complexity of the defined structures for a distributed application of a virtual store.

Stable Operation and Electricity Generating Characteristics of a Single-Cylinder Free Piston Engine Linear Generator: Simulation and Experiments

Directory of Open Access Journals (Sweden)

Huihua Feng

2015-01-01

Full Text Available We present a novel design of a single-cylinder free piston engine linear generator (FPELG incorporating a linear motor as a rebound device. A systematic simulation model of this FPELG system was built containing a kinematic and dynamic model of the piston and mover, a magneto-electric model of the linear generator, a thermodynamic model of the single-cylinder engine, and a friction model between the piston ring and cylinder liner. Simulations were performed to understand the relationships between pre-set motor parameters and the running performance of the FPELG. From the simulation results, it was found that a motor rebound force with a parabolic profile had clear advantages over a force with a triangular profile, such as a higher running frequency and peak cylinder pressure, faster piston motion, etc. The rebound position and the amplitude of rebound force were also determined by simulations. The energy conversion characteristics of the generator were obtained from our FPELG test rig. The parameters of intake pressure, motor frequency, and load resistance were varied over certain ranges, and relationships among these three parameters were obtained. The electricity-generating characteristic parameters include output power and system efficiency, which can measure the quality of matching the controllable parameters. The output power can reach 25.9 W and the system efficiency can reach 13.7%. The results in terms of matching parameters and electricity-generating characteristics should be useful to future research in adapting these engines to various operating modes.

Evidence for Stable v = 0, j = 1 → 0 SiO Maser Emission from VY Canis Majoris

Science.gov (United States)

McIntosh, G. C.; Rislow, B.

2009-02-01

Observations of the SiO v = 0, J = 1 → 0 spectra from VY CMa from 2003 through 2006 indicate an unusually long-lived, highly linearly polarized maser emission at a V lsr of approximately 18.5 km s-1. A time series cross-correlation analysis has been developed for calculating the characteristic lifetime of linearly polarized spectra. Applying the cross-correlation to these spectra indicates a characteristic lifetime of 5600 ± 400 days. These emission characteristics may be generated in a region of relatively stable outflow geometry and magnetic field rather than in the more ephemeral circumstellar environment.

EVIDENCE FOR STABLE v = 0, J = 1 → 0 SiO MASER EMISSION FROM VY CANIS MAJORIS

International Nuclear Information System (INIS)

McIntosh, G. C.; Rislow, B.

2009-01-01

Observations of the SiO v = 0, J = 1 → 0 spectra from VY CMa from 2003 through 2006 indicate an unusually long-lived, highly linearly polarized maser emission at a V lsr of approximately 18.5 km s -1 . A time series cross-correlation analysis has been developed for calculating the characteristic lifetime of linearly polarized spectra. Applying the cross-correlation to these spectra indicates a characteristic lifetime of 5600 ± 400 days. These emission characteristics may be generated in a region of relatively stable outflow geometry and magnetic field rather than in the more ephemeral circumstellar environment.

A study on stable levitation of permanent magnet transportation system with coreless linear synchronous motor

Energy Technology Data Exchange (ETDEWEB)

Hiwaki, H [Dept. of Electrical and Electronic Engineering, Musashi Inst. of Technology, Tokyo (Japan); Watada, M [Dept. of Electrical and Electronic Engineering, Musashi Inst. of Technology, Tokyo (Japan); Torii, S [Dept. of Electrical and Electronic Engineering, Musashi Inst. of Technology, Tokyo (Japan); Ebihara, D [Dept. of Electrical and Electronic Engineering, Musashi Inst. of Technology, Tokyo (Japan)

1996-12-31

In the permanent magnet levitation system, it is impossible to stabilize the motion of the vehicle in both levitation and guidance directions only by permanent magnet. Therefore, the authors proposed the combined system of permanent magnet for levitation and coreless linear synchronous motor (coreless LSM). To design the coreless coils for LSM, the method to calculate the spring coefficient between coreless coil and permanent magnet for LSM is shown. By using this method, the spring coefficients of the three coil arrangements are compared and coreless coil is designed. Furthermore, the authors showed the possibility of stabilizing the motion of the levitation system with coreless LSM. (orig.)

Catalytic mechanism of phenylacetone monooxygenases for non-native linear substrates.

Science.gov (United States)

Carvalho, Alexandra T P; Dourado, Daniel F A R; Skvortsov, Timofey; de Abreu, Miguel; Ferguson, Lyndsey J; Quinn, Derek J; Moody, Thomas S; Huang, Meilan

2017-10-11

Phenylacetone monooxygenase (PAMO) is the most stable and thermo-tolerant member of the Baeyer-Villiger monooxygenase family, and therefore it is an ideal candidate for the synthesis of industrially relevant compounds. However, its limited substrate scope has largely limited its industrial applications. In the present work, we provide, for the first time, the catalytic mechanism of PAMO for the native substrate phenylacetone as well as for a linear non-native substrate 2-octanone, using molecular dynamics simulations, quantum mechanics and quantum mechanics/molecular mechanics calculations. We provide a theoretical basis for the preference of the enzyme for the native aromatic substrate over non-native linear substrates. Our study provides fundamental atomic-level insights that can be employed in the rational engineering of PAMO for wide applications in industrial biocatalysis, in particular, in the biotransformation of long-chain aliphatic oils into potential biodiesels.

Feedback Linearized Aircraft Control Using Dynamic Cell Structure

Science.gov (United States)

Jorgensen, C. C.

1998-01-01

A Dynamic Cell Structure (DCS ) Neural Network was developed which learns a topology representing network (TRN) of F-15 aircraft aerodynamic stability and control derivatives. The network is combined with a feedback linearized tracking controller to produce a robust control architecture capable of handling multiple accident and off-nominal flight scenarios. This paper describes network and its performance for accident scenarios including differential stabilator lock, soft sensor failure, control, stability derivative variation, and turbulence.

Investigating Years 7 to 12 students' knowledge of linear relationships through different contexts and representations

Science.gov (United States)

Wilkie, Karina J.; Ayalon, Michal

2018-02-01

A foundational component of developing algebraic thinking for meaningful calculus learning is the idea of "function" that focuses on the relationship between varying quantities. Students have demonstrated widespread difficulties in learning calculus, particularly interpreting and modeling dynamic events, when they have a poor understanding of relationships between variables. Yet, there are differing views on how to develop students' functional thinking over time. In the Australian curriculum context, linear relationships are introduced to lower secondary students with content that reflects a hybrid of traditional and reform algebra pedagogy. This article discusses an investigation into Australian secondary students' understanding of linear functional relationships from Years 7 to 12 (approximately 12 to 18 years old; n = 215) in their approaches to three tasks (finding rate of change, pattern generalisation and interpretation of gradient) involving four different representations (table, geometric growing pattern, equation and graph). From the findings, it appears that these students' knowledge of linear functions remains context-specific rather than becoming connected over time.

Bistable energy harvesting enhancement with an auxiliary linear oscillator

Science.gov (United States)

Harne, R. L.; Thota, M.; Wang, K. W.

2013-12-01

Recent work has indicated that linear vibrational energy harvesters with an appended degree-of-freedom (DOF) may be advantageous for introducing new dynamic forms to extend the operational bandwidth. Given the additional interest in bistable harvester designs, which exhibit a propitious snap through effect from one stable state to the other, it is a logical extension to explore the influence of an added DOF to a bistable system. However, bistable snap through is not a resonant phenomenon, which tempers the presumption that the dynamics induced by an additional DOF on bistable designs would inherently be beneficial as for linear systems. This paper presents two analytical formulations to assess the fundamental and superharmonic steady-state dynamics of an excited bistable energy harvester to which is attached an auxiliary linear oscillator. From an energy harvesting perspective, the model predicts that the additional linear DOF uniformly amplifies the bistable harvester response magnitude and generated power for excitation frequencies less than the attachment’s resonance while improved power density spans a bandwidth below this frequency. Analyses predict bandwidths having co-existent responses composed of a unique proportion of fundamental and superharmonic dynamics. Experiments validate key analytical predictions and observe the ability for the coupled system to develop an advantageous multi-harmonic interwell response when the initial conditions are insufficient for continuous high-energy orbit at the excitation frequency. Overall, the addition of an auxiliary linear oscillator to a bistable harvester is found to be an effective means of enhancing the energy harvesting performance and robustness.

Coupled dimensionality reduction and classification for supervised and semi-supervised multilabel learning.

Science.gov (United States)

Gönen, Mehmet

2014-03-01

Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F 1 , and micro F 1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks.

Of Linear Colliders, the GDE Workshop at Bangalore, Mughals, Camels, Elephants and Sundials

International Nuclear Information System (INIS)

Loew, Greg

2006-01-01

In this colloquium, the speaker will give a summary of the recent International Linear Collider (ILC) Global Design Effort (GDE) Workshop at Bangalore and how the High Energy Physics community converged to this meeting after many years of electron-positron linear collider design and experimental work. Given that this workshop for the first time took place in India, the speaker will also show a few pictures and talk briefly about what he learned in that fascinating country.

Linear time delay methods and stability analyses of the human spine. Effects of neuromuscular reflex response.

Science.gov (United States)

Franklin, Timothy C; Granata, Kevin P; Madigan, Michael L; Hendricks, Scott L

2008-08-01

Linear stability methods were applied to a biomechanical model of the human musculoskeletal spine to investigate effects of reflex gain and reflex delay on stability. Equations of motion represented a dynamic 18 degrees-of-freedom rigid-body model with time-delayed reflexes. Optimal muscle activation levels were identified by minimizing metabolic power with the constraints of equilibrium and stability with zero reflex time delay. Muscle activation levels and associated muscle forces were used to find the delay margin, i.e., the maximum reflex delay for which the system was stable. Results demonstrated that stiffness due to antagonistic co-contraction necessary for stability declined with increased proportional reflex gain. Reflex delay limited the maximum acceptable proportional reflex gain, i.e., long reflex delay required smaller maximum reflex gain to avoid instability. As differential reflex gain increased, there was a small increase in acceptable reflex delay. However, differential reflex gain with values near intrinsic damping caused the delay margin to approach zero. Forward-dynamic simulations of the fully nonlinear time-delayed system verified the linear results. The linear methods accurately found the delay margin below which the nonlinear system was asymptotically stable. These methods may aid future investigations in the role of reflexes in musculoskeletal stability.

On the Use of Linearized Euler Equations in the Prediction of Jet Noise

Science.gov (United States)

Mankbadi, Reda R.; Hixon, R.; Shih, S.-H.; Povinelli, L. A.

1995-01-01

Linearized Euler equations are used to simulate supersonic jet noise generation and propagation. Special attention is given to boundary treatment. The resulting solution is stable and nearly free from boundary reflections without the need for artificial dissipation, filtering, or a sponge layer. The computed solution is in good agreement with theory and observation and is much less CPU-intensive as compared to large-eddy simulations.

Farmers’ perception of stable schools as a tool to improve management for the benefit of mink welfare

DEFF Research Database (Denmark)

Henriksen, Britt I. F.; Anneberg, Inger; Sørensen, Jan Tind

2015-01-01

The aim of the study was to explore farmers' perception of stable schools as a tool to improve management for the benefit of mink welfare. Stable schools are knowledge exchange between farmers working towards a common goal, being able to give practical advice to each other. The concept is based......, and that motivation for working towards a common goal is very important for the process of common learning among the farmers. The uniform production system at mink farms gives special challenges in how to work with the different subjects to ensure farmer ownership of the process. The farmers did not see the seasonal...

Off-line learning from clustered input examples

NARCIS (Netherlands)

Marangi, Carmela; Solla, Sara A.; Biehl, Michael; Riegler, Peter; Marinaro, Maria; Tagliaferri, Roberto

1996-01-01

We analyze the generalization ability of a simple perceptron acting on a structured input distribution for the simple case of two clusters of input data and a linearly separable rule. The generalization ability computed for three learning scenarios: maximal stability, Gibbs, and optimal learning, is

Psychotic Experiences and Overhasty Inferences Are Related to Maladaptive Learning.

Directory of Open Access Journals (Sweden)

Heiner Stuke

2017-01-01

Full Text Available Theoretical accounts suggest that an alteration in the brain's learning mechanisms might lead to overhasty inferences, resulting in psychotic symptoms. Here, we sought to elucidate the suggested link between maladaptive learning and psychosis. Ninety-eight healthy individuals with varying degrees of delusional ideation and hallucinatory experiences performed a probabilistic reasoning task that allowed us to quantify overhasty inferences. Replicating previous results, we found a relationship between psychotic experiences and overhasty inferences during probabilistic reasoning. Computational modelling revealed that the behavioral data was best explained by a novel computational learning model that formalizes the adaptiveness of learning by a non-linear distortion of prediction error processing, where an increased non-linearity implies a growing resilience against learning from surprising and thus unreliable information (large prediction errors. Most importantly, a decreased adaptiveness of learning predicted delusional ideation and hallucinatory experiences. Our current findings provide a formal description of the computational mechanisms underlying overhasty inferences, thereby empirically substantiating theories that link psychosis to maladaptive learning.

Visualizing the Inner Product Space R[superscript m x n] in a MATLAB-Assisted Linear Algebra Classroom

Science.gov (United States)

Caglayan, Günhan

2018-01-01

This linear algebra note offers teaching and learning ideas in the treatment of the inner product space R[superscript m x n] in a technology-supported learning environment. Classroom activities proposed in this note demonstrate creative ways of integrating MATLAB technology into various properties of Frobenius inner product as visualization tools…

Skeletal muscle mass and exercise performance in stable ambulatory patients with heart failure.

Science.gov (United States)

Lang, C C; Chomsky, D B; Rayos, G; Yeoh, T K; Wilson, J R

1997-01-01

The purpose of this study was to determine whether skeletal muscle atrophy limits the maximal exercise capacity of stable ambulatory patients with heart failure. Body composition and maximal exercise capacity were measured in 100 stable ambulatory patients with heart failure. Body composition was assessed by using dual-energy X-ray absorption. Peak exercise oxygen consumption (VO2peak) and the anaerobic threshold were measured by using a Naughton treadmill protocol and a Medical Graphics CardioO2 System. VO2peak averaged 13.4 +/- 3.3 ml.min-1.kg-1 or 43 +/- 12% of normal. Lean body mass averaged 52.9 +/- 10.5 kg and leg lean mass 16.5 +/- 3.6 kg. Leg lean mass correlated linearly with VO2peak (r = 0.68, P < 0.01), suggesting that exercise performance is influences by skeletal muscle mass. However, lean body mass was comparable to levels noted in 1,584 normal control subjects, suggesting no decrease in muscle mass. Leg muscle mass was comparable to levels noted in 34 normal control subjects, further supporting this conclusion. These findings suggest that exercise intolerance in stable ambulatory patients with heart failure is not due to skeletal muscle atrophy.

Learning from input and memory evolution: points of vulnerability on a pathway to mastery in word learning.

Science.gov (United States)

Storkel, Holly L

2015-02-01

Word learning consists of at least two neurocognitive processes: learning from input during training and memory evolution during gaps between training sessions. Fine-grained analysis of word learning by normal adults provides evidence that learning from input is swift and stable, whereas memory evolution is a point of potential vulnerability on the pathway to mastery. Moreover, success during learning from input is linked to positive outcomes from memory evolution. These two neurocognitive processes can be overlaid on to components of clinical treatment with within-session variables (i.e. dose form and dose) potentially linked to learning from input and between-session variables (i.e. dose frequency) linked to memory evolution. Collecting data at the beginning and end of a treatment session can be used to identify the point of vulnerability in word learning for a given client and the appropriate treatment component can then be adjusted to improve the client's word learning. Two clinical cases are provided to illustrate this approach.

Sufficient condition for the linearization stability of N = 1 supergravity: A preliminary report

International Nuclear Information System (INIS)

Bao, D.

1984-01-01

This paper outlines how the methods developed by Fischer, Marsden, and Moncrief (A. Fischer and J. Marsden, ''Isolated Gravitating Systems in General Relativity,'' (J. Ehlers, Ed.), Proceedings of the International School of Physics Enrico Fermi Course XVII, North-Holland, Amsterdam, 1979; A. Fischer, J. Marsden, and V. Moncrief, Ann. Inst. Henri Poincare 33 (1980), 147-194) for general relativity are being used to show that classical N = 1 supergravity, as a non-linear system of partial differential equtions, is linearization stable at any solution which lacks Killing symmetry. It is assumed (for convenience) throughout that the underlying spacetime is topologically Σ 0 x R, where Σ 0 is a compact, spacelike, and boundaryless 3-dimensional hypersurface

Understanding Linear Function: A Comparison of Selected Textbooks from England and Shanghai

Science.gov (United States)

Wang, Yuqian; Barmby, Patrick; Bolden, David

2017-01-01

This study describes a comparison of how worked examples in selected textbooks from England and Shanghai presented possible learning trajectories towards understanding linear function. Six selected English textbooks and one Shanghai compulsory textbook were analysed with regards to the understanding required for pure mathematics knowledge in…

Applied Research of Enterprise Cost Control Based on Linear Programming

Directory of Open Access Journals (Sweden)

Yu Shuo

2015-01-01

This paper researches the enterprise cost control through the linear programming model, and analyzes the restriction factors of the labor of enterprise production, raw materials, processing equipment, sales price, and other factors affecting the enterprise income, so as to obtain an enterprise cost control model based on the linear programming. This model can calculate rational production mode in the case of limited resources, and acquire optimal enterprise income. The production guiding program and scheduling arrangement of the enterprise can be obtained through calculation results, so as to provide scientific and effective guidance for the enterprise production. This paper adds the sensitivity analysis in the linear programming model, so as to learn about the stability of the enterprise cost control model based on linear programming through the sensitivity analysis, and verify the rationality of the model, and indicate the direction for the enterprise cost control. The calculation results of the model can provide a certain reference for the enterprise planning in the market economy environment, which have strong reference and practical significance in terms of the enterprise cost control.

Linear versus non-linear supersymmetry, in general

Energy Technology Data Exchange (ETDEWEB)

Ferrara, Sergio [Theoretical Physics Department, CERN,CH-1211 Geneva 23 (Switzerland); INFN - Laboratori Nazionali di Frascati,Via Enrico Fermi 40, I-00044 Frascati (Italy); Department of Physics and Astronomy, UniversityC.L.A.,Los Angeles, CA 90095-1547 (United States); Kallosh, Renata [SITP and Department of Physics, Stanford University,Stanford, California 94305 (United States); Proeyen, Antoine Van [Institute for Theoretical Physics, Katholieke Universiteit Leuven,Celestijnenlaan 200D, B-3001 Leuven (Belgium); Wrase, Timm [Institute for Theoretical Physics, Technische Universität Wien,Wiedner Hauptstr. 8-10, A-1040 Vienna (Austria)

2016-04-12

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Linear versus non-linear supersymmetry, in general

International Nuclear Information System (INIS)

Ferrara, Sergio; Kallosh, Renata; Proeyen, Antoine Van; Wrase, Timm

2016-01-01

We study superconformal and supergravity models with constrained superfields. The underlying version of such models with all unconstrained superfields and linearly realized supersymmetry is presented here, in addition to the physical multiplets there are Lagrange multiplier (LM) superfields. Once the equations of motion for the LM superfields are solved, some of the physical superfields become constrained. The linear supersymmetry of the original models becomes non-linearly realized, its exact form can be deduced from the original linear supersymmetry. Known examples of constrained superfields are shown to require the following LM’s: chiral superfields, linear superfields, general complex superfields, some of them are multiplets with a spin.

Self-similar decay to the marginally stable ground state in a model for film flow over inclined wavy bottoms

Directory of Open Access Journals (Sweden)

Tobias Hacker

2012-04-01

Full Text Available The integral boundary layer system (IBL with spatially periodic coefficients arises as a long wave approximation for the flow of a viscous incompressible fluid down a wavy inclined plane. The Nusselt-like stationary solution of the IBL is linearly at best marginally stable; i.e., it has essential spectrum at least up to the imaginary axis. Nevertheless, in this stable case we show that localized perturbations of the ground state decay in a self-similar way. The proof uses the renormalization group method in Bloch variables and the fact that in the stable case the Burgers equation is the amplitude equation for long waves of small amplitude in the IBL. It is the first time that such a proof is given for a quasilinear PDE with spatially periodic coefficients.

Stable Boundary Layer Issues

OpenAIRE

Steeneveld, G.J.

2012-01-01

Understanding and prediction of the stable atmospheric boundary layer is a challenging task. Many physical processes are relevant in the stable boundary layer, i.e. turbulence, radiation, land surface coupling, orographic turbulent and gravity wave drag, and land surface heterogeneity. The development of robust stable boundary layer parameterizations for use in NWP and climate models is hampered by the multiplicity of processes and their unknown interactions. As a result, these models suffer ...

A non-linear manifold alignment approach to robot learning from demonstrations

CSIR Research Space (South Africa)

Makondo, Ndivhuwo

2018-04-01

Full Text Available with potentially different, but unknown, kinematics from humans. This paper proposes a method that enables robots with unknown kinematics to learn skills from demonstrations. Our proposed method requires a motion trajectory obtained from human demonstrations via a...

Explanation-based learning in infancy.

Science.gov (United States)

Baillargeon, Renée; DeJong, Gerald F

2017-10-01

In explanation-based learning (EBL), domain knowledge is leveraged in order to learn general rules from few examples. An explanation is constructed for initial exemplars and is then generalized into a candidate rule that uses only the relevant features specified in the explanation; if the rule proves accurate for a few additional exemplars, it is adopted. EBL is thus highly efficient because it combines both analytic and empirical evidence. EBL has been proposed as one of the mechanisms that help infants acquire and revise their physical rules. To evaluate this proposal, 11- and 12-month-olds (n = 260) were taught to replace their current support rule (that an object is stable when half or more of its bottom surface is supported) with a more sophisticated rule (that an object is stable when half or more of the entire object is supported). Infants saw teaching events in which asymmetrical objects were placed on a base, followed by static test displays involving a novel asymmetrical object and a novel base. When the teaching events were designed to facilitate EBL, infants learned the new rule with as few as two (12-month-olds) or three (11-month-olds) exemplars. When the teaching events were designed to impede EBL, however, infants failed to learn the rule. Together, these results demonstrate that even infants, with their limited knowledge about the world, benefit from the knowledge-based approach of EBL.

Designing a Responsive E-Learning Infrastructure: Systemic Change in Higher Education

Science.gov (United States)

Chow, Anthony S.; Croxton, Rebecca A.

2017-01-01

As university administrators respond to increasing demands of the educational market to offer greater opportunities for online learning, their capacity to create an economically stable, sustainable, yet rich teaching and learning environment deserves immediate and continued attention. A university-wide study involving 130 participants examined the…

Linear Stability of Binary Alloy Solidification for Unsteady Growth Rates

Science.gov (United States)

Mazuruk, K.; Volz, M. P.

2010-01-01

An extension of the Mullins and Sekerka (MS) linear stability analysis to the unsteady growth rate case is considered for dilute binary alloys. In particular, the stability of the planar interface during the initial solidification transient is studied in detail numerically. The rapid solidification case, when the system is traversing through the unstable region defined by the MS criterion, has also been treated. It has been observed that the onset of instability is quite accurately defined by the "quasi-stationary MS criterion", when the growth rate and other process parameters are taken as constants at a particular time of the growth process. A singular behavior of the governing equations for the perturbed quantities at the constitutional supercooling demarcation line has been observed. However, when the solidification process, during its transient, crosses this demarcation line, a planar interface is stable according to the linear analysis performed.

Decoupling Design and Verification of a Free-Piston Linear Generator

Directory of Open Access Journals (Sweden)

Peng Sun

2016-12-01

Full Text Available This paper proposes a decoupling design approach for a free-piston linear generator (FPLG constituted of three key components, including a combustion chamber, a linear generator and a gas spring serving as rebounding device. The approach is based on the distribution of the system power and efficiency, which provides a theoretical design method from the viewpoint of the overall power and efficiency demands. The energy flow and conversion processes of the FPLG are analyzed, and the power and efficiency demands of the thermal-mechanical and mechanical-electrical energy conversion are confirmed. The energy and efficiency distributions of the expansion and compression strokes within a single stable operation cycle are analyzed and determined. Detailed design methodologies of crucial geometric dimensions and operational parameters of each key component are described. The feasibility of the proposed decoupling design approach is validated through several design examples with different output power.

Studying the formation of non-linear bursts in fully turbulent channel flows

Science.gov (United States)

Encinar, Miguel P.; Jimenez, Javier

2017-11-01

Linear transient growth has been suggested as a possible explanation for the intermittent behaviour, or `bursting', in shear flows with a stable mean velocity profile. Analysing fully non-linear DNS databases yields a similar Orr+lift-up mechanism, but acting on spatially localised wave packets rather than on monochromatic infinite wavetrains. The Orr mechanism requires the presence of backwards-leaning wall-normal velocity perturbations as initial condition, but the linear theory fails to clarify how these perturbations are formed. We investigate the latter in a time-resolved wavelet-filtered turbulent channel database, which allows us to assign an amplitude and an inclination angle to a flow region of selected size. This yields regions that match the dynamics of linear Orr for short times. We find that a short streamwise velocity (u) perturbation (i.e. a streak meander) consistently appears before the burst, but disappears before the burst reaches its maximum amplitude. Lift-up then generates a longer streamwise velocity perturbation. The initial streamwise velocity is also found to be backwards-leaning, contrary to the averaged energy-containing scales, which are known to be tilted forward. Funded by the ERC COTURB project.

Transition to turbulence for flows without linear criticality

International Nuclear Information System (INIS)

Nagata, Masato

2010-01-01

It is well known that plane Couette flow (PCF) and pipe flow (PF) are linearly stable against arbitrary three-dimensional perturbations at any finite Reynolds number, so that transitions from the basic laminar states, if they exist, must be abrupt. Due to this lack of linear criticality, weakly nonlinear analysis does not work in general and numerical approaches must be resorted to. It is only recently that non-trivial nonlinear states for these flows have been discovered numerically at finite Reynolds number as solutions bifurcating from infinity. The onset of turbulence in a subcritical transition is believed to be related to the appearance of steady/travelling wave states caused by disturbances of finite amplitude that take the flows out of the basin of attraction of the laminar state in phase space. In this paper, we introduce other flows that, in a similar way to PCF and PF, exhibit no linear critical point for the laminar states, namely flow in a square duct and sliding Couette flow in an annulus with a certain range of gap ratio. We shall show our recent numerical investigations on these flows where nonlinear travelling wave states are found for the first time by a homotopy approach. We believe that these states constitute the skeleton around which a time-dependent trajectory in the phase space is organized and help in understanding non-equilibrium turbulent processes.

Label Information Guided Graph Construction for Semi-Supervised Learning.

Science.gov (United States)

Zhuang, Liansheng; Zhou, Zihan; Gao, Shenghua; Yin, Jingwen; Lin, Zhouchen; Ma, Yi

2017-09-01

In the literature, most existing graph-based semi-supervised learning methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph. In this paper, we argue that it is beneficial to consider the label information in the graph learning stage. Specifically, by enforcing the weight of edges between labeled samples of different classes to be zero, we explicitly incorporate the label information into the state-of-the-art graph learning methods, such as the low-rank representation (LRR), and propose a novel semi-supervised graph learning method called semi-supervised low-rank representation. This results in a convex optimization problem with linear constraints, which can be solved by the linearized alternating direction method. Though we take LRR as an example, our proposed method is in fact very general and can be applied to any self-representation graph learning methods. Experiment results on both synthetic and real data sets demonstrate that the proposed graph learning method can better capture the global geometric structure of the data, and therefore is more effective for semi-supervised learning tasks.

Effect of chamber enclosure time on soil respiration flux: A comparison of linear and non-linear flux calculation methods

DEFF Research Database (Denmark)

Kandel, Tanka P; Lærke, Poul Erik; Elsgaard, Lars

2016-01-01

One of the shortcomings of closed chamber methods for soil respiration (SR) measurements is the decreased CO2 diffusion rate from soil to chamber headspace that may occur due to increased chamber CO2 concentrations. This feedback on diffusion rate may lead to underestimation of pre-deployment flu......One of the shortcomings of closed chamber methods for soil respiration (SR) measurements is the decreased CO2 diffusion rate from soil to chamber headspace that may occur due to increased chamber CO2 concentrations. This feedback on diffusion rate may lead to underestimation of pre...... was placed on fixed collars, and CO2 concentration in the chamber headspace were recorded at 1-s intervals for 45 min. Fluxes were measured in different soil types (sandy, sandy loam and organic soils), and for various manipulations (tillage, rain and drought) and soil conditions (temperature and moisture......) to obtain a range of fluxes with different shapes of flux curves. The linear method provided more stable flux results during short enclosure times (few min) but underestimated initial fluxes by 15–300% after 45 min deployment time. Non-linear models reduced the underestimation as average underestimation...

Stable lead geochronology of fine-grained sediments in Southern Lake Michigan

International Nuclear Information System (INIS)

Robbins, J.A.; Edgington, D.N.

1974-01-01

In a previous article, it was shown that the vertical distribution of stable lead in the fine-grained sediments of Lake Michigan reflects the history of cultural lead inputs. It was found that the lead distributions in dated cores are quantitatively described by a universal time-dependent loading or source function which is a linear combination of estimated annual inputs of atmospheric lead derived from the combustion of leaded gasoline and the burning of coal in and around Chicago since about 1800. The existence of such a source function for lead implies that stable lead itself may be used to date sediment cores. Mercury depth profiles in western Lake Erie sediments have shown several horizons which correspond to the development of local industrial use of mercury over the past forty years or so. The construction of the lead source function for Lake Michigan sediments was based on only four lead-210 dated cores. To establish the validity of the source function concept, it is applied to the distribution of lead determined in many cores previously obtained from southern Lake Michigan

Wall-crossing between stable and co-stable ADHM data

Science.gov (United States)

Ohkawa, Ryo

2018-06-01

We prove formula between Nekrasov partition functions defined from stable and co-stable ADHM data for the plane following method by Nakajima and Yoshioka (Kyoto J Math 51(2):263-335, 2011) based on the theory of wall-crossing formula developed by Mochizuki (Donaldson type invariants for algebraic surfaces: transition of moduli stacks, Lecture notes in mathematics, vol 1972, Springer, Berlin, 2009). This formula is similar to conjectures by Ito et al. [J High Energy Phys 2013(5):045, 2013, (4.1), (4.2)] for A1 singularity.

Permitted and forbidden sets in symmetric threshold-linear networks.

Science.gov (United States)

Hahnloser, Richard H R; Seung, H Sebastian; Slotine, Jean-Jacques

2003-03-01

The richness and complexity of recurrent cortical circuits is an inexhaustible source of inspiration for thinking about high-level biological computation. In past theoretical studies, constraints on the synaptic connection patterns of threshold-linear networks were found that guaranteed bounded network dynamics, convergence to attractive fixed points, and multistability, all fundamental aspects of cortical information processing. However, these conditions were only sufficient, and it remained unclear which were the minimal (necessary) conditions for convergence and multistability. We show that symmetric threshold-linear networks converge to a set of attractive fixed points if and only if the network matrix is copositive. Furthermore, the set of attractive fixed points is nonconnected (the network is multiattractive) if and only if the network matrix is not positive semidefinite. There are permitted sets of neurons that can be coactive at a stable steady state and forbidden sets that cannot. Permitted sets are clustered in the sense that subsets of permitted sets are permitted and supersets of forbidden sets are forbidden. By viewing permitted sets as memories stored in the synaptic connections, we provide a formulation of long-term memory that is more general than the traditional perspective of fixed-point attractor networks. There is a close correspondence between threshold-linear networks and networks defined by the generalized Lotka-Volterra equations.

Status of the SLC: Developments in Linear Collider physics

International Nuclear Information System (INIS)

Krejcik, P.

1994-11-01

This paper reviews the performance of the SLAC Linear Collider, both from the perspective of a machine delivering high luminosity polarized beams for physics, and as a test for future linear colliders. The development of the SLC taken place over a number of years and the steady improvements have been documented in previous review papers. As a review paper, the list references also serves as a bibliography, pointing to the work of the many people contributing to the upgrades and commissioning of the various SLC systems. The major upgrades for this present run have been an improved final focus optics, new low impedance vacuum chambers for the damping rings and improved polarization from the electron source. The performance of the SLC is driven to some extent by its unique 3-beam operation in which the linac accelerates both the electron and positron bunches for collision, as well as the electron bunch to produce the positrons. The special attention required to maintain stable operation in the face of the interactions caused by beam loading from the bunches will (fortunately exclamation point) not be an issue in future linear colliders. They will deal instead with the problems associated with handling long bunch trains

Linear Look-ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation

Directory of Open Access Journals (Sweden)

John L Kubie

2012-04-01

Full Text Available The crisp organization of the firing bumps of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed linear look-ahead, by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies of rigid modules of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-minute walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive-cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: The pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look ahead starting in any location and extending in any direction. We speculate that this process may: 1. compute linear paths to goals; 2. update grid cell firing during navigation; and 3. stabilize the rigid modules of grid cells and conjunctive cells.

Classically and quantum stable emergent universe from conservation laws

Energy Technology Data Exchange (ETDEWEB)

Campo, Sergio del; Herrera, Ramón [Instituto de Física, Pontificia Universidad Católica de Valparaíso, Avenida Brasil 2950, Casilla 4059, Valparaíso (Chile); Guendelman, Eduardo I. [Physics Department, Ben Gurion University of the Negev, Beer Sheva 84105 (Israel); Labraña, Pedro, E-mail: guendel@bgu.ac.il, E-mail: ramon.herrera@ucv.cl, E-mail: plabrana@ubiobio.cl [Departamento de Física, Universidad del Bío Bío and Grupo de Cosmología y Gravitación-UBB, Avenida Collao 1202, Casilla 5-C, Concepción (Chile)

2016-08-01

It has been recently pointed out by Mithani-Vilenkin [1-4] that certain emergent universe scenarios which are classically stable are nevertheless unstable semiclassically to collapse. Here, we show that there is a class of emergent universes derived from scale invariant two measures theories with spontaneous symmetry breaking (s.s.b) of the scale invariance, which can have both classical stability and do not suffer the instability pointed out by Mithani-Vilenkin towards collapse. We find that this stability is due to the presence of a symmetry in the 'emergent phase', which together with the non linearities of the theory, does not allow that the FLRW scale factor to be smaller that a certain minimum value a {sub 0} in a certain protected region.

Stable polarization short pulse passively Q-switched monolithic microchip laser with [110] cut Cr4+:YAG

International Nuclear Information System (INIS)

Wang, Y; Gong, M; Yan, P; Huang, L; Li, D

2009-01-01

A monolithic Nd:YAG microchip laser with [110] cut Cr 4+ :YAG is presented. The output beam is linearly polarized with polarization ratio higher than 100:1. The polarization direction is stable, independent of pump power, crystal temperature, LD temperature. In single longitudinal mode operation, stable 259 ps pulses at 2.5 kHz with 82 kW peak power and diffraction limited beam mode are output. With a simple and compact one-pass Nd:YVO 4 amplifier, 144 kW peak power is achieved. Single longitudinal and fundamental transverse mode is kept after passing through the amplifier stage. The microchip laser can be operated in two longitudinal modes with two sets of output pulses by increasing the pump power

Learning via Query Synthesis

KAUST Repository

Alabdulmohsin, Ibrahim Mansour

2017-05-07

Active learning is a subfield of machine learning that has been successfully used in many applications. One of the main branches of active learning is query synthe- sis, where the learning agent constructs artificial queries from scratch in order to reveal sensitive information about the underlying decision boundary. It has found applications in areas, such as adversarial reverse engineering, automated science, and computational chemistry. Nevertheless, the existing literature on membership query synthesis has, generally, focused on finite concept classes or toy problems, with a limited extension to real-world applications. In this thesis, I develop two spectral algorithms for learning halfspaces via query synthesis. The first algorithm is a maximum-determinant convex optimization method while the second algorithm is a Markovian method that relies on Khachiyan’s classical update formulas for solving linear programs. The general theme of these methods is to construct an ellipsoidal approximation of the version space and to synthesize queries, afterward, via spectral decomposition. Moreover, I also describe how these algorithms can be extended to other settings as well, such as pool-based active learning. Having demonstrated that halfspaces can be learned quite efficiently via query synthesis, the second part of this thesis proposes strategies for mitigating the risk of reverse engineering in adversarial environments. One approach that can be used to render query synthesis algorithms ineffective is to implement a randomized response. In this thesis, I propose a semidefinite program (SDP) for learning a distribution of classifiers, subject to the constraint that any individual classifier picked at random from this distributions provides reliable predictions with a high probability. This algorithm is, then, justified both theoretically and empirically. A second approach is to use a non-parametric classification method, such as similarity-based classification. In this

Angina Pectoris (Stable Angina)

Science.gov (United States)

... Peripheral Artery Disease Venous Thromboembolism Aortic Aneurysm More Angina Pectoris (Stable Angina) Updated:Aug 21,2017 You may have heard the term “angina pectoris” or “stable angina” in your doctor’s office, ...

Non-linear 3D simulations of current-driven instabilities in jets

International Nuclear Information System (INIS)

Ivanovski, S.; Bonanno, A.

2009-01-01

We present global 3D nonlinear simulations of the Taylor instability in the presence of vertical fields. The initial configuration is in equilibrium, which is achieved by a pressure gradient or an external potential force. The non linear evolution of the system leads to a stable equilibrium with a current free toroidal field. We find the that presence of a vertical poloidal field stabilize the system if B φ ∼B z . The implication of our findings for the physics of astrophysical jets are discussed.

Foundations of linear and generalized linear models

CERN Document Server

Agresti, Alan

2015-01-01

A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,

Modulated molecular beam mass spectrometry: A generalized expression for the ''reaction product vector'' for linear systems

International Nuclear Information System (INIS)

Chang, H.; Weinberg, W.H.

1977-01-01

A generalized expression is developed that relates the ''reaction product vector'', epsilon exp(-iphi), to the kinetic parameters of a linear system. The formalism is appropriate for the analysis of modulated molecular beam mass spectrometry data and facilitates the correlation of experimental results to (proposed) linear models. A study of stability criteria appropriate for modulated molecular beam mass spectrometry experiments is also presented. This investigation has led to interesting inherent limitations which have not heretofore been emphasized, as well as a delineation of the conditions under which stable chemical oscillations may occur in the reacting system

The role of intrinsic muscle properties for stable hopping-stability is achieved by the force-velocity relation

International Nuclear Information System (INIS)

Haeufle, D F B; Grimmer, S; Seyfarth, A

2010-01-01

A reductionist approach was presented to investigate which level of detail of the physiological muscle is required for stable locomotion. Periodic movements of a simplified one-dimensional hopping model with a Hill-type muscle (one contractile element, neither serial nor parallel elastic elements) were analyzed. Force-length and force-velocity relations of the muscle were varied in three levels of approximation (constant, linear and Hill-shaped nonlinear) resulting in nine different hopping models of different complexity. Stability of these models was evaluated by return map analysis and the performance by the maximum hopping height. The simplest model (constant force-length and constant force-velocity relations) outperformed all others in the maximum hopping height but was unstable. Stable hopping was achieved with linear and Hill-shaped nonlinear characteristic of the force-velocity relation. The characteristics of the force-length relation marginally influenced hopping stability. The results of this approach indicate that the intrinsic properties of the contractile element are responsible for stabilization of periodic movements. This connotes that (a) complex movements like legged locomotion could benefit from stabilizing effects of muscle properties, and (b) technical systems could benefit from the emerging stability when implementing biological characteristics into artificial muscles.

Predicting the dissolution kinetics of silicate glasses using machine learning

Science.gov (United States)

Anoop Krishnan, N. M.; Mangalathu, Sujith; Smedskjaer, Morten M.; Tandia, Adama; Burton, Henry; Bauchy, Mathieu

2018-05-01

Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic factors. Here, we assess the potential of data-driven models based on machine learning to predict the dissolution rates of various aluminosilicate glasses exposed to a wide range of solution pH values, from acidic to caustic conditions. Four classes of machine learning methods are investigated, namely, linear regression, support vector machine regression, random forest, and artificial neural network. We observe that, although linear methods all fail to describe the dissolution kinetics, the artificial neural network approach offers excellent predictions, thanks to its inherent ability to handle non-linear data. Overall, we suggest that a more extensive use of machine learning approaches could significantly accelerate the design of novel glasses with tailored properties.

Quantum Kramers model: Corrections to the linear response theory for continuous bath spectrum

Science.gov (United States)

Rips, Ilya

2017-01-01

Decay of the metastable state is analyzed within the quantum Kramers model in the weak-to-intermediate dissipation regime. The decay kinetics in this regime is determined by energy exchange between the unstable mode and the stable modes of thermal bath. In our previous paper [Phys. Rev. A 42, 4427 (1990), 10.1103/PhysRevA.42.4427], Grabert's perturbative approach to well dynamics in the case of the discrete bath [Phys. Rev. Lett. 61, 1683 (1988), 10.1103/PhysRevLett.61.1683] has been extended to account for the second order terms in the classical equations of motion (EOM) for the stable modes. Account of the secular terms reduces EOM for the stable modes to those of the forced oscillator with the time-dependent frequency (TDF oscillator). Analytic expression for the characteristic function of energy loss of the unstable mode has been derived in terms of the generating function of the transition probabilities for the quantum forced TDF oscillator. In this paper, the approach is further developed and applied to the case of the continuous frequency spectrum of the bath. The spectral density functions of the bath of stable modes are expressed in terms of the dissipative properties (the friction function) of the original bath. They simplify considerably for the one-dimensional systems, when the density of phonon states is constant. Explicit expressions for the fourth order corrections to the linear response theory result for the characteristic function of the energy loss and its cumulants are obtained for the particular case of the cubic potential with Ohmic (Markovian) dissipation. The range of validity of the perturbative approach in this case is determined (γ /ωbrate for the quantum and for the classical Kramers models. Results for the classical escape rate are in very good agreement with the numerical simulations for high barriers. The results can serve as an additional proof of the robustness and accuracy of the linear response theory.

Normal modified stable processes

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2002-01-01

Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added flexibility in the modelling of the dynamics of financial time series, of importance especially as regards OU based stochastic volatility models for equities. In the special case of the tempered stable OU process......This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse...

Using machine learning, neural networks and statistics to predict bankruptcy

NARCIS (Netherlands)

Pompe, P.P.M.; Feelders, A.J.; Feelders, A.J.

1997-01-01

Recent literature strongly suggests that machine learning approaches to classification outperform "classical" statistical methods. We make a comparison between the performance of linear discriminant analysis, classification trees, and neural networks in predicting corporate bankruptcy. Linear

Motion characteristic of a free piston linear engine

Energy Technology Data Exchange (ETDEWEB)

Xiao, Jin; Li, Qingfeng; Huang, Zhen [Key Laboratory for Power Machinery and Engineering of Ministry of Education, Shanghai Jiao Tong University, Shanghai, 200240 (China)

2010-04-15

A mathematical model of a free piston linear engine is established. The motion characteristics as well as the natural frequency map of the free piston are established. Then, its motion characteristics are successfully explained from the oscillation point. The full simulation model is built up in Matlab/Simulink for a better understanding of its motion features. The results show that the free piston system is a forced vibration system with variable damping coefficient and stiffness. Its steady-state response of periodical excitation is convergent which means that the system is stable under the periodical combustion. Furthermore, it has some unique features which are different from those of traditional Internal Combustion (IC) engines. (author)

On the linear programming bound for linear Lee codes.

Science.gov (United States)

Astola, Helena; Tabus, Ioan

2016-01-01

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.

Canonical-ensemble extended Lagrangian Born-Oppenheimer molecular dynamics for the linear scaling density functional theory.

Science.gov (United States)

Hirakawa, Teruo; Suzuki, Teppei; Bowler, David R; Miyazaki, Tsuyoshi

2017-10-11

We discuss the development and implementation of a constant temperature (NVT) molecular dynamics scheme that combines the Nosé-Hoover chain thermostat with the extended Lagrangian Born-Oppenheimer molecular dynamics (BOMD) scheme, using a linear scaling density functional theory (DFT) approach. An integration scheme for this canonical-ensemble extended Lagrangian BOMD is developed and discussed in the context of the Liouville operator formulation. Linear scaling DFT canonical-ensemble extended Lagrangian BOMD simulations are tested on bulk silicon and silicon carbide systems to evaluate our integration scheme. The results show that the conserved quantity remains stable with no systematic drift even in the presence of the thermostat.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum

Directory of Open Access Journals (Sweden)

Tjeerd V. olde Scheper

2018-01-01

Full Text Available Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized

Uses of stable isotopes

International Nuclear Information System (INIS)

Axente, Damian

1998-01-01

The most important fields of stable isotope use with examples are presented. These are: 1. Isotope dilution analysis: trace analysis, measurements of volumes and masses; 2. Stable isotopes as tracers: transport phenomena, environmental studies, agricultural research, authentication of products and objects, archaeometry, studies of reaction mechanisms, structure and function determination of complex biological entities, studies of metabolism, breath test for diagnostic; 3. Isotope equilibrium effects: measurement of equilibrium effects, investigation of equilibrium conditions, mechanism of drug action, study of natural processes, water cycle, temperature measurements; 4. Stable isotope for advanced nuclear reactors: uranium nitride with 15 N as nuclear fuel, 157 Gd for reactor control. In spite of some difficulties of stable isotope use, particularly related to the analytical techniques, which are slow and expensive, the number of papers reporting on this subject is steadily growing as well as the number of scientific meetings organized by International Isotope Section and IAEA, Gordon Conferences, and regional meeting in Germany, France, etc. Stable isotope application development on large scale is determined by improving their production technologies as well as those of labeled compound and the analytical techniques. (author)

Robust iterative learning control for multi-phase batch processes: an average dwell-time method with 2D convergence indexes

Science.gov (United States)

Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong

2018-01-01

In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.

Maximizing mandibular prosthesis stability utilizing linear occlusion, occlusal plane selection, and centric recording.

Science.gov (United States)

Williamson, Richard A; Williamson, Anne E; Bowley, John; Toothaker, Randy

2004-03-01

The stability of mandibular complete dentures may be improved by reducing the transverse forces on the denture base through linear (noninterceptive) occlusion, selecting an occlusal plane that reduces horizontal vectors of force at occlusal contact, and utilizing a central bearing intraoral gothic arch tracing to record jaw relations. This article is intended to acquaint the reader with one technique for providing stable complete denture prostheses using the aforementioned materials, devices, and procedures.

Using Machine Learning to Predict Student Performance

OpenAIRE

Pojon, Murat

2017-01-01

This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

Cascade Structure of Digital Predistorter for Power Amplifier Linearization

Directory of Open Access Journals (Sweden)

E. B. Solovyeva

2015-12-01

Full Text Available In this paper, a cascade structure of nonlinear digital predistorter (DPD synthesized by the direct learning adaptive algorithm is represented. DPD is used for linearization of power amplifier (PA characteristic, namely for compensation of PA nonlinear distortion. Blocks of the cascade DPD are described by different models: the functional link artificial neural network (FLANN, the polynomial perceptron network (PPN and the radially pruned Volterra model (RPVM. At synthesis of the cascade DPD there is possibility to overcome the ill conditionality problem due to reducing the dimension of DPD nonlinear operator approximation. Results of compensating nonlinear distortion in Wiener–Hammerstein model of PA at the GSM–signal with four carriers are shown. The highest accuracy of PA linearization is produced by the cascade DPD containing PPN and RPVM.

Enthalpy and high temperature relaxation kinetics of stable vapor-deposited glasses of toluene

International Nuclear Information System (INIS)

Bhattacharya, Deepanjan; Sadtchenko, Vlad

2014-01-01

Stable non-crystalline toluene films of micrometer and nanometer thicknesses were grown by vapor deposition at distinct rates and probed by fast scanning calorimetry. Fast scanning calorimetry is shown to be extremely sensitive to the structure of the vapor-deposited phase and was used to characterize simultaneously its kinetic stability and its thermodynamic properties. According to our analysis, transformation of vapor-deposited samples of toluene during heating with rates in excess 10 5 K s −1 follows the zero-order kinetics. The transformation rate correlates strongly with the initial enthalpy of the sample, which increases with the deposition rate according to sub-linear law. Analysis of the transformation kinetics of vapor-deposited toluene films of various thicknesses reveal a sudden increase in the transformation rate for films thinner than 250 nm. The change in kinetics seems to correlate with the surface roughness scale of the substrate. The implications of these findings for the formation mechanism and structure of vapor-deposited stable glasses are discussed

A Simple and Practical Linear Algebra Library Interface with Static Size Checking

Directory of Open Access Journals (Sweden)

Akinori Abe

2015-12-01

Full Text Available Linear algebra is a major field of numerical computation and is widely applied. Most linear algebra libraries (in most programming languages do not statically guarantee consistency of the dimensions of vectors and matrices, causing runtime errors. While advanced type systems—specifically, dependent types on natural numbers—can ensure consistency among the sizes of collections such as lists and arrays, such type systems generally require non-trivial changes to existing languages and application programs, or tricky type-level programming. We have developed a linear algebra library interface that verifies the consistency (with respect to dimensions of matrix operations by means of generative phantom types, implemented via fairly standard ML types and module system. To evaluate its usability, we ported to it a practical machine learning library from a traditional linear algebra library. We found that most of the changes required for the porting could be made mechanically, and changes that needed human thought are minor.

Stable isotopes labelled compounds

International Nuclear Information System (INIS)

1982-09-01

The catalogue on stable isotopes labelled compounds offers deuterium, nitrogen-15, and multiply labelled compounds. It includes: (1) conditions of sale and delivery, (2) the application of stable isotopes, (3) technical information, (4) product specifications, and (5) the complete delivery programme

Stable Boundary Layer Issues

NARCIS (Netherlands)

Steeneveld, G.J.

2012-01-01

Understanding and prediction of the stable atmospheric boundary layer is a challenging task. Many physical processes are relevant in the stable boundary layer, i.e. turbulence, radiation, land surface coupling, orographic turbulent and gravity wave drag, and land surface heterogeneity. The

Embedded Incremental Feature Selection for Reinforcement Learning

Science.gov (United States)

2012-05-01

Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

Linear algebra

CERN Document Server

Shilov, Georgi E

1977-01-01

Covers determinants, linear spaces, systems of linear equations, linear functions of a vector argument, coordinate transformations, the canonical form of the matrix of a linear operator, bilinear and quadratic forms, Euclidean spaces, unitary spaces, quadratic forms in Euclidean and unitary spaces, finite-dimensional space. Problems with hints and answers.

Remembering New Words: Integrating Early Memory Development into Word Learning

OpenAIRE

Wojcik, Erica H.

2013-01-01

In order to successfully acquire a new word, young children must learn the correct associations between labels and their referents. For decades, word-learning researchers have explored how young children are able to form these associations. However, in addition to learning label-referent mappings, children must also remember them. Despite the importance of memory processes in forming a stable lexicon, there has been little integration of early memory research into the study of early word lear...

Preparation and performance evaluation of novel alkaline stable anion exchange membranes

Science.gov (United States)

Irfan, Muhammad; Bakangura, Erigene; Afsar, Noor Ul; Hossain, Md. Masem; Ran, Jin; Xu, Tongwen

2017-07-01

Novel alkaline stable anion exchange membranes are prepared from various amounts of N-methyl dipicolylamine (MDPA) and brominated poly (2,6-dimethyl-1,4-phenylene oxide) (BPPO). The dipicolylamine and MDPA are synthesized through condensation reaction and confirmed by 1H NMR spectroscopy. The morphologies of prepared membranes are investigated by atomic force microscopy (AFM), fourier transform infrared spectroscopy (FTIR), 1H NMR spectroscopy and scanning electron microscopy (SEM). The electrochemical and physical properties of AEMs are tested comprising water uptake (WU), ion exchange capacity (IEC), alkaline stability, linear expansion ratio (LER), thermal stability and mechanical stability. The obtained hydroxide conductivity of MDPA-4 is 66.5 mS/cm at 80 °C. The MDPA-4 membrane shows good alkaline stability, high hydroxide conductivity, low methanol permeability (3.43 × 10-7 cm2/s), higher selectivity (8.26 × 107 mS s/cm3), less water uptake (41.1%) and lower linear expansion (11.1%) despite of high IEC value (1.62 mmol/g). The results prove that MDPA membranes have great potential application in anion exchange membrane fuel cell.

Fault Diagnosis of Supervision and Homogenization Distance Based on Local Linear Embedding Algorithm

Directory of Open Access Journals (Sweden)

Guangbin Wang

2015-01-01

Full Text Available In view of the problems of uneven distribution of reality fault samples and dimension reduction effect of locally linear embedding (LLE algorithm which is easily affected by neighboring points, an improved local linear embedding algorithm of homogenization distance (HLLE is developed. The method makes the overall distribution of sample points tend to be homogenization and reduces the influence of neighboring points using homogenization distance instead of the traditional Euclidean distance. It is helpful to choose effective neighboring points to construct weight matrix for dimension reduction. Because the fault recognition performance improvement of HLLE is limited and unstable, the paper further proposes a new local linear embedding algorithm of supervision and homogenization distance (SHLLE by adding the supervised learning mechanism. On the basis of homogenization distance, supervised learning increases the category information of sample points so that the same category of sample points will be gathered and the heterogeneous category of sample points will be scattered. It effectively improves the performance of fault diagnosis and maintains stability at the same time. A comparison of the methods mentioned above was made by simulation experiment with rotor system fault diagnosis, and the results show that SHLLE algorithm has superior fault recognition performance.

A thermodynamic study for the optimization of stable operation of free piston Stirling engines

Energy Technology Data Exchange (ETDEWEB)

Rogdakis, E.D.; Bormpilas, N.A.; Koniakos, I.K. [National Technical Univerisity, Athens (Greece). Dept. of Mechanical Engineering

2004-03-01

One of the most novel applications of the Stirling cycle is in the free piston configuration that was initially designed by W. Beale. In free piston Stirling engines (FPSEs), there are no mechanical linkages coupling the pistons or displacers, the motions of the reciprocating components follow the working gas pressure variations. Fillipo de Monte and G. Benvenuto have recently proposed a linearization technique of the dynamic balance equations. The aim of this paper is to predict the thermodynamic conditions for stable operation of FPSEs and their modeling. The equations of the angular velocity are solved analytically in terms of the working gas mass and the displacer-piston phase angle of the machine. Using the criterion of stable engine cyclic steady operation, a mathematically rigorous form is obtained for the main parameters of the engine. Furthermore, for simplicity reasons, thermodynamic magnitudes are obtained using the Schmidt analysis (isothermal model). (author)

A thermodynamic study for the optimization of stable operation of free piston Stirling engines

International Nuclear Information System (INIS)

Rogdakis, E.D.; Bormpilas, N.A.; Koniakos, I.K.

2004-01-01

One of the most novel applications of the Stirling cycle is in the free piston configuration that was initially designed by W. Beale. In free piston Stirling engines (FPSEs), there are no mechanical linkages coupling the pistons or displacers, the motions of the reciprocating components follow the working gas pressure variations. Fillipo de Monte and G. Benvenuto have recently proposed a linearization technique of the dynamic balance equations. The aim of this paper is to predict the thermodynamic conditions for stable operation of FPSEs and their modeling. The equations of the angular velocity are solved analytically in terms of the working gas mass and the displacer-piston phase angle of the machine. Using the criterion of stable engine cyclic steady operation, a mathematically rigorous form is obtained for the main parameters of the engine. Furthermore, for simplicity reasons, thermodynamic magnitudes are obtained using the Schmidt analysis (isothermal model)

On non-linear magnetic-charged black hole surrounded by quintessence

Science.gov (United States)

Nam, Cao H.

2018-06-01

We derive a non-linear magnetic-charged black hole surrounded by quintessence, which behaves asymptotically like the Schwarzschild black hole surrounded by quintessence but at the short distances like the dS geometry. The horizon properties of this black hole are investigated in detail. The thermodynamics of the black hole is studied in the local and global views. Finally, by calculating the heat capacity and the free energy, we point to that the black hole may undergo a thermal phase transition, between a larger unstable black hole and a smaller stable black hole, at a critical temperature.

An Entropy Stable h/p Non-Conforming Discontinuous Galerkin Method with the Summation-by-Parts Property

KAUST Repository

Friedrich, Lucas

2017-12-29

This work presents an entropy stable discontinuous Galerkin (DG) spectral element approximation for systems of non-linear conservation laws with general geometric (h) and polynomial order (p) non-conforming rectangular meshes. The crux of the proofs presented is that the nodal DG method is constructed with the collocated Legendre-Gauss-Lobatto nodes. This choice ensures that the derivative/mass matrix pair is a summation-by-parts (SBP) operator such that entropy stability proofs from the continuous analysis are discretely mimicked. Special attention is given to the coupling between nonconforming elements as we demonstrate that the standard mortar approach for DG methods does not guarantee entropy stability for non-linear problems, which can lead to instabilities. As such, we describe a precise procedure and modify the mortar method to guarantee entropy stability for general non-linear hyperbolic systems on h/p non-conforming meshes. We verify the high-order accuracy and the entropy conservation/stability of fully non-conforming approximation with numerical examples.

Endogenous Risks and Learning in Climate Change Decision Analysis

International Nuclear Information System (INIS)

O'Neill, B.C.; Ermoliev, Y.; Ermolieva, T.

2005-01-01

We analyze the effects of risks and learning on climate change decisions. A two-stage, dynamic, climate change stabilization problem is formulated. The explicit incorporation of ex-post learning induces risk aversion among ex-ante decisions, which is characterized in linear models by VaR- (Value at Risk) and CVaR-type risk (Conditional Value at Risk) measures. Combined with explicit introduction of 'safety' constraints, it creates a 'hit-or-miss' type decision making situation and shows that, even in linear models, learning may lead to either less or more restrictive ex-ante emission reductions. We analyze stylized elements of the model in order to identify the key factors driving outcomes, in particular, the critical role of quantiles of probability distributions characterizing key uncertainties

Learning to Estimate Dynamical State with Probabilistic Population Codes.

Directory of Open Access Journals (Sweden)

Joseph G Makin

2015-11-01

Full Text Available Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is known that this process of state estimation can be learned purely from the statistics of noisy observations. When the dynamics are simply linear with additive Gaussian noise, the optimal solution is the well known Kalman filter (KF, the parameters of which can be learned via latent-variable density estimation (the EM algorithm. The brain does not, however, directly manipulate matrices and vectors, but instead appears to represent probability distributions with the firing rates of population of neurons, "probabilistic population codes." We show that a recurrent neural network-a modified form of an exponential family harmonium (EFH-that takes a linear probabilistic population code as input can learn, without supervision, to estimate the state of a linear dynamical system. After observing a series of population responses (spike counts to the position of a moving object, the network learns to represent the velocity of the object and forms nearly optimal predictions about the position at the next time-step. This result builds on our previous work showing that a similar network can learn to perform multisensory integration and coordinate transformations for static stimuli. The receptive fields of the trained network also make qualitative predictions about the developing and learning brain: tuning gradually emerges for higher-order dynamical states not explicitly present in the inputs, appearing as delayed tuning for the lower-order states.

Structure of acid-stable carmine.

Science.gov (United States)

Sugimoto, Naoki; Kawasaki, Yoko; Sato, Kyoko; Aoki, Hiromitsu; Ichi, Takahito; Koda, Takatoshi; Yamazaki, Takeshi; Maitani, Tamio

2002-02-01

Acid-stable carmine has recently been distributed in the U.S. market because of its good acid stability, but it is not permitted in Japan. We analyzed and determined the structure of the major pigment in acid-stable carmine, in order to establish an analytical method for it. Carminic acid was transformed into a different type of pigment, named acid-stable carmine, through amination when heated in ammonia solution. The features of the structure were clarified using a model compound, purpurin, in which the orientation of hydroxyl groups on the A ring of the anthraquinone skeleton is the same as that of carminic acid. By spectroscopic means and the synthesis of acid-stable carmine and purpurin derivatives, the structure of the major pigment in acid-stable carmine was established as 4-aminocarminic acid, a novel compound.

Evidence of a stable binary CdCa quasicrystalline phase

DEFF Research Database (Denmark)

Jiang, Jianzhong; Jensen, C.H.; Rasmussen, A.R.

2001-01-01

Quasicrystals with a primitive icosahedral structure and a quasilattice constant of 5.1215 Angstrom have been synthesized in a binary Cd-Ca system. The thermal stability of the quasicrystal has been investigated by in situ high-temperature x-ray powder diffraction using synchrotron radiation. It ....... It is demonstrated that the binary CdCa quasicrystal is thermodynamic stable up to its melting temperature. The linear thermal expansion coefficient of the quasicrystal is 2.765x10(-5) K-1. (C) 2001 American Institute of Physics.......Quasicrystals with a primitive icosahedral structure and a quasilattice constant of 5.1215 Angstrom have been synthesized in a binary Cd-Ca system. The thermal stability of the quasicrystal has been investigated by in situ high-temperature x-ray powder diffraction using synchrotron radiation...

Applications of stable isotopes

International Nuclear Information System (INIS)

Letolle, R.; Mariotti, A.; Bariac, T.

1991-06-01

This report reviews the historical background and the properties of stable isotopes, the methods used for their measurement (mass spectrometry and others), the present technics for isotope enrichment and separation, and at last the various present and foreseeable application (in nuclear energy, physical and chemical research, materials industry and research; tracing in industrial, medical and agronomical tests; the use of natural isotope variations for environmental studies, agronomy, natural resources appraising: water, minerals, energy). Some new possibilities in the use of stable isotope are offered. A last chapter gives the present state and forecast development of stable isotope uses in France and Europe

Learning automata theory and applications

CERN Document Server

Najim, K

1994-01-01

Learning systems have made a significant impact on all areas of engineering problems. They are attractive methods for solving many problems which are too complex, highly non-linear, uncertain, incomplete or non-stationary, and have subtle and interactive exchanges with the environment where they operate. The main aim of the book is to give a systematic treatment of learning automata and to produce a guide to a wide variety of ideas and methods that can be used in learning systems, including enough theoretical material to enable the user of the relevant techniques and concepts to understand why

Evolution of learning in fluctuating environments: when selection favors both social and exploratory individual learning.

Science.gov (United States)

Borenstein, Elhanan; Feldman, Marcus W; Aoki, Kenichi

2008-03-01

Cumulative cultural change requires organisms that are capable of both exploratory individual learning and faithful social learning. In our model, an organism's phenotype is initially determined innately (by its genotypic value) or by social learning (copying a phenotype from the parental generation), and then may or may not be modified by individual learning (exploration around the initial phenotype). The environment alternates periodically between two states, each defined as a certain range of phenotypes that can survive. These states may overlap, in which case the same phenotype can survive in both states, or they may not. We find that a joint social and exploratory individual learning strategy-the strategy that supports cumulative culture-is likely to spread when the environmental states do not overlap. In particular, when the environmental states are contiguous and mutation is allowed among the genotypic values, this strategy will spread in either moderately or highly stable environments, depending on the exact nature of the individual learning applied. On the other hand, natural selection often favors a social learning strategy without exploration when the environmental states overlap. We find only partial support for the "consensus" view, which holds that individual learning, social learning, and innate determination of behavior will evolve at short, intermediate, and long environmental periodicities, respectively.

Cures for the shock instability: Development of a shock-stable Roe scheme

CERN Document Server

Kim, S S; Rho, O H; Kyu-Hong, S

2003-01-01

This paper deals with the development of an improved Roe scheme that is free from the shock instability and still preserves the accuracy and efficiency of the original Roe's Flux Difference Splitting (FDS). Roe's FDS is known to possess good accuracy but to suffer from the shock instability, such as the carbuncle phenomenon. As the first step towards a shock-stable scheme, Roe's FDS is compared with the HLLE scheme to identify the source of the shock instability. Through a linear perturbation analysis on the odd-even decoupling problem, damping characteristic is examined and Mach number-based functions f and g are introduced to balance damping and feeding rates, which leads to a shock-stable Roe scheme. In order to satisfy the conservation of total enthalpy, which is crucial in predicting surface heat transfer rate in high-speed steady flows, an analysis of dissipation mechanism in the energy equation is carried out to find out the error source and to make the proposed scheme preserve total enthalpy. By modif...

Linear and non-linear optics of condensed matter

International Nuclear Information System (INIS)

McLean, T.P.

1977-01-01

Part I - Linear optics: 1. General introduction. 2. Frequency dependence of epsilon(ω, k vector). 3. Wave-vector dependence of epsilon(ω, k vector). 4. Tensor character of epsilon(ω, k vector). Part II - Non-linear optics: 5. Introduction. 6. A classical theory of non-linear response in one dimension. 7. The generalization to three dimensions. 8. General properties of the polarizability tensors. 9. The phase-matching condition. 10. Propagation in a non-linear dielectric. 11. Second harmonic generation. 12. Coupling of three waves. 13. Materials and their non-linearities. 14. Processes involving energy exchange with the medium. 15. Two-photon absorption. 16. Stimulated Raman effect. 17. Electro-optic effects. 18. Limitations of the approach presented here. (author)

Context and Deep Learning Design

Science.gov (United States)

Boyle, Tom; Ravenscroft, Andrew

2012-01-01

Conceptual clarification is essential if we are to establish a stable and deep discipline of technology enhanced learning. The technology is alluring; this can distract from deep design in a surface rush to exploit the affordances of the new technology. We need a basis for design, and a conceptual unit of organization, that are applicable across…

ALPS - A LINEAR PROGRAM SOLVER

Science.gov (United States)

Viterna, L. A.

1994-01-01

Linear programming is a widely-used engineering and management tool. Scheduling, resource allocation, and production planning are all well-known applications of linear programs (LP's). Most LP's are too large to be solved by hand, so over the decades many computer codes for solving LP's have been developed. ALPS, A Linear Program Solver, is a full-featured LP analysis program. ALPS can solve plain linear programs as well as more complicated mixed integer and pure integer programs. ALPS also contains an efficient solution technique for pure binary (0-1 integer) programs. One of the many weaknesses of LP solvers is the lack of interaction with the user. ALPS is a menu-driven program with no special commands or keywords to learn. In addition, ALPS contains a full-screen editor to enter and maintain the LP formulation. These formulations can be written to and read from plain ASCII files for portability. For those less experienced in LP formulation, ALPS contains a problem "parser" which checks the formulation for errors. ALPS creates fully formatted, readable reports that can be sent to a printer or output file. ALPS is written entirely in IBM's APL2/PC product, Version 1.01. The APL2 workspace containing all the ALPS code can be run on any APL2/PC system (AT or 386). On a 32-bit system, this configuration can take advantage of all extended memory. The user can also examine and modify the ALPS code. The APL2 workspace has also been "packed" to be run on any DOS system (without APL2) as a stand-alone "EXE" file, but has limited memory capacity on a 640K system. A numeric coprocessor (80X87) is optional but recommended. The standard distribution medium for ALPS is a 5.25 inch 360K MS-DOS format diskette. IBM, IBM PC and IBM APL2 are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.

Observation of a current-limited double layer in a linear turbulent-heating device

International Nuclear Information System (INIS)

Inuzuka, H.; Torii, Y.; Nagatsu, M.; Tsukishima, T.

1985-01-01

Time- and space-resolved measurements of strong double layers (DLs) have been carried out for the first time on a linear turbulent-heating device, together with those of fluctuation spectra and precise current measurements. A stable stong DL is formed even when the electric current through the DL is less than the so-called Bohm value. Discussion of the formation and decay processes is given, indicating a transition from an ion-acoustic DL to a monotonic DL

Explaining IT Implementation Through Group Learning

NARCIS (Netherlands)

Bondarouk, Tatiana; Sikkel, Nicolaas

2005-01-01

Implementation of an IT system in an organization takes a certain amount of time. System usage becomes stable when users have appropriated the system and new work practices have been established. We propose a concept of group learning as a framework to highlight relevant aspects of such a process. A

Setting Learning Analytics in Context: Overcoming the Barriers to Large-Scale Adoption

Science.gov (United States)

Ferguson, Rebecca; Macfadyen, Leah P.; Clow, Doug; Tynan, Belinda; Alexander, Shirley; Dawson, Shane

2014-01-01

A core goal for most learning analytic projects is to move from small-scale research towards broader institutional implementation, but this introduces a new set of challenges because institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires explicit and…

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

Energy Technology Data Exchange (ETDEWEB)

Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

International Nuclear Information System (INIS)

Bornholdt, S.

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback

Network Traffic Monitoring Using Poisson Dynamic Linear Models

Energy Technology Data Exchange (ETDEWEB)

Merl, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2011-05-09

In this article, we discuss an approach for network forensics using a class of nonstationary Poisson processes with embedded dynamic linear models. As a modeling strategy, the Poisson DLM (PoDLM) provides a very flexible framework for specifying structured effects that may influence the evolution of the underlying Poisson rate parameter, including diurnal and weekly usage patterns. We develop a novel particle learning algorithm for online smoothing and prediction for the PoDLM, and demonstrate the suitability of the approach to real-time deployment settings via a new application to computer network traffic monitoring.

Linearity and Non-linearity of Photorefractive effect in Materials ...

African Journals Online (AJOL)

In this paper we have studied the Linearity and Non-linearity of Photorefractive effect in materials using the band transport model. For low light beam intensities the change in the refractive index is proportional to the electric field for linear optics while for non- linear optics the change in refractive index is directly proportional ...

INFORMATION PROVISION OF DISTANCE LEARNING SYSTEM

Directory of Open Access Journals (Sweden)

Viacheslav M. Oleksenko

2010-09-01

Full Text Available The article deals with the results of the research concerning the relevant information resources elaborated and introduced into the pedagogical process by the author. The peculiarities of the first in Ukraine dictionary on theory and practice of distance learning, distance course “Linear Algebra” and the course-book “Linear Algebra and Analytical Geometry”, which promote the raising in quality of education and training of specialists, are revealed.

A square-plate piezoelectric linear motor operating in two orthogonal and isomorphic face-diagonal-bending modes.

Science.gov (United States)

Ci, Penghong; Chen, Zhijiang; Liu, Guoxi; Dong, Shuxiang

2014-01-01

We report a piezoelectric linear motor made of a single Pb(Zr,Ti)O3 square-plate, which operates in two orthogonal and isomorphic face-diagonal-bending modes to produce precision linear motion. A 15 × 15 × 2 mm prototype was fabricated, and the motor generated a driving force of up to 1.8 N and a speed of 170 mm/s under an applied voltage of 100 Vpp at the resonance frequency of 136.5 kHz. The motor shows such advantages as large driving force under relatively low driving voltage, simple structure, and stable motion because of its isomorphic face-diagonal-bending mode.

Influence of a high vacuum on the precise positioning using an ultrasonic linear motor.

Science.gov (United States)

Kim, Wan-Soo; Lee, Dong-Jin; Lee, Sun-Kyu

2011-01-01

This paper presents an investigation of the ultrasonic linear motor stage for use in a high vacuum environment. The slider table is driven by the hybrid bolt-clamped Langevin-type ultrasonic linear motor, which is excited with its different modes of natural frequencies in both lateral and longitudinal directions. In general, the friction behavior in a vacuum environment becomes different from that in an environment of atmospheric pressure and this difference significantly affects the performance of the ultrasonic linear motor. In this paper, to consistently provide stable and high power of output in a high vacuum, frequency matching was conducted. Moreover, to achieve the fine control performance in the vacuum environment, a modified nominal characteristic trajectory following control method was adopted. Finally, the stage was operated under high vacuum condition, and the operating performances were investigated compared with that of a conventional PI compensator. As a result, robustness of positioning was accomplished in a high vacuum condition with nanometer-level accuracy.

Influence of a high vacuum on the precise positioning using an ultrasonic linear motor

International Nuclear Information System (INIS)

Kim, Wan-Soo; Lee, Dong-Jin; Lee, Sun-Kyu

2011-01-01

This paper presents an investigation of the ultrasonic linear motor stage for use in a high vacuum environment. The slider table is driven by the hybrid bolt-clamped Langevin-type ultrasonic linear motor, which is excited with its different modes of natural frequencies in both lateral and longitudinal directions. In general, the friction behavior in a vacuum environment becomes different from that in an environment of atmospheric pressure and this difference significantly affects the performance of the ultrasonic linear motor. In this paper, to consistently provide stable and high power of output in a high vacuum, frequency matching was conducted. Moreover, to achieve the fine control performance in the vacuum environment, a modified nominal characteristic trajectory following control method was adopted. Finally, the stage was operated under high vacuum condition, and the operating performances were investigated compared with that of a conventional PI compensator. As a result, robustness of positioning was accomplished in a high vacuum condition with nanometer-level accuracy.

Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process

Directory of Open Access Journals (Sweden)

Dazi Li

2015-01-01

Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.

A 3D Fractional-Order Chaotic System with Only One Stable Equilibrium and Controlling Chaos

Directory of Open Access Journals (Sweden)

Shiyun Shen

2017-01-01

Full Text Available One 3D fractional-order chaotic system with only one locally asymptotically stable equilibrium is reported. To verify the chaoticity, the maximum Lyapunov exponent (MAXLE with respect to the fractional-order and chaotic attractors are obtained by numerical calculation for this system. Furthermore, by linear scalar controller consisting of a single state variable, one control scheme for stabilization of the 3D fractional-order chaotic system is suggested. The numerical simulations show the feasibility of the control scheme.

Relativistic mean-field theory for unstable nuclei with non-linear σ and ω terms

International Nuclear Information System (INIS)

Sugahara, Y.; Toki, H.

1994-01-01

We search for a new parameter set for the description of stable as well as unstable nuclei in the wide mass range within the relativistic mean-field theory. We include a non-linear ω self-coupling term in addition to the non-linear σ self-coupling terms, the necessity of which is suggested by the relativistic Brueckner-Hartree-Fock (RBHF) theory of nuclear matter. We find two parameter sets, one of which is for nuclei above Z=20 and the other for nuclei below that. The calculated results agree very well with the existing data for finite nuclei. The parameter set for the heavy nuclei provides the equation of state of nuclear matter similar to the one of the RBHF theory. ((orig.))

Non-linear models for the detection of impaired cerebral blood flow autoregulation.

Science.gov (United States)

Chacón, Max; Jara, José Luis; Miranda, Rodrigo; Katsogridakis, Emmanuel; Panerai, Ronney B

2018-01-01

The ability to discriminate between normal and impaired dynamic cerebral autoregulation (CA), based on measurements of spontaneous fluctuations in arterial blood pressure (BP) and cerebral blood flow (CBF), has considerable clinical relevance. We studied 45 normal subjects at rest and under hypercapnia induced by breathing a mixture of carbon dioxide and air. Non-linear models with BP as input and CBF velocity (CBFV) as output, were implemented with support vector machines (SVM) using separate recordings for learning and validation. Dynamic SVM implementations used either moving average or autoregressive structures. The efficiency of dynamic CA was estimated from the model's derived CBFV response to a step change in BP as an autoregulation index for both linear and non-linear models. Non-linear models with recurrences (autoregressive) showed the best results, with CA indexes of 5.9 ± 1.5 in normocapnia, and 2.5 ± 1.2 for hypercapnia with an area under the receiver-operator curve of 0.955. The high performance achieved by non-linear SVM models to detect deterioration of dynamic CA should encourage further assessment of its applicability to clinical conditions where CA might be impaired.

Symposium on electron linear accelerators in honor of Richard B. Neal's 80th birthday: Proceedings

International Nuclear Information System (INIS)

Siemann, R.H.

1998-07-01

The papers presented at the conference are: (1) the construction of SLAC and the role of R.B. Neal; (2) symposium speech; (3) lessons learned from the SLC; (4) alternate approaches to future electron-positron linear colliders; (5) the NLC technical program; (6) advanced electron linacs; (7) medical uses of linear accelerators; (8) linac-based, intense, coherent X-ray source using self-amplified spontaneous emission. Selected papers have been indexed separately for inclusion in the Energy Science and Technology Database

Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections

Science.gov (United States)

Burbank, Kendra S.; Kreiman, Gabriel

2012-01-01

Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body. PMID:22396630

Depression-biased reverse plasticity rule is required for stable learning at top-down connections.

Directory of Open Access Journals (Sweden)

Kendra S Burbank

Full Text Available Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.

Electrophysiological Correlates of Error Monitoring and Feedback Processing in Second Language Learning.

Science.gov (United States)

Bultena, Sybrine; Danielmeier, Claudia; Bekkering, Harold; Lemhöfer, Kristin

2017-01-01

Humans monitor their behavior to optimize performance, which presumably relies on stable representations of correct responses. During second language (L2) learning, however, stable representations have yet to be formed while knowledge of the first language (L1) can interfere with learning, which in some cases results in persistent errors. In order to examine how correct L2 representations are stabilized, this study examined performance monitoring in the learning process of second language learners for a feature that conflicts with their first language. Using EEG, we investigated if L2 learners in a feedback-guided word gender assignment task showed signs of error detection in the form of an error-related negativity (ERN) before and after receiving feedback, and how feedback is processed. The results indicated that initially, response-locked negativities for correct (CRN) and incorrect (ERN) responses were of similar size, showing a lack of internal error detection when L2 representations are unstable. As behavioral performance improved following feedback, the ERN became larger than the CRN, pointing to the first signs of successful error detection. Additionally, we observed a second negativity following the ERN/CRN components, the amplitude of which followed a similar pattern as the previous negativities. Feedback-locked data indicated robust FRN and P300 effects in response to negative feedback across different rounds, demonstrating that feedback remained important in order to update memory representations during learning. We thus show that initially, L2 representations may often not be stable enough to warrant successful error monitoring, but can be stabilized through repeated feedback, which means that the brain is able to overcome L1 interference, and can learn to detect errors internally after a short training session. The results contribute a different perspective to the discussion on changes in ERN and FRN components in relation to learning, by extending the

Learning in a game context: strategy choice by some keeps learning from evolving in others.

Science.gov (United States)

Dubois, Frédérique; Morand-Ferron, Julie; Giraldeau, Luc-Alain

2010-12-07

Behavioural decisions in a social context commonly have frequency-dependent outcomes and so require analysis using evolutionary game theory. Learning provides a mechanism for tracking changing conditions and it has frequently been predicted to supplant fixed behaviour in shifting environments; yet few studies have examined the evolution of learning specifically in a game-theoretic context. We present a model that examines the evolution of learning in a frequency-dependent context created by a producer-scrounger game, where producers search for their own resources and scroungers usurp the discoveries of producers. We ask whether a learning mutant that can optimize its use of producer and scrounger to local conditions can invade a population of non-learning individuals that play producer and scrounger with fixed probabilities. We find that learning provides an initial advantage but never evolves to fixation. Once a stable equilibrium is attained, the population is always made up of a majority of fixed players and a minority of learning individuals. This result is robust to variation in the initial proportion of fixed individuals, the rate of within- and between-generation environmental change, and population size. Such learning polymorphisms will manifest themselves in a wide range of contexts, providing an important element leading to behavioural syndromes.

Population Games, Stable Games, and Passivity

Directory of Open Access Journals (Sweden)

Michael J. Fox

2013-10-01

Full Text Available The class of “stable games”, introduced by Hofbauer and Sandholm in 2009, has the attractive property of admitting global convergence to equilibria under many evolutionary dynamics. We show that stable games can be identified as a special case of the feedback-system-theoretic notion of a “passive” dynamical system. Motivated by this observation, we develop a notion of passivity for evolutionary dynamics that complements the definition of the class of stable games. Since interconnections of passive dynamical systems exhibit stable behavior, we can make conclusions about passive evolutionary dynamics coupled with stable games. We show how established evolutionary dynamics qualify as passive dynamical systems. Moreover, we exploit the flexibility of the definition of passive dynamical systems to analyze generalizations of stable games and evolutionary dynamics that include forecasting heuristics as well as certain games with memory.

Linearization and efficiency enhancement techniques for silicon power amplifiers from RF to mmW

CERN Document Server

Kerhervé, Eric

2015-01-01

This book provides an overview of current efficiency enhancement and linearization techniques for silicon power amplifier designs. It examines the latest state of the art technologies and design techniques to address challenges for RF cellular mobile, base stations, and RF and mmW WLAN applications. Coverage includes material on current silicon (CMOS, SiGe) RF and mmW power amplifier designs, focusing on advantages and disadvantages compared with traditional GaAs implementations. With this book you will learn: The principles of linearization and efficiency improvement techniquesThe arch

Special set linear algebra and special set fuzzy linear algebra

OpenAIRE

Kandasamy, W. B. Vasantha; Smarandache, Florentin; Ilanthenral, K.

2009-01-01

The authors in this book introduce the notion of special set linear algebra and special set fuzzy Linear algebra, which is an extension of the notion set linear algebra and set fuzzy linear algebra. These concepts are best suited in the application of multi expert models and cryptology. This book has five chapters. In chapter one the basic concepts about set linear algebra is given in order to make this book a self contained one. The notion of special set linear algebra and their fuzzy analog...

LabData database sub-systems for post-processing and quality control of stable isotope and gas chromatography measurements

Science.gov (United States)

Suckow, A. O.

2013-12-01

Measurements need post-processing to obtain results that are comparable between laboratories. Raw data may need to be corrected for blank, memory, drift (change of reference values with time), linearity (dependence of reference on signal height) and normalized to international reference materials. Post-processing parameters need to be stored for traceability of results. State of the art stable isotope correction schemes are available based on MS Excel (Geldern and Barth, 2012; Gröning, 2011) or MS Access (Coplen, 1998). These are specialized to stable isotope measurements only, often only to the post-processing of a special run. Embedding of algorithms into a multipurpose database system was missing. This is necessary to combine results of different tracers (3H, 3He, 2H, 18O, CFCs, SF6...) or geochronological tools (Sediment dating e.g. with 210Pb, 137Cs), to relate to attribute data (submitter, batch, project, geographical origin, depth in core, well information etc.) and for further interpretation tools (e.g. lumped parameter modelling). Database sub-systems to the LabData laboratory management system (Suckow and Dumke, 2001) are presented for stable isotopes and for gas chromatographic CFC and SF6 measurements. The sub-system for stable isotopes allows the following post-processing: 1. automated import from measurement software (Isodat, Picarro, LGR), 2. correction for sample-to sample memory, linearity, drift, and renormalization of the raw data. The sub-system for gas chromatography covers: 1. storage of all raw data 2. storage of peak integration parameters 3. correction for blank, efficiency and linearity The user interface allows interactive and graphical control of the post-processing and all corrections by export to and plot in MS Excel and is a valuable tool for quality control. The sub-databases are integrated into LabData, a multi-user client server architecture using MS SQL server as back-end and an MS Access front-end and installed in four

Stable isotopic labeling-based quantitative targeted glycomics (i-QTaG).

Science.gov (United States)

Kim, Kyoung-Jin; Kim, Yoon-Woo; Kim, Yun-Gon; Park, Hae-Min; Jin, Jang Mi; Hwan Kim, Young; Yang, Yung-Hun; Kyu Lee, Jun; Chung, Junho; Lee, Sun-Gu; Saghatelian, Alan

2015-01-01

Mass spectrometry (MS) analysis combined with stable isotopic labeling is a promising method for the relative quantification of aberrant glycosylation in diseases and disorders. We developed a stable isotopic labeling-based quantitative targeted glycomics (i-QTaG) technique for the comparative and quantitative analysis of total N-glycans using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). We established the analytical procedure with the chemical derivatizations (i.e., sialic acid neutralization and stable isotopic labeling) of N-glycans using a model glycoprotein (bovine fetuin). Moreover, the i-QTaG using MALDI-TOF MS was evaluated with various molar ratios (1:1, 1:2, 1:5) of (13) C6 /(12) C6 -2-aminobenzoic acid-labeled glycans from normal human serum. Finally, this method was applied to direct comparison of the total N-glycan profiles between normal human sera (n = 8) and prostate cancer patient sera (n = 17). The intensities of the N-glycan peaks from i-QTaG method showed a good linearity (R(2) > 0.99) with the amount of the bovine fetuin glycoproteins. The ratios of relative intensity between the isotopically 2-AA labeled N-glycans were close to the theoretical molar ratios (1:1, 1:2, 1:5). We also demonstrated that the up-regulation of the Lewis antigen (~82%) in sera from prostate cancer patients. In this proof-of-concept study, we demonstrated that the i-QTaG method, which enables to achieve a reliable comparative quantitation of total N-glycans via MALDI-TOF MS analysis, has the potential to diagnose and monitor alterations in glycosylation associated with disease states or biotherapeutics. © 2015 American Institute of Chemical Engineers.

A novel Lagrangian approach for the stable numerical simulation of fault and fracture mechanics

Science.gov (United States)

Franceschini, Andrea; Ferronato, Massimiliano; Janna, Carlo; Teatini, Pietro

2016-06-01

The simulation of the mechanics of geological faults and fractures is of paramount importance in several applications, such as ensuring the safety of the underground storage of wastes and hydrocarbons or predicting the possible seismicity triggered by the production and injection of subsurface fluids. However, the stable numerical modeling of ground ruptures is still an open issue. The present work introduces a novel formulation based on the use of the Lagrange multipliers to prescribe the constraints on the contact surfaces. The variational formulation is modified in order to take into account the frictional work along the activated fault portion according to the principle of maximum plastic dissipation. The numerical model, developed in the framework of the Finite Element method, provides stable solutions with a fast convergence of the non-linear problem. The stabilizing properties of the proposed model are emphasized with the aid of a realistic numerical example dealing with the generation of ground fractures due to groundwater withdrawal in arid regions.

Recent development of linear scaling quantum theories in GAMESS

Energy Technology Data Exchange (ETDEWEB)

Choi, Cheol Ho [Kyungpook National Univ., Daegu (Korea, Republic of)

2003-06-01

Linear scaling quantum theories are reviewed especially focusing on the method adopted in GAMESS. The three key translation equations of the fast multipole method (FMM) are deduced from the general polypolar expansions given earlier by Steinborn and Rudenberg. Simplifications are introduced for the rotation-based FMM that lead to a very compact FMM formalism. The OPS (optimum parameter searching) procedure, a stable and efficient way of obtaining the optimum set of FMM parameters, is established with complete control over the tolerable error {epsilon}. In addition, a new parallel FMM algorithm requiring virtually no inter-node communication, is suggested which is suitable for the parallel construction of Fock matrices in electronic structure calculations.

Pinning Synchronization of Linear Complex Coupling Synchronous Generators Network of Hydroelectric Generating Set

Directory of Open Access Journals (Sweden)

Xuefei Wu

2014-01-01

Full Text Available A novel linear complex system for hydroturbine-generator sets in multimachine power systems is suggested in this paper and synchronization of the power-grid networks is studied. The advanced graph theory and stability theory are combined to solve the problem. Here we derive a sufficient condition under which the synchronous state of power-grid networks is stable in disturbance attenuation. Finally, numerical simulations are provided to illustrate the effectiveness of the results by the IEEE 39 bus system.

Photon induced non-linear quantized double layer charging in quaternary semiconducting quantum dots.

Science.gov (United States)

Nair, Vishnu; Ananthoju, Balakrishna; Mohapatra, Jeotikanta; Aslam, M

2018-03-15

Room temperature quantized double layer charging was observed in 2 nm Cu 2 ZnSnS 4 (CZTS) quantum dots. In addition to this we observed a distinct non-linearity in the quantized double layer charging arising from UV light modulation of double layer. UV light irradiation resulted in a 26% increase in the integral capacitance at the semiconductor-dielectric (CZTS-oleylamine) interface of the quantum dot without any change in its core size suggesting that the cause be photocapacitive. The increasing charge separation at the semiconductor-dielectric interface due to highly stable and mobile photogenerated carriers cause larger electrostatic forces between the quantum dot and electrolyte leading to an enhanced double layer. This idea was supported by a decrease in the differential capacitance possible due to an enhanced double layer. Furthermore the UV illumination enhanced double layer gives us an AC excitation dependent differential double layer capacitance which confirms that the charging process is non-linear. This ultimately illustrates the utility of a colloidal quantum dot-electrolyte interface as a non-linear photocapacitor. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction of minimum temperatures in an alpine region by linear and non-linear post-processing of meteorological models

Directory of Open Access Journals (Sweden)

R. Barbiero

2007-05-01

Full Text Available Model Output Statistics (MOS refers to a method of post-processing the direct outputs of numerical weather prediction (NWP models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511–L60 and LAMI-3. Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself.

Privacy-Preserving Distributed Linear Regression on High-Dimensional Data

Directory of Open Access Journals (Sweden)

Gascón Adrià

2017-10-01

Full Text Available We propose privacy-preserving protocols for computing linear regression models, in the setting where the training dataset is vertically distributed among several parties. Our main contribution is a hybrid multi-party computation protocol that combines Yao’s garbled circuits with tailored protocols for computing inner products. Like many machine learning tasks, building a linear regression model involves solving a system of linear equations. We conduct a comprehensive evaluation and comparison of different techniques for securely performing this task, including a new Conjugate Gradient Descent (CGD algorithm. This algorithm is suitable for secure computation because it uses an efficient fixed-point representation of real numbers while maintaining accuracy and convergence rates comparable to what can be obtained with a classical solution using floating point numbers. Our technique improves on Nikolaenko et al.’s method for privacy-preserving ridge regression (S&P 2013, and can be used as a building block in other analyses. We implement a complete system and demonstrate that our approach is highly scalable, solving data analysis problems with one million records and one hundred features in less than one hour of total running time.

Constrained paths based on the Farey sequence in learning to juggle.

Science.gov (United States)

Yamamoto, Kota; Tsutsui, Seijiro; Yamamoto, Yuji

2015-12-01

In this article we report the results of a study conducted to investigate the learning dynamics of three-ball juggling from the perspective of frequency locking. Based on the Farey sequence, we predicted that four stable coordination patterns, corresponding to dwell ratios of 0.83, 0.75, 0.67, and 0.50, would appear in the learning process. We examined the learning process in terms of task performance, taking into account individual differences in the amount of learning. We observed that the participants acquired individual-specific coordination patterns in a relatively early stage of learning, and that those coordination patterns were preserved in subsequent learning, even though performance in terms of number of successful consecutive throws increased substantially. This increase appeared to be related to a reduction in spatial variability of the juggling movements. Finally, the observed coordination patterns were in agreement with the predicted patterns, with the proviso that the pattern corresponding to a dwell ratio of 0.50 was not realized and only a hint of evidence was found for the dwell ratio of 0.67. This implies that the dwell ratios of 0.83 and 0.75 in particular exhibited a stable coordination structure due to strong frequency locking between the temporal variables of juggling. Copyright © 2015 Elsevier B.V. All rights reserved.

An Investigation into the Relationship Between Distillate Yield and Stable Isotope Fractionation

Science.gov (United States)

Sowers, T.; Wagner, A. J.

2016-12-01

Recent breakthroughs in laser spectrometry have allowed for faster, more efficient analyses of stable isotopic ratios in water samples. Commercially available instruments from Los Gatos Research and Picarro allow users to quickly analyze a wide range of samples, from seawater to groundwater, with accurate isotope ratios of D/H to within ± 0.2 ‰ and 18O/16O to within ± 0.03 ‰. While these instruments have increased the efficiency of stable isotope laboratories, they come with some major limitations, such as not being able to analyze hypersaline waters. The Los Gatos Research Liquid Water Isotope Analyzer (LWIA) can accurately and consistently measure the stable isotope ratios in waters with salinities ranging from 0 to 4 grams per liter (0 to 40 parts per thousand). In order to analyze water samples with salinities greater than 4 grams per liter, however, it was necessary to develop a consistent method through which to reduce salinity while causing as little fractionation as possible. Using a consistent distillation method, predictable fractionation of δ 18O and δ 2 H values was found to occur. This fractionation occurs according to a linear relationship with respect to the percent yield of the water in the sample. Using this method, samples with high salinity can be analyzed using laser spectrometry instruments, thereby enabling laboratories with Los Gatos or Picarro instruments to analyze those samples in house without having to dilute them using labor-intensive in-house standards or expensive premade standards.

Relationship between mathematical abstraction in learning parallel coordinates concept and performance in learning analytic geometry of pre-service mathematics teachers: an investigation

Science.gov (United States)

Nurhasanah, F.; Kusumah, Y. S.; Sabandar, J.; Suryadi, D.

2018-05-01

As one of the non-conventional mathematics concepts, Parallel Coordinates is potential to be learned by pre-service mathematics teachers in order to give them experiences in constructing richer schemes and doing abstraction process. Unfortunately, the study related to this issue is still limited. This study wants to answer a research question “to what extent the abstraction process of pre-service mathematics teachers in learning concept of Parallel Coordinates could indicate their performance in learning Analytic Geometry”. This is a case study that part of a larger study in examining mathematical abstraction of pre-service mathematics teachers in learning non-conventional mathematics concept. Descriptive statistics method is used in this study to analyze the scores from three different tests: Cartesian Coordinate, Parallel Coordinates, and Analytic Geometry. The participants in this study consist of 45 pre-service mathematics teachers. The result shows that there is a linear association between the score on Cartesian Coordinate and Parallel Coordinates. There also found that the higher levels of the abstraction process in learning Parallel Coordinates are linearly associated with higher student achievement in Analytic Geometry. The result of this study shows that the concept of Parallel Coordinates has a significant role for pre-service mathematics teachers in learning Analytic Geometry.

Attributional processes in the learned helplessness paradigm: behavioral effects of global attributions.

Science.gov (United States)

Mikulincer, M

1986-12-01

Following the learned helplessness paradigm, I assessed in this study the effects of global and specific attributions for failure on the generalization of performance deficits in a dissimilar situation. Helplessness training consisted of experience with noncontingent failures on four cognitive discrimination problems attributed to either global or specific causes. Experiment 1 found that performance in a dissimilar situation was impaired following exposure to globally attributed failure. Experiment 2 examined the behavioral effects of the interaction between stable and global attributions of failure. Exposure to unsolvable problems resulted in reduced performance in a dissimilar situation only when failure was attributed to global and stable causes. Finally, Experiment 3 found that learned helplessness deficits were a product of the interaction of global and internal attribution. Performance deficits following unsolvable problems were recorded when failure was attributed to global and internal causes. Results were discussed in terms of the reformulated learned helplessness model.

Low-rank sparse learning for robust visual tracking

KAUST Repository

Zhang, Tianzhu

2012-01-01

In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm capitalizes on the inherent low-rank structure of particle representations that are learned jointly. As such, it casts the tracking problem as a low-rank matrix learning problem. This low-rank sparse tracker (LRST) has a number of attractive properties. (1) Since LRST adaptively updates dictionary templates, it can handle significant changes in appearance due to variations in illumination, pose, scale, etc. (2) The linear representation in LRST explicitly incorporates background templates in the dictionary and a sparse error term, which enables LRST to address the tracking drift problem and to be robust against occlusion respectively. (3) LRST is computationally attractive, since the low-rank learning problem can be efficiently solved as a sequence of closed form update operations, which yield a time complexity that is linear in the number of particles and the template size. We evaluate the performance of LRST by applying it to a set of challenging video sequences and comparing it to 6 popular tracking methods. Our experiments show that by representing particles jointly, LRST not only outperforms the state-of-the-art in tracking accuracy but also significantly improves the time complexity of methods that use a similar sparse linear representation model for particles [1]. © 2012 Springer-Verlag.

Linear Algebraic Method for Non-Linear Map Analysis

International Nuclear Information System (INIS)

Yu, L.; Nash, B.

2009-01-01

We present a newly developed method to analyze some non-linear dynamics problems such as the Henon map using a matrix analysis method from linear algebra. Choosing the Henon map as an example, we analyze the spectral structure, the tune-amplitude dependence, the variation of tune and amplitude during the particle motion, etc., using the method of Jordan decomposition which is widely used in conventional linear algebra.

Model structure learning: A support vector machine approach for LPV linear-regression models

NARCIS (Netherlands)

Toth, R.; Laurain, V.; Zheng, W-X.; Poolla, K.

2011-01-01

Accurate parametric identification of Linear Parameter-Varying (LPV) systems requires an optimal prior selection of a set of functional dependencies for the parametrization of the model coefficients. Inaccurate selection leads to structural bias while over-parametrization results in a variance

The Relationship between Residential Electricity Consumption and Income: A Piecewise Linear Model with Panel Data

Directory of Open Access Journals (Sweden)

Yanan Liu

2016-10-01

Full Text Available There are many uncertainties and risks in residential electricity consumption associated with economic development. Knowledge of the relationship between residential electricity consumption and its key determinant—income—is important to the sustainable development of the electric power industry. Using panel data from 30 provinces for the 1995–2012 period, this study investigates how residential electricity consumption changes as incomes increase in China. Previous studies typically used linear or quadratic double-logarithmic models imposing ex ante restrictions on the indistinct relationship between residential electricity consumption and income. Contrary to those models, we employed a reduced piecewise linear model that is self-adaptive and highly flexible and circumvents the problem of “prior restrictions”. Robust tests of different segment specifications and regression methods are performed to ensure the validity of the research. The results provide strong evidence that the income elasticity was approximately one, and it remained stable throughout the estimation period. The income threshold at which residential electricity consumption automatically remains stable or slows has not been reached. To ensure the sustainable development of the electric power industry, introducing higher energy efficiency standards for electrical appliances and improving income levels are vital. Government should also emphasize electricity conservation in the industrial sector rather than in residential sector.

Synthesis, Characterization and Biological Studies of New Linear Thermally Stable Schiff Base Polymers with Flexible Spacers.

Science.gov (United States)

Qureshi, Farah; Khuhawar, Muhammad Yar; Jahangir, Taj Muhammad; Channar, Abdul Hamid

2016-01-01

Five new linear Schiff base polymers having azomethine structures, ether linkages and extended aliphatic chain lengths with flexible spacers were synthesized by polycondensation of dialdehyde (monomer) with aliphatic and aromatic diamines. The formation yields of monomer and polymers were obtained within 75-92%. The polymers with flexible spacers of n-hexane were somewhat soluble in acetone, chloroform, THF, DMF and DMSO on heating. The monomer and polymers were characterized by melting point, elemental microanalysis, FT-IR, (1)HNMR, UV-Vis spectroscopy, thermogravimetry (TG), differential thermal analysis (DTA), fluorescence emission, scanning electron microscopy (SEM) and viscosities and thermodynamic parameters measurements of their dilute solutions. The studies supported formation of the monomer and polymers and on the basis of these studies their structures have been assigned. The synthesized polymers were tested for their antibacterial and antifungal activities.

Undergraduate Political Communication in Action: Volunteer Experiences in a Situated Learning Course

Science.gov (United States)

Brubaker, Jennifer

2011-01-01

In many college classes, students spend their time learning about the theories from the linear logic of a textbook. However, true learning occurs when these theories are integrated with hands-on authentic experiences. Situated learning courses are designed to bridge the gap between the theoretical and the authentic. Students apply classroom…

Factors affecting metacognition of undergraduate nursing students in a blended learning environment.

Science.gov (United States)

Hsu, Li-Ling; Hsieh, Suh-Ing

2014-06-01

This paper is a report of a study to examine the influence of demographic, learning involvement and learning performance variables on metacognition of undergraduate nursing students in a blended learning environment. A cross-sectional, correlational survey design was adopted. Ninety-nine students invited to participate in the study were enrolled in a professional nursing ethics course at a public nursing college. The blended learning intervention is basically an assimilation of classroom learning and online learning. Simple linear regression showed significant associations between frequency of online dialogues, the Case Analysis Attitude Scale scores, the Case Analysis Self Evaluation Scale scores, the Blended Learning Satisfaction Scale scores, and Metacognition Scale scores. Multiple linear regression indicated that frequency of online dialogues, the Case Analysis Self Evaluation Scale and the Blended Learning Satisfaction Scale were significant independent predictors of metacognition. Overall, the model accounted for almost half of the variance in metacognition. The blended learning module developed in this study proved successful in the end as a catalyst for the exercising of metacognitive abilities by the sample of nursing students. Learners are able to develop metacognitive ability in comprehension, argumentation, reasoning and various forms of higher order thinking through the blended learning process. © 2013 Wiley Publishing Asia Pty Ltd.

Bayes-Optimal Entropy Pursuit for Active Choice-Based Preference Learning

OpenAIRE

Pallone, Stephen N.; Frazier, Peter I.; Henderson, Shane G.

2017-01-01

We analyze the problem of learning a single user's preferences in an active learning setting, sequentially and adaptively querying the user over a finite time horizon. Learning is conducted via choice-based queries, where the user selects her preferred option among a small subset of offered alternatives. These queries have been shown to be a robust and efficient way to learn an individual's preferences. We take a parametric approach and model the user's preferences through a linear classifier...

Extreme learning machines 2013 algorithms and applications

CERN Document Server

Toh, Kar-Ann; Romay, Manuel; Mao, Kezhi

2014-01-01

In recent years, ELM has emerged as a revolutionary technique of computational intelligence, and has attracted considerable attentions. An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods. The outstanding merits of extreme learning machine (ELM) are its fast learning speed, trivial human intervene and high scalability.   This book contains some selected papers from the International Conference on Extreme Learning Machine 2013, which was held in Beijing China, October 15-17, 2013. This conference aims to bring together the researchers and practitioners of extreme learning machine from a variety of fields including artificial intelligence, biomedical engineering and bioinformatics, system modelling and control, and signal and image processing, to promote research and discu...

Analysis of junior high school students' attempt to solve a linear inequality problem

Science.gov (United States)

Taqiyuddin, Muhammad; Sumiaty, Encum; Jupri, Al

2017-08-01

Linear inequality is one of fundamental subjects within junior high school mathematics curricula. Several studies have been conducted to asses students' perform on linear inequality. However, it can hardly be found that linear inequality problems are in the form of "ax + b condition leads to the research questions concerning students' attempt on solving a simple linear inequality problem in this form. In order to do so, the written test was administered to 58 students from two schools in Bandung followed by interviews. The other sources of the data are from teachers' interview and mathematics books used by students. After that, the constant comparative method was used to analyse the data. The result shows that the majority approached the question by doing algebraic operations. Interestingly, most of them did it incorrectly. In contrast, algebraic operations were correctly used by some of them. Moreover, the others performed expected-numbers solution, rewriting the question, translating the inequality into words, and blank answer. Furthermore, we found that there is no one who was conscious of the existence of all-numbers solution. It was found that this condition is reasonably due to how little the learning components concern about why a procedure of solving a linear inequality works and possibilities of linear inequality solution.