International Nuclear Information System (INIS)
Li, Huihua
1992-01-01
The traditional generalization methods such as FIKE's macro-operator learning and Explanation-Based Learning (EBL) deal with totally ordered plans. They generalize only the plan operators and the conditions under which the generalized plan can be applied in its initial total order, but not the partial order among operators in which the generalized plan can be successfully executed. In this paper, we extend the notion of the EBL on the partial order of plans. A new method is presented for learning, from a totally or partially ordered plan, partially ordered macro-operators (generalized plans) each of which requires a set of the weakest conditions for its reuse. It is also valuable for generalizing partially ordered plans. The operators are generalized in the FIKE's triangle table. We introduce the domain axioms to generate the constraints for the consistency of generalized states. After completing the triangle table with the information concerning the operator destructions (interactions), we obtain the global explanation of the partial order on the operators. Then, we represent all the necessary ordering relations by a directed graph. The exploitation of this graph permits to explicate the dependence between the partial orders and the constraints among the parameters of generalized operators, and allows all the solutions to be obtained. (author) [fr
DEFF Research Database (Denmark)
Darkner, Sune; Sporring, Jon
2011-01-01
Mutual Information (MI) and normalized mutual information (NMI) are popular choices as similarity measure for multimodal image registration. Presently, one of two approaches is often used for estimating these measures: The Parzen Window (PW) and the Generalized Partial Volume (GPV). Their theoret...... of view as well as w.r.t. computational complexity. Finally, we present algorithms for both approaches for NMI which is comparable in speed to Sum of Squared Differences (SSD), and we illustrate the differences between PW and GPV on a number of registration examples....
Partial Differential Equations in General Relativity
International Nuclear Information System (INIS)
Choquet-Bruhat, Yvonne
2008-01-01
General relativity is a physical theory basic in the modeling of the universe at the large and small scales. Its mathematical formulation, the Einstein partial differential equations, are geometrically simple, but intricate for the analyst, involving both hyperbolic and elliptic PDE, with local and global problems. Many problems remain open though remarkable progress has been made recently towards their solutions. Alan Rendall's book states, in a down-to-earth form, fundamental results used to solve different types of equations. In each case he gives applications to special models as well as to general properties of Einsteinian spacetimes. A chapter on ODE contains, in particular, a detailed discussion of Bianchi spacetimes. A chapter entitled 'Elliptic systems' treats the Einstein constraints. A chapter entitled 'Hyperbolic systems' is followed by a chapter on the Cauchy problem and a chapter 'Global results' which contains recently proved theorems. A chapter is dedicated to the Einstein-Vlasov system, of which the author is a specialist. On the whole, the book surveys, in a concise though precise way, many essential results of recent interest in mathematical general relativity, and it is very clearly written. Each chapter is followed by an up to date bibliography. In conclusion, this book will be a valuable asset to relativists who wish to learn clearly-stated mathematical results and to mathematicians who want to penetrate into the subtleties of general relativity, as a mathematical and physical theory. (book review)
Partial Differential Equations in General Relativity
Energy Technology Data Exchange (ETDEWEB)
Choquet-Bruhat, Yvonne
2008-09-07
General relativity is a physical theory basic in the modeling of the universe at the large and small scales. Its mathematical formulation, the Einstein partial differential equations, are geometrically simple, but intricate for the analyst, involving both hyperbolic and elliptic PDE, with local and global problems. Many problems remain open though remarkable progress has been made recently towards their solutions. Alan Rendall's book states, in a down-to-earth form, fundamental results used to solve different types of equations. In each case he gives applications to special models as well as to general properties of Einsteinian spacetimes. A chapter on ODE contains, in particular, a detailed discussion of Bianchi spacetimes. A chapter entitled 'Elliptic systems' treats the Einstein constraints. A chapter entitled 'Hyperbolic systems' is followed by a chapter on the Cauchy problem and a chapter 'Global results' which contains recently proved theorems. A chapter is dedicated to the Einstein-Vlasov system, of which the author is a specialist. On the whole, the book surveys, in a concise though precise way, many essential results of recent interest in mathematical general relativity, and it is very clearly written. Each chapter is followed by an up to date bibliography. In conclusion, this book will be a valuable asset to relativists who wish to learn clearly-stated mathematical results and to mathematicians who want to penetrate into the subtleties of general relativity, as a mathematical and physical theory. (book review)
Testing the generalized partial credit model
Glas, Cornelis A.W.
1996-01-01
The partial credit model (PCM) (G.N. Masters, 1982) can be viewed as a generalization of the Rasch model for dichotomous items to the case of polytomous items. In many cases, the PCM is too restrictive to fit the data. Several generalizations of the PCM have been proposed. In this paper, a
Generalized solutions of nonlinear partial differential equations
Rosinger, EE
1987-01-01
During the last few years, several fairly systematic nonlinear theories of generalized solutions of rather arbitrary nonlinear partial differential equations have emerged. The aim of this volume is to offer the reader a sufficiently detailed introduction to two of these recent nonlinear theories which have so far contributed most to the study of generalized solutions of nonlinear partial differential equations, bringing the reader to the level of ongoing research.The essence of the two nonlinear theories presented in this volume is the observation that much of the mathematics concernin
Testing the generalized partial credit model
Glas, Cornelis A.W.
1996-01-01
The partial credit model (PCM) (G.N. Masters, 1982) can be viewed as a generalization of the Rasch model for dichotomous items to the case of polytomous items. In many cases, the PCM is too restrictive to fit the data. Several generalizations of the PCM have been proposed. In this paper, a generalization of the PCM (GPCM), a further generalization of the one-parameter logistic model, is discussed. The model is defined and the conditional maximum likelihood procedure for the method is describe...
Unsupervised Learning and Generalization
DEFF Research Database (Denmark)
Hansen, Lars Kai; Larsen, Jan
1996-01-01
The concept of generalization is defined for a general class of unsupervised learning machines. The generalization error is a straightforward extension of the corresponding concept for supervised learning, and may be estimated empirically using a test set or by statistical means-in close analogy ...... with supervised learning. The empirical and analytical estimates are compared for principal component analysis and for K-means clustering based density estimation......The concept of generalization is defined for a general class of unsupervised learning machines. The generalization error is a straightforward extension of the corresponding concept for supervised learning, and may be estimated empirically using a test set or by statistical means-in close analogy...
Generalized geometry and partial supersymmetry breaking
Energy Technology Data Exchange (ETDEWEB)
Triendl, Hagen Mathias
2010-08-15
This thesis consists of two parts. In the first part we use the formalism of (exceptional) generalized geometry to derive the scalar field space of SU(2) x SU(2)-structure compactifications. We show that in contrast to SU(3) x SU(3) structures, there is no dynamical SU(2) x SU(2) structure interpolating between an SU(2) structure and an identity structure. Furthermore, we derive the scalar manifold of the low-energy effective action for consistent Kaluza-Klein truncations as expected from N = 4 supergravity. In the second part we then determine the general conditions for the existence of stable Minkowski and AdS N = 1 vacua in spontaneously broken gauged N = 2 supergravities and construct the general solution under the assumption that two appropriate commuting isometries exist in the hypermultiplet sector. Furthermore, we derive the low-energy effective action below the scale of partial supersymmetry breaking and show that it satisfies the constraints of N = 1 supergravity. We then apply the discussion to special quaternionic-Kaehler geometries which appear in the low-energy limit of SU(3) x SU(3)-structure compactifications and construct Killing vectors with the right properties. Finally we discuss the string theory realizations for these solutions. (orig.)
Generalized geometry and partial supersymmetry breaking
International Nuclear Information System (INIS)
Triendl, Hagen Mathias
2010-08-01
This thesis consists of two parts. In the first part we use the formalism of (exceptional) generalized geometry to derive the scalar field space of SU(2) x SU(2)-structure compactifications. We show that in contrast to SU(3) x SU(3) structures, there is no dynamical SU(2) x SU(2) structure interpolating between an SU(2) structure and an identity structure. Furthermore, we derive the scalar manifold of the low-energy effective action for consistent Kaluza-Klein truncations as expected from N = 4 supergravity. In the second part we then determine the general conditions for the existence of stable Minkowski and AdS N = 1 vacua in spontaneously broken gauged N = 2 supergravities and construct the general solution under the assumption that two appropriate commuting isometries exist in the hypermultiplet sector. Furthermore, we derive the low-energy effective action below the scale of partial supersymmetry breaking and show that it satisfies the constraints of N = 1 supergravity. We then apply the discussion to special quaternionic-Kaehler geometries which appear in the low-energy limit of SU(3) x SU(3)-structure compactifications and construct Killing vectors with the right properties. Finally we discuss the string theory realizations for these solutions. (orig.)
Partially Observed Mixtures of IRT Models: An Extension of the Generalized Partial-Credit Model
Von Davier, Matthias; Yamamoto, Kentaro
2004-01-01
The generalized partial-credit model (GPCM) is used frequently in educational testing and in large-scale assessments for analyzing polytomous data. Special cases of the generalized partial-credit model are the partial-credit model--or Rasch model for ordinal data--and the two parameter logistic (2PL) model. This article extends the GPCM to the…
A Generalized Partial Credit Model: Application of an EM Algorithm.
Muraki, Eiji
1992-01-01
The partial credit model with a varying slope parameter is developed and called the generalized partial credit model (GPCM). Analysis results for simulated data by this and other polytomous item-response models demonstrate that the rating formulation of the GPCM is adaptable to the analysis of polytomous item responses. (SLD)
Learning with partially labeled and interdependent data
Amini, Massih-Reza
2015-01-01
This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data. It reveals new applications, primarily web related, that transgress the classical machine learning framework through learning with interdependent data. The book traces how the semi-supervised paradigm and the learning to rank paradigm emerged from new web applications, leading to a massive production of heterogeneous textual data. It explains how semi-supervised learning techniques are widely used, but only allow a limited analysis of the information content and thus d
Constructing general partial differential equations using polynomial and neural networks.
Zjavka, Ladislav; Pedrycz, Witold
2016-01-01
Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transform the weighted sum of inputs to describe overall similarity relationships of trained and new testing input patterns. Differential polynomial neural networks form a new class of neural networks, which construct and solve an unknown general partial differential equation of a function of interest with selected substitution relative terms using non-linear multi-variable composite polynomials. The layers of the network generate simple and composite relative substitution terms whose convergent series combinations can describe partial dependent derivative changes of the input variables. This regression is based on trained generalized partial derivative data relations, decomposed into a multi-layer polynomial network structure. The sigmoidal function, commonly used as a nonlinear activation of artificial neurons, may transform some polynomial items together with the parameters with the aim to improve the polynomial derivative term series ability to approximate complicated periodic functions, as simple low order polynomials are not able to fully make up for the complete cycles. The similarity analysis facilitates substitutions for differential equations or can form dimensional units from data samples to describe real-world problems. Copyright © 2015 Elsevier Ltd. All rights reserved.
Optimal Designs for the Generalized Partial Credit Model
Bürkner, Paul-Christian; Schwabe, Rainer; Holling, Heinz
2018-01-01
Analyzing ordinal data becomes increasingly important in psychology, especially in the context of item response theory. The generalized partial credit model (GPCM) is probably the most widely used ordinal model and finds application in many large scale educational assessment studies such as PISA. In the present paper, optimal test designs are investigated for estimating persons' abilities with the GPCM for calibrated tests when item parameters are known from previous studies. We will derive t...
Estimation and variable selection for generalized additive partial linear models
Wang, Li
2011-08-01
We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.
BOOK REVIEW: Partial Differential Equations in General Relativity
Halburd, Rodney G.
2008-11-01
Although many books on general relativity contain an overview of the relevant background material from differential geometry, very little attention is usually paid to background material from the theory of differential equations. This is understandable in a first course on relativity but it often limits the kinds of problems that can be studied rigorously. Einstein's field equations lie at the heart of general relativity. They are a system of partial differential equations (PDEs) relating the curvature of spacetime to properties of matter. A central part of most problems in general relativity is to extract information about solutions of these equations. Most standard texts achieve this by studying exact solutions or numerical and analytical approximations. In the book under review, Alan Rendall emphasises the role of rigorous qualitative methods in general relativity. There has long been a need for such a book, giving a broad overview of the relevant background from the theory of partial differential equations, and not just from differential geometry. It should be noted that the book also covers the basic theory of ordinary differential equations. Although there are many good books on the rigorous theory of PDEs, methods related to the Einstein equations deserve special attention, not only because of the complexity and importance of these equations, but because these equations do not fit into any of the standard classes of equations (elliptic, parabolic, hyperbolic) that one typically encounters in a course on PDEs. Even specifying exactly what ones means by a Cauchy problem in general relativity requires considerable care. The main problem here is that the manifold on which the solution is defined is determined by the solution itself. This means that one does not simply define data on a submanifold. Rendall's book gives a good overview of applications and results from the qualitative theory of PDEs to general relativity. It would be impossible to give detailed
Hidden physics models: Machine learning of nonlinear partial differential equations
Raissi, Maziar; Karniadakis, George Em
2018-03-01
While there is currently a lot of enthusiasm about "big data", useful data is usually "small" and expensive to acquire. In this paper, we present a new paradigm of learning partial differential equations from small data. In particular, we introduce hidden physics models, which are essentially data-efficient learning machines capable of leveraging the underlying laws of physics, expressed by time dependent and nonlinear partial differential equations, to extract patterns from high-dimensional data generated from experiments. The proposed methodology may be applied to the problem of learning, system identification, or data-driven discovery of partial differential equations. Our framework relies on Gaussian processes, a powerful tool for probabilistic inference over functions, that enables us to strike a balance between model complexity and data fitting. The effectiveness of the proposed approach is demonstrated through a variety of canonical problems, spanning a number of scientific domains, including the Navier-Stokes, Schrödinger, Kuramoto-Sivashinsky, and time dependent linear fractional equations. The methodology provides a promising new direction for harnessing the long-standing developments of classical methods in applied mathematics and mathematical physics to design learning machines with the ability to operate in complex domains without requiring large quantities of data.
Qin, Jin; Tang, Siqi; Han, Congying; Guo, Tiande
2018-04-01
Partial fingerprint identification technology which is mainly used in device with small sensor area like cellphone, U disk and computer, has taken more attention in recent years with its unique advantages. However, owing to the lack of sufficient minutiae points, the conventional method do not perform well in the above situation. We propose a new fingerprint matching technique which utilizes ridges as features to deal with partial fingerprint images and combines the modified generalized Hough transform and scoring strategy based on machine learning. The algorithm can effectively meet the real-time and space-saving requirements of the resource constrained devices. Experiments on in-house database indicate that the proposed algorithm have an excellent performance.
More on PT-Symmetry in (Generalized Effect Algebras and Partial Groups
Directory of Open Access Journals (Sweden)
J. Paseka
2011-01-01
Full Text Available We continue in the direction of our paper on PT-Symmetry in (Generalized Effect Algebras and Partial Groups. Namely we extend our considerations to the setting of weakly ordered partial groups. In this setting, any operator weakly ordered partial group is a pasting of its partially ordered commutative subgroups of linear operators with a fixed dense domain over bounded operators. Moreover, applications of our approach for generalized effect algebras are mentioned.
Informal and Formal Learning of General Practitioners
Spaan, Nadia Roos; Dekker, Anne R. J.; van der Velden, Alike W.; de Groot, Esther
2016-01-01
Purpose: The purpose of this study is to understand the influence of formal learning from a web-based training and informal (workplace) learning afterwards on the behaviour of general practitioners (GPs) with respect to prescription of antibiotics. Design/methodology/approach: To obtain insight in various learning processes, semi-structured…
Learning partial differential equations via data discovery and sparse optimization.
Schaeffer, Hayden
2017-01-01
We investigate the problem of learning an evolution equation directly from some given data. This work develops a learning algorithm to identify the terms in the underlying partial differential equations and to approximate the coefficients of the terms only using data. The algorithm uses sparse optimization in order to perform feature selection and parameter estimation. The features are data driven in the sense that they are constructed using nonlinear algebraic equations on the spatial derivatives of the data. Several numerical experiments show the proposed method's robustness to data noise and size, its ability to capture the true features of the data, and its capability of performing additional analytics. Examples include shock equations, pattern formation, fluid flow and turbulence, and oscillatory convection.
Informal and formal learning of general practitioners
Spaan, Nadia Roos; Dekker, Anne R. J.; van der Velden, Alike W.; de Groot, Esther
2016-01-01
Purpose The purpose of this study is to understand the influence of formal learning from a web-based training and informal (workplace) learning afterwards on the behaviour of general practitioners (GPs) with respect to prescription of antibiotics. Design/methodology/approach To obtain insight in
Context generalization in Drosophila visual learning requires the mushroom bodies
Liu, Li; Wolf, Reinhard; Ernst, Roman; Heisenberg, Martin
1999-08-01
The world is permanently changing. Laboratory experiments on learning and memory normally minimize this feature of reality, keeping all conditions except the conditioned and unconditioned stimuli as constant as possible. In the real world, however, animals need to extract from the universe of sensory signals the actual predictors of salient events by separating them from non-predictive stimuli (context). In principle, this can be achieved ifonly those sensory inputs that resemble the reinforcer in theirtemporal structure are taken as predictors. Here we study visual learning in the fly Drosophila melanogaster, using a flight simulator,, and show that memory retrieval is, indeed, partially context-independent. Moreover, we show that the mushroom bodies, which are required for olfactory but not visual or tactile learning, effectively support context generalization. In visual learning in Drosophila, it appears that a facilitating effect of context cues for memory retrieval is the default state, whereas making recall context-independent requires additional processing.
A Model Fit Statistic for Generalized Partial Credit Model
Liang, Tie; Wells, Craig S.
2009-01-01
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…
Topographic generalization of tactile perceptual learning.
Harrar, Vanessa; Spence, Charles; Makin, Tamar R
2014-02-01
Perceptual learning can improve our sensory abilities. Understanding its underlying mechanisms, in particular, when perceptual learning generalizes, has become a focus of research and controversy. Specifically, there is little consensus regarding the extent to which tactile perceptual learning generalizes across fingers. We measured tactile orientation discrimination abilities on 4 fingers (index and middle fingers of both hands), using psychophysical measures, before and after 4 training sessions on 1 finger. Given the somatotopic organization of the hand representation in the somatosensory cortex, the topography of the cortical areas underlying tactile perceptual learning can be inferred from the pattern of generalization across fingers; only fingers sharing cortical representation with the trained finger ought to improve with it. Following training, performance improved not only for the trained finger but also for its adjacent and homologous fingers. Although these fingers were not exposed to training, they nevertheless demonstrated similar levels of learning as the trained finger. Conversely, the performance of the finger that was neither adjacent nor homologous to the trained finger was unaffected by training, despite the fact that our procedure was designed to enhance generalization, as described in recent visual perceptual learning research. This pattern of improved performance is compatible with previous reports of neuronal receptive fields (RFs) in the primary somatosensory cortex (SI) spanning adjacent and homologous digits. We conclude that perceptual learning rooted in low-level cortex can still generalize, and suggest potential applications for the neurorehabilitation of syndromes associated with maladaptive plasticity in SI. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Domain general constraints on statistical learning.
Thiessen, Erik D
2011-01-01
All theories of language development suggest that learning is constrained. However, theories differ on whether these constraints arise from language-specific processes or have domain-general origins such as the characteristics of human perception and information processing. The current experiments explored constraints on statistical learning of patterns, such as the phonotactic patterns of an infants' native language. Infants in these experiments were presented with a visual analog of a phonotactic learning task used by J. R. Saffran and E. D. Thiessen (2003). Saffran and Thiessen found that infants' phonotactic learning was constrained such that some patterns were learned more easily than other patterns. The current results indicate that infants' learning of visual patterns shows the same constraints as infants' learning of phonotactic patterns. This is consistent with theories suggesting that constraints arise from domain-general sources and, as such, should operate over many kinds of stimuli in addition to linguistic stimuli. © 2011 The Author. Child Development © 2011 Society for Research in Child Development, Inc.
General formalism for partial spatial coherence in reflection Mueller matrix polarimetry.
Ossikovski, Razvigor; Hingerl, Kurt
2016-09-01
Starting from the first principles, we derive the expressions governing partially coherent Mueller matrix reflection polarimetry on spatially inhomogeneous samples. These are reported both in their general form and in the practically important specific form for two juxtaposed media.
Cheng, Guang; Zhou, Lan; Huang, Jianhua Z.
2014-01-01
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based
The generalized tanh method to obtain exact solutions of nonlinear partial differential equation
Gómez, César
2007-01-01
In this paper, we present the generalized tanh method to obtain exact solutions of nonlinear partial differential equations, and we obtain solitons and exact solutions of some important equations of the mathematical physics.
Logarithmic learning for generalized classifier neural network.
Ozyildirim, Buse Melis; Avci, Mutlu
2014-12-01
Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.
Discriminative Transfer Learning for General Image Restoration
Xiao, Lei
2018-04-30
Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.
Discriminative Transfer Learning for General Image Restoration
Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael
2018-01-01
Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.
Directory of Open Access Journals (Sweden)
Yusuf Pandir
2013-01-01
Full Text Available We firstly give some new functions called generalized hyperbolic functions. By the using of the generalized hyperbolic functions, new kinds of transformations are defined to discover the exact approximate solutions of nonlinear partial differential equations. Based on the generalized hyperbolic function transformation of the generalized KdV equation and the coupled equal width wave equations (CEWE, we find new exact solutions of two equations and analyze the properties of them by taking different parameter values of the generalized hyperbolic functions. We think that these solutions are very important to explain some physical phenomena.
International Nuclear Information System (INIS)
LaChapelle, J.
2004-01-01
A path integral is presented that solves a general class of linear second order partial differential equations with Dirichlet/Neumann boundary conditions. Elementary kernels are constructed for both Dirichlet and Neumann boundary conditions. The general solution can be specialized to solve elliptic, parabolic, and hyperbolic partial differential equations with boundary conditions. This extends the well-known path integral solution of the Schroedinger/diffusion equation in unbounded space. The construction is based on a framework for functional integration introduced by Cartier/DeWitt-Morette
Lewis, F L; Vamvoudakis, Kyriakos G
2011-02-01
Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.
Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.
Lin, Huiming; Fu, Bo; Qin, Guoyou; Zhu, Zhongyi
2017-12-01
We develop a doubly robust estimation of generalized partial linear models for longitudinal data with dropouts. Our method extends the highly efficient aggregate unbiased estimating function approach proposed in Qu et al. (2010) to a doubly robust one in the sense that under missing at random (MAR), our estimator is consistent when either the linear conditional mean condition is satisfied or a model for the dropout process is correctly specified. We begin with a generalized linear model for the marginal mean, and then move forward to a generalized partial linear model, allowing for nonparametric covariate effect by using the regression spline smoothing approximation. We establish the asymptotic theory for the proposed method and use simulation studies to compare its finite sample performance with that of Qu's method, the complete-case generalized estimating equation (GEE) and the inverse-probability weighted GEE. The proposed method is finally illustrated using data from a longitudinal cohort study. © 2017, The International Biometric Society.
Gomez, Rapson
2012-01-01
Objective: Generalized partial credit model, which is based on item response theory (IRT), was used to test differential item functioning (DIF) for the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed.), inattention (IA), and hyperactivity/impulsivity (HI) symptoms across boys and girls. Method: To accomplish this, parents completed…
Penfield, Randall D.; Bergeron, Jennifer M.
2005-01-01
This article applies a weighted maximum likelihood (WML) latent trait estimator to the generalized partial credit model (GPCM). The relevant equations required to obtain the WML estimator using the Newton-Raphson algorithm are presented, and a simulation study is described that compared the properties of the WML estimator to those of the maximum…
A Comparison of Item Exposure Control Procedures with the Generalized Partial Credit Model
Sanchez, Edgar Isaac
2008-01-01
To enhance test security of high stakes tests, it is vital to understand the way various exposure control strategies function under various IRT models. To that end the present dissertation focused on the performance of several exposure control strategies under the generalized partial credit model with an item pool of 100 and 200 items. These…
Davis, Laurie Laughlin
2004-01-01
Choosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline…
Roberts, James S.; Bao, Han; Huang, Chun-Wei; Gagne, Phill
Characteristic curve approaches for linking parameters from the generalized partial credit model were examined for cases in which common (anchor) items are calibrated separately in two groups. Three of these approaches are simple extensions of the test characteristic curve (TCC), item characteristic curve (ICC), and operating characteristic curve…
Prediction in Partial Duration Series With Generalized Pareto-Distributed Exceedances
DEFF Research Database (Denmark)
Rosbjerg, Dan; Madsen, Henrik; Rasmussen, Peter Funder
1992-01-01
As a generalization of the common assumption of exponential distribution of the exceedances in Partial duration series the generalized Pareto distribution has been adopted. Estimators for the parameters are presented using estimation by both method of moments and probability-weighted moments...... distributions (with physically justified upper limit) the correct exceedance distribution should be applied despite a possible acceptance of the exponential assumption by a test of significance....
The Relationship between Feelings-of-Knowing and Partial Knowledge for General Knowledge Questions.
Norman, Elisabeth; Blakstad, Oskar; Johnsen, Øivind; Martinsen, Stig K; Price, Mark C
2016-01-01
Feelings of knowing (FoK) are introspective self-report ratings of the felt likelihood that one will be able to recognize a currently unrecallable memory target. Previous studies have shown that FoKs are influenced by retrieved fragment knowledge related to the target, which is compatible with the accessibility hypothesis that FoK is partly based on currently activated partial knowledge about the memory target. However, previous results have been inconsistent as to whether or not FoKs are influenced by the accuracy of such information. In our study (N = 26), we used a recall-judge-recognize procedure where stimuli were general knowledge questions. The measure of partial knowledge was wider than those applied previously, and FoK was measured before rather than after partial knowledge. The accuracy of reported partial knowledge was positively related to subsequent recognition accuracy, and FoK only predicted recognition on trials where there was correct partial knowledge. Importantly, FoK was positively related to the amount of correct partial knowledge, but did not show a similar incremental relation with incorrect knowledge.
Computer use changes generalization of movement learning.
Wei, Kunlin; Yan, Xiang; Kong, Gaiqing; Yin, Cong; Zhang, Fan; Wang, Qining; Kording, Konrad Paul
2014-01-06
Over the past few decades, one of the most salient lifestyle changes for us has been the use of computers. For many of us, manual interaction with a computer occupies a large portion of our working time. Through neural plasticity, this extensive movement training should change our representation of movements (e.g., [1-3]), just like search engines affect memory [4]. However, how computer use affects motor learning is largely understudied. Additionally, as virtually all participants in studies of perception and actions are computer users, a legitimate question is whether insights from these studies bear the signature of computer-use experience. We compared non-computer users with age- and education-matched computer users in standard motor learning experiments. We found that people learned equally fast but that non-computer users generalized significantly less across space, a difference negated by two weeks of intensive computer training. Our findings suggest that computer-use experience shaped our basic sensorimotor behaviors, and this influence should be considered whenever computer users are recruited as study participants. Copyright © 2014 Elsevier Ltd. All rights reserved.
General plan for the partial dismantling of the IRT-Sofia research reactor
Directory of Open Access Journals (Sweden)
Apostolov Tihomir G.
2006-01-01
Full Text Available After the decision of the Bulgarian Government to reconstruct it, the strategy concerning the IRT-Sofia Research Reactor is to partially dismantle the old systems and equipment. The removal of the reactor core and replacement of old equipment will not pose any significant problems. For a more efficient use of existing resources, there is a need for an engineering project which has been already prepared under the title "General Plan for the Partial Dismantling of Equipment at the IRT-Sofia as a Part of the Reconstruction into a Low Power RR".
Slower Reacquisition after Partial Extinction in Human Contingency Learning
Morís, Joaquín; Barberia, Itxaso; Vadillo, Miguel A.; Andrades, Ainhoa; López, Francisco J.
2017-01-01
Extinction is a very relevant learning phenomenon from a theoretical and applied point of view. One of its most relevant features is that relapse phenomena often take place once the extinction training has been completed. Accordingly, as extinction-based therapies constitute the most widespread empirically validated treatment of anxiety disorders,…
Yilmaz, Ferkan
2011-11-01
In this paper, in contrast to the relay selection protocols available in the literature, we propose a partial relay selection protocol utilizing only the shadowing side information of the relays instead of their full channel side information in order to select a relay in a dual-hop relaying system through the available limited feedback channels and power budget. We then presented an exact unified performance expression combining the average bit error probability, ergodic capacity, and moments-generating function of the proposed partial relay selection over generalized fading channels. Referring to the unified performance expression introduced in [1], we explicitly offer a generic unified performance expression that can be easily calculated and that is applicable to a wide variety of fading scenarios. Finally, as an illustration of the mathematical formalism, some numerical and simulation results are generated for an extended generalized-K fading environment, and these numerical and simulation results are shown to be in perfect agreement. © 2011 IEEE.
DEFF Research Database (Denmark)
Madsen, Henrik; Rosbjerg, Dan
1997-01-01
parameters is inferred from regional data using generalized least squares (GLS) regression. Two different Bayesian T-year event estimators are introduced: a linear estimator that requires only some moments of the prior distributions to be specified and a parametric estimator that is based on specified......A regional estimation procedure that combines the index-flood concept with an empirical Bayes method for inferring regional information is introduced. The model is based on the partial duration series approach with generalized Pareto (GP) distributed exceedances. The prior information of the model...
Implementing E-Learning Designed Courses in General Education
Nuangchalerm, Prasart; Sakkumduang, Krissada; Uhwha, Suleepornn; Chansirisira, Pacharawit
2014-01-01
The aim of this study is to implement e-learning designed course for general education. The study employed 3 phases for developing e-learning course: contextual study, designing, and implementing. Two courses general education, 217 undergraduate students are participated the study. Research tool consisted of interview about e-learning form and…
Prediction in Partial Duration Series With Generalized Pareto-Distributed Exceedances
DEFF Research Database (Denmark)
Rosbjerg, Dan; Madsen, Henrik; Rasmussen, Peter Funder
1992-01-01
As a generalization of the common assumption of exponential distribution of the exceedances in Partial duration series the generalized Pareto distribution has been adopted. Estimators for the parameters are presented using estimation by both method of moments and probability-weighted moments......-weighted moments. Maintaining the generalized Pareto distribution as the parent exceedance distribution the T-year event is estimated assuming the exceedances to be exponentially distributed. For moderately long-tailed exceedance distributions and small to moderate sample sizes it is found, by comparing mean...... square errors of the T-year event estimators, that the exponential distribution is preferable to the correct generalized Pareto distribution despite the introduced model error and despite a possible rejection of the exponential hypothesis by a test of significance. For moderately short-tailed exceedance...
Robust-BD Estimation and Inference for General Partially Linear Models
Directory of Open Access Journals (Sweden)
Chunming Zhang
2017-11-01
Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.
New multidimensional partially integrable generalization of S-integrable N-wave equation
International Nuclear Information System (INIS)
Zenchuk, A. I.
2007-01-01
This paper develops a modification of the dressing method based on the inhomogeneous linear integral equation with integral operator having nonempty kernel. The method allows one to construct the systems of multidimensional partial differential equations having differential polynomial structure in any dimension n. The associated solution space is not full, although it is parametrized by certain number of arbitrary functions of (n-1) variables. We consider four-dimensional generalization of the classical (2+1)-dimensional S-integrable N-wave equation as an example
Generalized concentration addition: a method for examining mixtures containing partial agonists.
Howard, Gregory J; Webster, Thomas F
2009-08-07
Environmentally relevant toxic exposures often consist of simultaneous exposure to multiple agents. Methods to predict the expected outcome of such combinations are critical both to risk assessment and to an accurate judgment of whether combinations are synergistic or antagonistic. Concentration addition (CA) has commonly been used to assess the presence of synergy or antagonism in combinations of similarly acting chemicals, and to predict effects of combinations of such agents. CA has the advantage of clear graphical interpretation: Curves of constant joint effect (isoboles) must be negatively sloped straight lines if the mixture is concentration additive. However, CA cannot be directly used to assess combinations that include partial agonists, although such agents are of considerable interest. Here, we propose a natural extension of CA to a functional form that may be applied to mixtures including full agonists and partial agonists. This extended definition, for which we suggest the term "generalized concentration addition," encompasses linear isoboles with slopes of any sign. We apply this approach to the simple example of agents with dose-response relationships described by Hill functions with slope parameter n=1. The resulting isoboles are in all cases linear, with negative, zero and positive slopes. Using simple mechanistic models of ligand-receptor systems, we show that the same isobole pattern and joint effects are generated by modeled combinations of full and partial agonists. Special cases include combinations of two full agonists and a full agonist plus a competitive antagonist.
General Video Game AI: Learning from Screen Capture
Kunanusont, Kamolwan; Lucas, Simon M.; Perez-Liebana, Diego
2017-01-01
General Video Game Artificial Intelligence is a general game playing framework for Artificial General Intelligence research in the video-games domain. In this paper, we propose for the first time a screen capture learning agent for General Video Game AI framework. A Deep Q-Network algorithm was applied and improved to develop an agent capable of learning to play different games in the framework. After testing this algorithm using various games of different categories and difficulty levels, th...
An Investigative, Cooperative Learning Approach to the General Microbiology Laboratory
Seifert, Kyle; Fenster, Amy; Dilts, Judith A.; Temple, Louise
2009-01-01
Investigative- and cooperative-based learning strategies have been used effectively in a variety of classrooms to enhance student learning and engagement. In the General Microbiology laboratory for juniors and seniors at James Madison University, these strategies were combined to make a semester-long, investigative, cooperative learning experience…
Development and Assessment of Service Learning Projects in General Biology
Felzien, Lisa; Salem, Laura
2008-01-01
Service learning involves providing service to the community while requiring students to meet learning goals in a specific course. A service learning project was implemented in a general biology course at Rockhurst University to involve students in promoting scientific education in conjunction with community partner educators. Students were…
Iordanov, Iordan V.; Vassilev, Andrey A.
2017-12-01
We construct a model of the trade relations between two regions for the case when the trading entities (consumers) compete for a scarce good and there is an element of strategic interdependence in the trading process. Additionally, local consumers enjoy partial protection in the form of guaranteed access to a part of the locally-supplied quantity of the good. The model is formulated for the general asymmetric case, where the two regions differ in terms of parameters such as income, size of the local market supply, degree of protection and transportation costs. For this general model we establish the existence of Nash equilibria and obtain their form as a function of the model parameters, producing a typology of the equilibria. This is a required step in order to rigorously study various types of price dynamics for the model.
Infants' Learning, Memory, and Generalization of Learning for Bimodal Events.
Morrongiello, Barbara A.; Lasenby, Jennifer; Lee, Naomi
2003-01-01
Two studies examined the impact of temporal synchrony on infants' learning of and memory for sight-sound pairs. Findings indicated that 7-month-olds had no difficulty learning auditory-visual pairs regardless of temporal synchrony, remembering them 10 minutes later and 1 week later. Three-month-olds showed poorer learning in no-synchrony than in…
Gradient descent learning algorithm overview: a general dynamical systems perspective.
Baldi, P
1995-01-01
Gives a unified treatment of gradient descent learning algorithms for neural networks using a general framework of dynamical systems. This general approach organizes and simplifies all the known algorithms and results which have been originally derived for different problems (fixed point/trajectory learning), for different models (discrete/continuous), for different architectures (forward/recurrent), and using different techniques (backpropagation, variational calculus, adjoint methods, etc.). The general approach can also be applied to derive new algorithms. The author then briefly examines some of the complexity issues and limitations intrinsic to gradient descent learning. Throughout the paper, the author focuses on the problem of trajectory learning.
Ullah, Raza
2016-05-01
The main objective of the study was to see whether medical students use more desirable approaches to studying than general education students. Survey method was used to collect data from both the medical students and the general education students. The survey of the medical students was carried out between January and March, 2012. The survey was administered to all the medical students present in lecture halls on day of data collection, while general education students were randomly selected from four subject areas at two universities. In total, 976 medical students and 912 general students participated in the study. Of the general students, 494(54%) were boys and 418(46%)were girls with an overall mean age of 20.53±1.77 years (range: 17-27 years). The medical students' perceptions of their learning environment and their learning preferences were broadly similar to that of general education students with the exception of workload. The medical students perceived the workload to be less appropriate (Mean = 2.06±0.72) than the students in general education (Mean = 2.84±0.90). The medical students were more likely to use the deep approach to studying (Mean = 3.66±0.59) than the students in general education (Mean = 3.16±0.91). The students in general education were slightly more likely to use the organized studying (Mean = 3.44±0.90) than the medical students (Mean =3.23±0.90). Both medical students and the students in general education tended to use the surface approaches along with other approaches to studying. There was not a great difference between the medical students and the students pursuing general education with regard to perceptions of the learning environment and approaches to learning.
Learning general phonological rules from distributional information: a computational model.
Calamaro, Shira; Jarosz, Gaja
2015-04-01
Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles. Copyright © 2014 Cognitive Science Society, Inc.
DEFF Research Database (Denmark)
Dlugosz, Stephan; Mammen, Enno; Wilke, Ralf
2017-01-01
Large data sets that originate from administrative or operational activity are increasingly used for statistical analysis as they often contain very precise information and a large number of observations. But there is evidence that some variables can be subject to severe misclassification...... or contain missing values. Given the size of the data, a flexible semiparametric misclassification model would be good choice but their use in practise is scarce. To close this gap a semiparametric model for the probability of observing labour market transitions is estimated using a sample of 20 m...... observations from Germany. It is shown that estimated marginal effects of a number of covariates are sizeably affected by misclassification and missing values in the analysis data. The proposed generalized partially linear regression extends existing models by allowing a misclassified discrete covariate...
Liu, Siwei; Gates, Kathleen M; Blandon, Alysia Y
2018-06-01
Despite recent research indicating that interpersonal linkage in physiology is a common phenomenon during social interactions, and the well-established role of respiratory sinus arrhythmia (RSA) in socially facilitative physiological regulation, little research has directly examined interpersonal influences in RSA, perhaps due to methodological challenges in analyzing multivariate RSA data. In this article, we aim to bridge this methodological gap by introducing a new method for quantifying interpersonal RSA influences. Specifically, we show that a frequency-domain statistic, generalized partial directed coherence (gPDC), can be used to capture lagged relations in RSA between social partners without first estimating RSA for each person. We illustrate its utility by examining the relation between gPDC and marital conflict in a sample of married couples. Finally, we discuss how gPDC complements existing methods in the time domain and provide guidelines for choosing among these different statistical techniques. © 2018 Society for Psychophysiological Research.
An Improved Generalized Predictive Control in a Robust Dynamic Partial Least Square Framework
Directory of Open Access Journals (Sweden)
Jin Xin
2015-01-01
Full Text Available To tackle the sensitivity to outliers in system identification, a new robust dynamic partial least squares (PLS model based on an outliers detection method is proposed in this paper. An improved radial basis function network (RBFN is adopted to construct the predictive model from inputs and outputs dataset, and a hidden Markov model (HMM is applied to detect the outliers. After outliers are removed away, a more robust dynamic PLS model is obtained. In addition, an improved generalized predictive control (GPC with the tuning weights under dynamic PLS framework is proposed to deal with the interaction which is caused by the model mismatch. The results of two simulations demonstrate the effectiveness of proposed method.
Engels, Paul T; de Gara, Chris
2010-06-30
Surgical education is evolving under the dual pressures of an enlarging body of knowledge required during residency and mounting work-hour restrictions. Changes in surgical residency training need to be based on available educational models and research to ensure successful training of surgeons. Experiential learning theory, developed by David Kolb, demonstrates the importance of individual learning styles in improving learning. This study helps elucidate the way in which medical students, surgical residents, and surgical faculty learn. The Kolb Learning Style Inventory, which divides individual learning styles into Accommodating, Diverging, Converging, and Assimilating categories, was administered to the second year undergraduate medical students, general surgery resident body, and general surgery faculty at the University of Alberta. A total of 241 faculty, residents, and students were surveyed with an overall response rate of 73%. The predominant learning style of the medical students was assimilating and this was statistically significant (p learning style found in the residents and faculty. The predominant learning styles of the residents and faculty were convergent and accommodative, with no statistically significant differences between the residents and the faculty. We conclude that medical students have a significantly different learning style from general surgical trainees and general surgeons. This has important implications in the education of general surgery residents.
Dan, Youquan; Xu, Yonggen
2018-04-01
The evolution law of arbitrary order moments of the Wigner distribution function, which can be applied to the different spatial power spectra, is obtained for partially coherent general beams propagating in atmospheric turbulence using the extended Huygens-Fresnel principle. A coupling coefficient of radiant intensity distribution (RID) in turbulence is introduced. Analytical expressions of the evolution of the first five-order moments, kurtosis parameter, coupling coefficient of RID for general beams in turbulence are derived, and the formulas are applied to Airy beams. Results show that there exist two types for general beams in turbulence. A larger value of kurtosis parameter for Airy beams also reveals that coupling effect due to turbulence is stronger. Both theoretical analysis and numerical results show that the maximum value of kurtosis parameter for an Airy beam in turbulence is independent of turbulence strength parameter and is only determined by inner scale of turbulence. Relative angular spread, kurtosis and coupling coefficient are less influenced by turbulence for Airy beams with a smaller decay factor and a smaller initial width of the first lobe.
Cheng, Guang
2014-02-01
We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and the generalized estimating equations (GEE). Although the model in consideration is natural and useful in many practical applications, the literature on this model is very limited because of challenges in dealing with dependent data for nonparametric additive models. We show that the proposed estimators are consistent and asymptotically normal even if the covariance structure is misspecified. An explicit consistent estimate of the asymptotic variance is also provided. Moreover, we derive the semiparametric efficiency score and information bound under general moment conditions. By showing that our estimators achieve the semiparametric information bound, we effectively establish their efficiency in a stronger sense than what is typically considered for GEE. The derivation of our asymptotic results relies heavily on the empirical processes tools that we develop for the longitudinal/clustered data. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2014 ISI/BS.
PAC-Learning from General Examples
DEFF Research Database (Denmark)
Fischer, Paul; Hoeffgen, K.- U.; Lefmann, H.
1997-01-01
dimension of a target class with respect to a sample class, which replaces the Vapnik-Chervonenkis dimension (V.N. Vapnik and A.Y. Chervonenkis, 1971). The investigation of structural aspects of the relative dimension is followed by its applications to learning environments. It turns out that computing...
Shared learning in general practice--facilitators and barriers.
van de Mortel, Thea; Silberberg, Peter; Ahern, Christine
2013-03-01
Capacity for teaching in general practice clinics is limited. Shared learning sessions are one form of vertically integrated teaching that may ameliorate capacity constraints. This study sought to understand the perceptions of general practitioner supervisors, learners and practice staff of the facilitators of shared learning in general practice clinics. Using a grounded theory approach, semistructured interviews were conducted and analysed to generate a theory about the topic. Thirty-five stakeholders from nine general practices participated. Facilitators of shared learning included enabling factors such as small group facilitation skills, space, administrative support and technological resources; reinforcing factors such as targeted funding, and predisposing factors such as participant attributes. Views from multiple stakeholders suggest that the implementation of shared learning in general practice clinics would be supported by an ecological approach that addresses all these factors.
Generalized projective synchronization of chaotic systems via adaptive learning control
International Nuclear Information System (INIS)
Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang
2010-01-01
In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)
Deep learning in medical imaging: General overview
Energy Technology Data Exchange (ETDEWEB)
Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug [University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)
2017-08-01
The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.
Deep learning in medical imaging: General overview
International Nuclear Information System (INIS)
Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug
2017-01-01
The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging
Deep Learning in Medical Imaging: General Overview
Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae
2017-01-01
The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging. PMID:28670152
Deep Learning in Medical Imaging: General Overview.
Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae; Seo, Joon Beom; Kim, Namkug
2017-01-01
The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.
General partial wave analysis of the decay of a hyperon of spin 1/2
International Nuclear Information System (INIS)
Lee, T.D.; Yang, C.N.
1983-01-01
This note is to consider the general problem of the decay of a hyperon of spin 1/2 into a pion and a nucleon under the general assumption of possible violations of parity conservation, charge-conjugation invariance, and time-reversal invariance. The discussion is in essence a partial wave analysis of the decay phenomena and is independent of the dynamics of the decay. Nonrelativistic approximations are not made on either of the decay products. In the reference system in which the hyperon is at rest there are two possible final states of the pion-nucleon system:s/sub 1/2/ and p/sub 1/2/. Denoting the amplitudes of these two states by A and B, one observes that the decay is physically characterized by three real constants specifying the magnitudes and the relative phase between these amplitudes. One of these constants can be taken to be absolute value a 2 + absolute value B 2 , and is evidently proportional to the decay probability per unit time. The other two constants are best defined in terms of experimentally measurable quantities. They discuss three types of experiments: (a) The angular distribution of the decay pion from a completely polarized hyperon at rest. (b) The longitudinal polarization of the nucleon emitted in the decay of unpolarized hyperons at rest. (c) Transverse polarization of the nucleon emitted in a given direction in the decay of a polarized hyperon
Owall, B; Jönsson, L
1998-01-01
The aim of this study was to analyze the techniques, production problems, and 2-year results of attachment-retained removable partial denture (RPD) treatment provided by general practitioners in Sweden. At a major dental laboratory, consecutive cases involving new production of crowns, or of fixed partial dentures (FPDs) and RPDs retained with precision attachments, were studied. Parameters of the dentition, crown or FPD, type and brand of attachment, etc, as well as early satisfaction by dentist and patient, were recorded using specially designed forms at the dental laboratory and questionnaires for the dentists. After 2 years, questionnaires were again sent out to the dentists to record complications and patients' and dentists' opinions of the results. The sample gathered totaled 83 constructions. After 2 years, responses for 57 patients, all of whom had distal-extension RPDs, were received. Most drop-outs in the study were explicable. The most frequently cited reasons for using attachments were esthetics and need for crowning the teeth abutting the RPD. McCollum rigid slide attachment was the predominant brand used (43% of constructions). Dentists and patients were dissatisfied with 6% of the constructions. During the first 2 years, 22 of 57 constructions were complication-free. Seventeen had attachment complications and 9 had serious complications related to the abutment teeth or RPDs. A comparison between these 2 groups revealed that those with complications had every second abutment root-canal treated and a root post, while the group without complications had every fifth abutment root-canal treated. There were many technical and biotechnical complications and failures; the exact ratio, however, depended on the definition of "complications" and "failure." The 2-year results also deviated considerably from the dentists' opinions of the early results.
Learning and generalization errors for the 2D binary perceptron
Klymovskiy, A.
2005-01-01
The statistical mechanics model of the binary perceptron learning is considered. It is proved that under the regularity conditions learning and generalization errors for the binary perceptron with two inputs tend to 0 at the average; the first term of the asymptotics is provided; its behavior with
Generalized SMO algorithm for SVM-based multitask learning.
Cai, Feng; Cherkassky, Vladimir
2012-06-01
Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be naturally separated into several groups, and incorporating this group information into learning may improve generalization. Recently, Vapnik proposed a general approach to formalizing such problems, known as "learning with structured data" and its support vector machine (SVM) based optimization formulation called SVM+. Liang and Cherkassky showed the connection between SVM+ and multitask learning (MTL) approaches in machine learning, and proposed an SVM-based formulation for MTL called SVM+MTL for classification. Training the SVM+MTL classifier requires the solution of a large quadratic programming optimization problem which scales as O(n(3)) with sample size n. So there is a need to develop computationally efficient algorithms for implementing SVM+MTL. This brief generalizes Platt's sequential minimal optimization (SMO) algorithm to the SVM+MTL setting. Empirical results show that, for typical SVM+MTL problems, the proposed generalized SMO achieves over 100 times speed-up, in comparison with general-purpose optimization routines.
Directory of Open Access Journals (Sweden)
de Gara Chris
2010-06-01
Full Text Available Abstract Background Surgical education is evolving under the dual pressures of an enlarging body of knowledge required during residency and mounting work-hour restrictions. Changes in surgical residency training need to be based on available educational models and research to ensure successful training of surgeons. Experiential learning theory, developed by David Kolb, demonstrates the importance of individual learning styles in improving learning. This study helps elucidate the way in which medical students, surgical residents, and surgical faculty learn. Methods The Kolb Learning Style Inventory, which divides individual learning styles into Accommodating, Diverging, Converging, and Assimilating categories, was administered to the second year undergraduate medical students, general surgery resident body, and general surgery faculty at the University of Alberta. Results A total of 241 faculty, residents, and students were surveyed with an overall response rate of 73%. The predominant learning style of the medical students was assimilating and this was statistically significant (p Conclusions We conclude that medical students have a significantly different learning style from general surgical trainees and general surgeons. This has important implications in the education of general surgery residents.
WenJun Zhang; Xin Li
2015-01-01
Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...
Echeto, Luisa F; Sposetti, Venita; Childs, Gail; Aguilar, Maria L; Behar-Horenstein, Linda S; Rueda, Luis; Nimmo, Arthur
2015-09-01
The aim of this study was to evaluate the effectiveness of team-based learning (TBL) methodology on dental students' retention of knowledge regarding removable partial denture (RPD) treatment. The process of learning RPD treatment requires that students first acquire foundational knowledge and then use critical thinking skills to apply that knowledge to a variety of clinical situations. The traditional approach to teaching, characterized by a reliance on lectures, is not the most effective method for learning clinical applications. To address the limitations of that approach, the teaching methodology of the RPD preclinical course at the University of Florida was changed to TBL, which has been shown to motivate student learning and improve clinical performance. A written examination was constructed to compare the impact of TBL with that of traditional teaching regarding students' retention of knowledge and their ability to evaluate, diagnose, and treatment plan a partially edentulous patient with an RPD prosthesis. Students taught using traditional and TBL methods took the same examination. The response rate (those who completed the examination) for the class of 2013 (traditional method) was 94% (79 students of 84); for the class of 2014 (TBL method), it was 95% (78 students of 82). The results showed that students who learned RPD with TBL scored higher on the examination than those who learned RPD with traditional methods. Compared to the students taught with the traditional method, the TBL students' proportion of passing grades was statistically significantly higher (p=0.002), and 23.7% more TBL students passed the examination. The mean score for the TBL class (0.758) compared to the conventional class (0.700) was statistically significant with a large effect size, also demonstrating the practical significance of the findings. The results of the study suggest that TBL methodology is a promising approach to teaching RPD with successful outcomes.
General informatics teaching with B-Learning teaching model
Directory of Open Access Journals (Sweden)
Nguyen The Dung
2018-03-01
Full Text Available Blended learning (B-learning, a combination of face-to-face teaching and E-learning-supported-teaching in an online course, and Information and Communication Technology (ICT tools have been studied in recent years. In addition, the use of this teaching model is effective in teaching and learning conditions in which some certain subjects are appropriate for the specific teaching context. As it has been a matter of concern of the universities in Vietnam today, deep studies related to this topic is crucial to be conducted. In this article, the process of developing online courses and organizing teaching for the General Informatics subject for first-year students at the Hue University of Education with B-learning teaching model will be presented. The combination of 60% face-to-face and 40% online learning.
Experimentally Induced Learned Helplessness: How Far Does it Generalize?
Tuffin, Keith; And Others
1985-01-01
Assessed whether experimentally induced learned helplessness on a cognitive training task generalized to a situationally dissimilar social interaction test task. No significant differences were observed between groups on the subsequent test task, showing that helplessness failed to generalize. (Author/ABB)
Stacked generalization: an introduction to super learning.
Naimi, Ashley I; Balzer, Laura B
2018-04-10
Stacked generalization is an ensemble method that allows researchers to combine several different prediction algorithms into one. Since its introduction in the early 1990s, the method has evolved several times into a host of methods among which is the "Super Learner". Super Learner uses V-fold cross-validation to build the optimal weighted combination of predictions from a library of candidate algorithms. Optimality is defined by a user-specified objective function, such as minimizing mean squared error or maximizing the area under the receiver operating characteristic curve. Although relatively simple in nature, use of Super Learner by epidemiologists has been hampered by limitations in understanding conceptual and technical details. We work step-by-step through two examples to illustrate concepts and address common concerns.
Stochastic abstract policies: generalizing knowledge to improve reinforcement learning.
Koga, Marcelo L; Freire, Valdinei; Costa, Anna H R
2015-01-01
Reinforcement learning (RL) enables an agent to learn behavior by acquiring experience through trial-and-error interactions with a dynamic environment. However, knowledge is usually built from scratch and learning to behave may take a long time. Here, we improve the learning performance by leveraging prior knowledge; that is, the learner shows proper behavior from the beginning of a target task, using the knowledge from a set of known, previously solved, source tasks. In this paper, we argue that building stochastic abstract policies that generalize over past experiences is an effective way to provide such improvement and this generalization outperforms the current practice of using a library of policies. We achieve that contributing with a new algorithm, AbsProb-PI-multiple and a framework for transferring knowledge represented as a stochastic abstract policy in new RL tasks. Stochastic abstract policies offer an effective way to encode knowledge because the abstraction they provide not only generalizes solutions but also facilitates extracting the similarities among tasks. We perform experiments in a robotic navigation environment and analyze the agent's behavior throughout the learning process and also assess the transfer ratio for different amounts of source tasks. We compare our method with the transfer of a library of policies, and experiments show that the use of a generalized policy produces better results by more effectively guiding the agent when learning a target task.
An appraisal of the learning curve in robotic general surgery.
Pernar, Luise I M; Robertson, Faith C; Tavakkoli, Ali; Sheu, Eric G; Brooks, David C; Smink, Douglas S
2017-11-01
Robotic-assisted surgery is used with increasing frequency in general surgery for a variety of applications. In spite of this increase in usage, the learning curve is not yet defined. This study reviews the literature on the learning curve in robotic general surgery to inform adopters of the technology. PubMed and EMBASE searches yielded 3690 abstracts published between July 1986 and March 2016. The abstracts were evaluated based on the following inclusion criteria: written in English, reporting original work, focus on general surgery operations, and with explicit statistical methods. Twenty-six full-length articles were included in final analysis. The articles described the learning curves in colorectal (9 articles, 35%), foregut/bariatric (8, 31%), biliary (5, 19%), and solid organ (4, 15%) surgery. Eighteen of 26 (69%) articles report single-surgeon experiences. Time was used as a measure of the learning curve in all studies (100%); outcomes were examined in 10 (38%). In 12 studies (46%), the authors identified three phases of the learning curve. Numbers of cases needed to achieve plateau performance were wide-ranging but overlapping for different kinds of operations: 19-128 cases for colorectal, 8-95 for foregut/bariatric, 20-48 for biliary, and 10-80 for solid organ surgery. Although robotic surgery is increasingly utilized in general surgery, the literature provides few guidelines on the learning curve for adoption. In this heterogeneous sample of reviewed articles, the number of cases needed to achieve plateau performance varies by case type and the learning curve may have multiple phases as surgeons add more complex cases to their case mix with growing experience. Time is the most common determinant for the learning curve. The literature lacks a uniform assessment of outcomes and complications, which would arguably reflect expertise in a more meaningful way than time to perform the operation alone.
Non-linear partial differential equations an algebraic view of generalized solutions
Rosinger, Elemer E
1990-01-01
A massive transition of interest from solving linear partial differential equations to solving nonlinear ones has taken place during the last two or three decades. The availability of better computers has often made numerical experimentations progress faster than the theoretical understanding of nonlinear partial differential equations. The three most important nonlinear phenomena observed so far both experimentally and numerically, and studied theoretically in connection with such equations have been the solitons, shock waves and turbulence or chaotical processes. In many ways, these phenomen
Learning Theory Estimates with Observations from General Stationary Stochastic Processes.
Hang, Hanyuan; Feng, Yunlong; Steinwart, Ingo; Suykens, Johan A K
2016-12-01
This letter investigates the supervised learning problem with observations drawn from certain general stationary stochastic processes. Here by general, we mean that many stationary stochastic processes can be included. We show that when the stochastic processes satisfy a generalized Bernstein-type inequality, a unified treatment on analyzing the learning schemes with various mixing processes can be conducted and a sharp oracle inequality for generic regularized empirical risk minimization schemes can be established. The obtained oracle inequality is then applied to derive convergence rates for several learning schemes such as empirical risk minimization (ERM), least squares support vector machines (LS-SVMs) using given generic kernels, and SVMs using gaussian kernels for both least squares and quantile regression. It turns out that for independent and identically distributed (i.i.d.) processes, our learning rates for ERM recover the optimal rates. For non-i.i.d. processes, including geometrically [Formula: see text]-mixing Markov processes, geometrically [Formula: see text]-mixing processes with restricted decay, [Formula: see text]-mixing processes, and (time-reversed) geometrically [Formula: see text]-mixing processes, our learning rates for SVMs with gaussian kernels match, up to some arbitrarily small extra term in the exponent, the optimal rates. For the remaining cases, our rates are at least close to the optimal rates. As a by-product, the assumed generalized Bernstein-type inequality also provides an interpretation of the so-called effective number of observations for various mixing processes.
DEFF Research Database (Denmark)
Madsen, H.; Mikkelsen, Peter Steen; Rosbjerg, Dan
2002-01-01
A general framework for regional analysis and modeling of extreme rainfall characteristics is presented. The model is based on the partial duration series (PDS) method that includes in the analysis all events above a threshold level. In the PDS model the average annual number of exceedances...
Pastor, Dena A.; Dodd, Barbara G.; Chang, Hua-Hua
2002-01-01
Studied the impact of using five different exposure control algorithms in two sizes of item pool calibrated using the generalized partial credit model. Simulation results show that the a-stratified design, in comparison to a no-exposure control condition, could be used to reduce item exposure and overlap and increase pool use, while degrading…
Matlock Cole, Ki Lynn; Turner, Ronna C.; Gitchel, W. Dent
2018-01-01
The generalized partial credit model (GPCM) is often used for polytomous data; however, the nominal response model (NRM) allows for the investigation of how adjacent categories may discriminate differently when items are positively or negatively worded. Ten items from three different self-reported scales were used (anxiety, depression, and…
Soto, Fabian A.; Gershman, Samuel J.; Niv, Yael
2014-01-01
How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed longstanding problems for rational theories of associative and causal learning. PMID:25090430
Algorithm-Dependent Generalization Bounds for Multi-Task Learning.
Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J
2017-02-01
Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.
Learning with Generalization Capability by Kernel Methods of Bounded Complexity
Czech Academy of Sciences Publication Activity Database
Kůrková, Věra; Sanguineti, M.
2005-01-01
Roč. 21, č. 3 (2005), s. 350-367 ISSN 0885-064X R&D Projects: GA AV ČR 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : supervised learning * generalization * model complexity * kernel methods * minimization of regularized empirical errors * upper bounds on rates of approximate optimization Subject RIV: BA - General Mathematics Impact factor: 1.186, year: 2005
Kastelic, Helena
2012-01-01
This thesis deals with personality characteristics and their connection with learning efficiency of deaf and partially deaf pupils and students in mainstream primary and secondary school. The theoretical part defines learning efficiency and focuses on the most significant factors of learning efficiency, including also personality characteristics of an individual. This thesis represents the idea of inclusion and its advantages and disadvantages and suggests to what extent it is present in our ...
Learning in neural networks based on a generalized fluctuation theorem
Hayakawa, Takashi; Aoyagi, Toshio
2015-11-01
Information maximization has been investigated as a possible mechanism of learning governing the self-organization that occurs within the neural systems of animals. Within the general context of models of neural systems bidirectionally interacting with environments, however, the role of information maximization remains to be elucidated. For bidirectionally interacting physical systems, universal laws describing the fluctuation they exhibit and the information they possess have recently been discovered. These laws are termed fluctuation theorems. In the present study, we formulate a theory of learning in neural networks bidirectionally interacting with environments based on the principle of information maximization. Our formulation begins with the introduction of a generalized fluctuation theorem, employing an interpretation appropriate for the present application, which differs from the original thermodynamic interpretation. We analytically and numerically demonstrate that the learning mechanism presented in our theory allows neural networks to efficiently explore their environments and optimally encode information about them.
Problem-Based Learning in a General Psychology Course.
Willis, Sandra A.
2002-01-01
Describes the adoption of problem-based learning (PBL) techniques in a general psychology course. States that the instructor used a combination of techniques, including think-pair-share, lecture/discussion, and PBL. Notes means and standard deviations for graded components of PBL format versus lecture/discussion format. (Contains 18 references.)…
Distributed Systems of Generalizing as the Basis of Workplace Learning
Virkkunen, Jaakko; Pihlaja, Juha
2004-01-01
This article proposes a new way of conceptualizing workplace learning as distributed systems of appropriation, development and the use of practice-relevant generalizations fixed within mediational artifacts. This article maintains that these systems change historically as technology and increasingly sophisticated forms of production develop.…
Learning and generalization from reward and punishment in opioid addiction.
Myers, Catherine E; Rego, Janice; Haber, Paul; Morley, Kirsten; Beck, Kevin D; Hogarth, Lee; Moustafa, Ahmed A
2017-01-15
This study adapts a widely-used acquired equivalence paradigm to investigate how opioid-addicted individuals learn from positive and negative feedback, and how they generalize this learning. The opioid-addicted group consisted of 33 participants with a history of heroin dependency currently in a methadone maintenance program; the control group consisted of 32 healthy participants without a history of drug addiction. All participants performed a novel variant of the acquired equivalence task, where they learned to map some stimuli to correct outcomes in order to obtain reward, and to map other stimuli to correct outcomes in order to avoid punishment; some stimuli were implicitly "equivalent" in the sense of being paired with the same outcome. On the initial training phase, both groups performed similarly on learning to obtain reward, but as memory load grew, the control group outperformed the addicted group on learning to avoid punishment. On a subsequent testing phase, the addicted and control groups performed similarly on retention trials involving previously-trained stimulus-outcome pairs, as well as on generalization trials to assess acquired equivalence. Since prior work with acquired equivalence tasks has associated stimulus-outcome learning with the nigrostriatal dopamine system, and generalization with the hippocampal region, the current results are consistent with basal ganglia dysfunction in the opioid-addicted patients. Further, a selective deficit in learning from punishment could contribute to processes by which addicted individuals continue to pursue drug use even at the cost of negative consequences such as loss of income and the opportunity to engage in other life activities. Published by Elsevier B.V.
Fokkinga, W.A.; Uchelen, J. van; Witter, D.J.; Mulder, J.; Creugers, N.H.J.
2016-01-01
This pilot study analyzed impression procedures for conventional metal frame removable partial dentures (RPDs). Heads of RPD departments of three dental laboratories were asked to record features of all incoming impressions for RPDs during a 2-month period. Records included: (1) impression
Robotic partial nephrectomy - Evaluation of the impact of case mix on the procedural learning curve.
Roman, A; Ahmed, K; Challacombe, B
2016-05-01
Although Robotic partial nephrectomy (RPN) is an emerging technique for the management of small renal masses, this approach is technically demanding. To date, there is limited data on the nature and progression of the learning curve in RPN. To analyse the impact of case mix on the RPN LC and to model the learning curve. The records of the first 100 RPN performed, were analysed at our institution that were carried out by a single surgeon (B.C) (June 2010-December 2013). Cases were split based on their Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score into the following groups: 6-7, 8-9 and >10. Using a split group (20 patients in each group) and incremental analysis, the mean, the curve of best fit and R(2) values were calculated for each group. Of 100 patients (F:28, M:72), the mean age was 56.4 ± 11.9 years. The number of patients in each PADUA score groups: 6-7, 8-9 and >10 were 61, 32 and 7 respectively. An increase in incidence of more complex cases throughout the cohort was evident within the 8-9 group (2010: 1 case, 2013: 16 cases). The learning process did not significantly affect the proxies used to assess surgical proficiency in this study (operative time and warm ischaemia time). Case difficulty is an important parameter that should be considered when evaluating procedural learning curves. There is not one well fitting model that can be used to model the learning curve. With increasing experience, clinicians tend to operate on more difficult cases. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.
Incremental and developmental perspectives for general-purpose learning systems
Directory of Open Access Journals (Sweden)
Fernando Martínez-Plumed
2017-02-01
Full Text Available The stupefying success of Articial Intelligence (AI for specic problems, from recommender systems to self-driving cars, has not yet been matched with a similar progress in general AI systems, coping with a variety of (dierent problems. This dissertation deals with the long-standing problem of creating more general AI systems, through the analysis of their development and the evaluation of their cognitive abilities. It presents a declarative general-purpose learning system and a developmental and lifelong approach for knowledge acquisition, consolidation and forgetting. It also analyses the use of the use of more ability-oriented evaluation techniques for AI evaluation and provides further insight for the understanding of the concepts of development and incremental learning in AI systems.
Directory of Open Access Journals (Sweden)
Pinki Majumder
2016-01-01
Full Text Available In this present study, a production inventory model with partial trade credit is formulated and solved in fuzzy environment via Generalized Hukuhara derivative approach. To capture the market, a supplier offers a trade credit period to its retailers. Due to this facility, retailer also offers a partial trade credit period to his/her customer to boost the demand of the item. In practical life situation, demands are generally dependent upon time. Constant demand of an item varies time to time. In this vague situation, demands are taken as time dependent, where its constant part is taken as Left Right - type fuzzy number. In this paper, Generalized Hukuhara derivative approach is used to solve the fuzzy inventory model. Four different cases are considered by using Generalized Hukuhara-(i differentiability and Generalized Hukuhara-(ii differentiability. The objective of this paper is to find out the optimal time so as the total inventory cost is minimum. Finally the model is solved by generalized reduced gradient method. The proposed model and technique are illustrated by numerical examples. Some sensitivity analyses both in tabular and graphical forms are presented and the effects of minimum cost with respect to various inventory parameters are discussed.
Biodynamic feedback training to assure learning partial load bearing on forearm crutches.
Krause, Daniel; Wünnemann, Martin; Erlmann, Andre; Hölzchen, Timo; Mull, Melanie; Olivier, Norbert; Jöllenbeck, Thomas
2007-07-01
To examine how biodynamic feedback training affects the learning of prescribed partial load bearing (200N). Three pre-post experiments. Biomechanics laboratory in a German university. A volunteer sample of 98 uninjured subjects who had not used crutches recently. There were 24 subjects in experiment 1 (mean age, 23.2y); 64 in experiment 2 (mean age, 43.6y); and 10 in experiment 3 (mean age, 40.3y), parallelized by arm force. Video instruction and feedback training: In experiment 1, 2 varied instruction videos and reduced feedback frequency; in experiment 2, varied frequencies of changing tasks (contextual interference); and in experiment 3, feedback training (walking) and transfer (stair tasks). Vertical ground reaction force. Absolute error of practiced tasks was significantly reduced for all samples (Pstairs might be beneficial.
Generalized multiple kernel learning with data-dependent priors.
Mao, Qi; Tsang, Ivor W; Gao, Shenghua; Wang, Li
2015-06-01
Multiple kernel learning (MKL) and classifier ensemble are two mainstream methods for solving learning problems in which some sets of features/views are more informative than others, or the features/views within a given set are inconsistent. In this paper, we first present a novel probabilistic interpretation of MKL such that maximum entropy discrimination with a noninformative prior over multiple views is equivalent to the formulation of MKL. Instead of using the noninformative prior, we introduce a novel data-dependent prior based on an ensemble of kernel predictors, which enhances the prediction performance of MKL by leveraging the merits of the classifier ensemble. With the proposed probabilistic framework of MKL, we propose a hierarchical Bayesian model to learn the proposed data-dependent prior and classification model simultaneously. The resultant problem is convex and other information (e.g., instances with either missing views or missing labels) can be seamlessly incorporated into the data-dependent priors. Furthermore, a variety of existing MKL models can be recovered under the proposed MKL framework and can be readily extended to incorporate these priors. Extensive experiments demonstrate the benefits of our proposed framework in supervised and semisupervised settings, as well as in tasks with partial correspondence among multiple views.
An investigative, cooperative learning approach to the general microbiology laboratory.
Seifert, Kyle; Fenster, Amy; Dilts, Judith A; Temple, Louise
2009-01-01
Investigative- and cooperative-based learning strategies have been used effectively in a variety of classrooms to enhance student learning and engagement. In the General Microbiology laboratory for juniors and seniors at James Madison University, these strategies were combined to make a semester-long, investigative, cooperative learning experience involving culture and identification of microbial isolates that the students obtained from various environments. To assess whether this strategy was successful, students were asked to complete a survey at the beginning and at the end of the semester regarding their comfort level with a variety of topics. For most of the topics queried, the students reported that their comfort had increased significantly during the semester. Furthermore, this group of students thought that the quality of this investigative lab experience was much better than that of any of their previous lab experiences.
What Should General Practice Trainees Learn about Atopic Eczema?
Directory of Open Access Journals (Sweden)
Deepani Munidasa
2015-02-01
Full Text Available Effective atopic eczema (AE control not only improves quality of life but may also prevent the atopic march. The Royal College of General Practitioners’ (RCGP curriculum does not currently provide specific learning outcomes on AE management. We aimed to gain consensus on learning outcomes to inform curriculum development. A modified Delphi method was used with questionnaires distributed to gather the views of a range of health care professionals (HCPs including general practitioners (GPs, dermatologists, dermatology nurses and parents of children with AE attending a dedicated paediatric dermatology clinic. Ninety-one questionnaires were distributed to 61 HCPs and 30 parents; 81 were returned. All agreed that learning should focus on the common clinical features, complications and management of AE and the need to appreciate its psychosocial impact. Areas of divergence included knowledge of alternative therapies. Parents felt GPs should better understand how to identify, manage and refer severe AD and recognized the value of the specialist eczema nurse. Dermatologists and parents highlighted inconsistencies in advice regarding topical steroids. This study identifies important areas for inclusion as learning outcomes on AE management in the RCGP curriculum and highlights the importance of patients and parents as a valuable resource in the development of medical education.
Extreme learning machine for ranking: generalization analysis and applications.
Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin
2014-05-01
The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.
On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.
Xie, Yuchen; Ho, Jeffrey; Vemuri, Baba
2013-01-01
Existing dictionary learning algorithms are based on the assumption that the data are vectors in an Euclidean vector space ℝ d , and the dictionary is learned from the training data using the vector space structure of ℝ d and its Euclidean L 2 -metric. However, in many applications, features and data often originated from a Riemannian manifold that does not support a global linear (vector space) structure. Furthermore, the extrinsic viewpoint of existing dictionary learning algorithms becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to the application. This paper proposes a novel framework for sparse coding and dictionary learning for data on a Riemannian manifold, and it shows that the existing sparse coding and dictionary learning methods can be considered as special (Euclidean) cases of the more general framework proposed here. We show that both the dictionary and sparse coding can be effectively computed for several important classes of Riemannian manifolds, and we validate the proposed method using two well-known classification problems in computer vision and medical imaging analysis.
Statistical mechanics of learning orthogonal signals for general covariance models
International Nuclear Information System (INIS)
Hoyle, David C
2010-01-01
Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation
Fokkinga, Wietske A; van Uchelen, Judith; Witter, Dick J; Mulder, Jan; Creugers, Nico H J
2016-01-01
This pilot study analyzed impression procedures for conventional metal frame removable partial dentures (RPDs). Heads of RPD departments of three dental laboratories were asked to record features of all incoming impressions for RPDs during a 2-month period. Records included: (1) impression procedure, tray type (stock/custom), impression material (elastomer/alginate), use of border-molding material (yes/no); and (2) RPD type requested (distal-extension/tooth-bounded/combination). Of the 132 total RPD impressions, 111 (84%) involved custom trays, of which 73 (55%) were combined with an elastomer. Impression border-molding material was used in 4% of the cases. Associations between impression procedure and RPD type or dentists' year/university of graduation were not found.
A Partial Test of Agnew's General Theory of Crime and Delinquency
Zhang, Yan; Day, George; Cao, Liqun
2012-01-01
In 2005, Agnew introduced a new integrated theory, which he labels a general theory of crime and delinquency. He proposes that delinquency is more likely to occur when constraints against delinquency are low and motivations for delinquency are high. In addition, he argues that constraints and motivations are influenced by variables in five life…
Machine Learning Classification of Buildings for Map Generalization
Directory of Open Access Journals (Sweden)
Jaeeun Lee
2017-10-01
Full Text Available A critical problem in mapping data is the frequent updating of large data sets. To solve this problem, the updating of small-scale data based on large-scale data is very effective. Various map generalization techniques, such as simplification, displacement, typification, elimination, and aggregation, must therefore be applied. In this study, we focused on the elimination and aggregation of the building layer, for which each building in a large scale was classified as “0-eliminated,” “1-retained,” or “2-aggregated.” Machine-learning classification algorithms were then used for classifying the buildings. The data of 1:1000 scale and 1:25,000 scale digital maps obtained from the National Geographic Information Institute were used. We applied to these data various machine-learning classification algorithms, including naive Bayes (NB, decision tree (DT, k-nearest neighbor (k-NN, and support vector machine (SVM. The overall accuracies of each algorithm were satisfactory: DT, 88.96%; k-NN, 88.27%; SVM, 87.57%; and NB, 79.50%. Although elimination is a direct part of the proposed process, generalization operations, such as simplification and aggregation of polygons, must still be performed for buildings classified as retained and aggregated. Thus, these algorithms can be used for building classification and can serve as preparatory steps for building generalization.
Learning regularization parameters for general-form Tikhonov
International Nuclear Information System (INIS)
Chung, Julianne; Español, Malena I
2017-01-01
Computing regularization parameters for general-form Tikhonov regularization can be an expensive and difficult task, especially if multiple parameters or many solutions need to be computed in real time. In this work, we assume training data is available and describe an efficient learning approach for computing regularization parameters that can be used for a large set of problems. We consider an empirical Bayes risk minimization framework for finding regularization parameters that minimize average errors for the training data. We first extend methods from Chung et al (2011 SIAM J. Sci. Comput. 33 3132–52) to the general-form Tikhonov problem. Then we develop a learning approach for multi-parameter Tikhonov problems, for the case where all involved matrices are simultaneously diagonalizable. For problems where this is not the case, we describe an approach to compute near-optimal regularization parameters by using operator approximations for the original problem. Finally, we propose a new class of regularizing filters, where solutions correspond to multi-parameter Tikhonov solutions, that requires less data than previously proposed optimal error filters, avoids the generalized SVD, and allows flexibility and novelty in the choice of regularization matrices. Numerical results for 1D and 2D examples using different norms on the errors show the effectiveness of our methods. (paper)
International Nuclear Information System (INIS)
Fischer, E.
1977-01-01
Various families of exact solutions to the Einstein and Einstein--Maxwell field equations of general relativity are treated for situations of sufficient symmetry that only two independent variables arise. The mathematical problem then reduces to consideration of sets of two coupled nonlinear differential equations. The physical situations in which such equations arise include: the external gravitational field of an axisymmetric, uncharged steadily rotating body, cylindrical gravitational waves with two degrees of freedom, colliding plane gravitational waves, the external gravitational and electromagnetic fields of a static, charged axisymmetric body, and colliding plane electromagnetic and gravitational waves. Through the introduction of suitable potentials and coordinate transformations, a formalism is presented which treats all these problems simultaneously. These transformations and potentials may be used to generate new solutions to the Einstein--Maxwell equations from solutions to the vacuum Einstein equations, and vice-versa. The calculus of differential forms is used as a tool for generation of similarity solutions and generalized similarity solutions. It is further used to find the invariance group of the equations; this in turn leads to various finite transformations that give new, physically distinct solutions from old. Some of the above results are then generalized to the case of three independent variables
Interstate Research Associates, Inc., Washington, DC.
This fact sheet providing general information about learning disabilities is presented in both English and Spanish versions. It begins with the federal definition of learning disabilities and a discussion of its implications followed by estimates of incidence. Typical characteristics of students with learning disabilities are then summarized as…
Directory of Open Access Journals (Sweden)
Shaw-Yang Yang Hund-Der Yeh
2012-01-01
Full Text Available This note develops a general mathematical model for describing the transient hydraulic head response for constant-head test, constant-flux test, and slug test in a radial confined aquifer system with a partially penetrating well. The Laplace-domain solution for the model is derived by applying the Laplace transform with respect to time and finite Fourier cosine transform with respect to the z-direction. This new solution has been shown to reduce to the constant-head test when discounting the wellbore storage and maintaining a constant well water level. This solution can also be reduced to the constant-flux test solution when discounting the wellbore storage and keeping a constant pumping rate in the well. Moreover, the solution becomes the slug test solution when there is no pumping in the well. This general solution can be used to develop a single computer code to estimate aquifer parameters if coupled with an optimization algorithm or to assess the effect of well partial penetration on hydraulic head distribution for three types of aquifer tests.
Directory of Open Access Journals (Sweden)
A. Kushlyk
2018-01-01
Full Text Available The problem of selection and application of dental prostheses in periodontal disease is especially relevant in case of severe generalized periodontitis, which is accompanied by mobile tooth removal resulting in overloading the periodontium of the remaining teeth as well as the increase in tooth mobility. Therefore, in generalized periodontitis, it is important to apply the method of direct dental prosthetic rehabilitation since, in case of partial tooth loss, it will prevent the development of generalized periodontitis complications. The objective of the research was to improve the effectiveness of combination therapy for patients with generalized periodontitis and partial tooth loss applying the developed method of direct fixed dental prosthetic rehabilitation based on the study of the periodontal status. Materials and methods. The study included 129 patients with general periodontitis, II-III degree and partial tooth loss over the age of 45 years. According to prosthodontic treatment, all the patients were divided into three groups: Group I consisted of 42 (20 women and 22 men patients who immediately after tooth extraction were rehabilitated with the application of direct plastic laminar immediate prosthesis and selective tooth grinding; permanent dental prosthetic rehabilitation was performed 6 weeks after tooth extraction; Group II included 43 (21 women and 22 men patients who underwent traditional permanent dental prosthetic rehabilitation using fixed dental bridges 6 weeks after mobile tooth removal and wound healing; Group III comprised 44 (21 women and 23 men patients who immediately after mobile tooth removal were rehabilitated with the application of direct fixed sectional dental bridge (Ukrainian patent UA 20995. 2007 Feb 15 and selective tooth grinding; permanent dental prosthetic rehabilitation was performed 6 months after tooth extraction. The control group consisted of 26 people with intact dentitions over the age of 45 years
Chanut Poondej; Thanita Lerdpornkulrat
2016-01-01
Researchers have reported empirical evidence that the deep approaches to learning account for significant successful learning. The present study aimed to investigate the relationship between students' motivational goal orientation, their perceptions of the general education classroom learning environment, and deep approaches to learning strategies. Participants (N = 494) were first- and second-year college students enrolled in any of the general education courses in higher education in Thaila...
Szu, Harold H.
1999-03-01
The early vision principle of redundancy reduction of 108 sensor excitations is understandable from computer vision viewpoint toward sparse edge maps. It is only recently derived using a truly unsupervised learning paradigm of artificial neural networks (ANN). In fact, the biological vision, Hubel- Wiesel edge maps, is reproduced seeking the underlying independent components analyses (ICA) among 102 image samples by maximizing the ANN output entropy (partial)H(V)/(partial)[W] equals (partial)[W]/(partial)t. When a pair of newborn eyes or ears meet the bustling and hustling world without supervision, they seek ICA by comparing 2 sensory measurements (x1(t), x2(t))T equalsV X(t). Assuming a linear and instantaneous mixture model of the external world X(t) equals [A] S(t), where both the mixing matrix ([A] equalsV [a1, a2] of ICA vectors and the source percentages (s1(t), s2(t))T equalsV S(t) are unknown, we seek the independent sources approximately equals [I] where the approximated sign indicates that higher order statistics (HOS) may not be trivial. Without a teacher, the ANN weight matrix [W] equalsV [w1, w2] adjusts the outputs V(t) equals tanh([W]X(t)) approximately equals [W]X(t) until no desired outputs except the (Gaussian) 'garbage' (neither YES '1' nor NO '-1' but at linear may-be range 'origin 0') defined by Gaussian covariance G equals [I] equals [W][A] the internal knowledge representation [W], as the inverse of the external world matrix [A]-1. To unify IC, PCA, ANN & HOS theories since 1991 (advanced by Jutten & Herault, Comon, Oja, Bell-Sejnowski, Amari-Cichocki, Cardoso), the LYAPONOV function L(v1,...,vn, w1,...wn,) equals E(v1,...,vn) - H(w1,...wn) is constructed as the HELMHOTZ free energy to prove both convergences of supervised energy E and unsupervised entropy H learning. Consequently, rather using the faithful but dumb computer: 'GARBAGE-IN, GARBAGE-OUT,' the smarter neurocomputer will be equipped with an unsupervised learning that extracts
Meir Drexler, Shira; Hamacher-Dang, Tanja C; Wolf, Oliver T
2017-05-01
In extinction learning, the individual learns that a previously acquired association (e.g. between a threat and its predictor) is no longer valid. This learning is the principle underlying many cognitive-behavioral psychotherapeutic treatments, e.g. 'exposure therapy'. However, extinction is often highly-context dependent, leading to renewal (relapse of extinguished conditioned response following context change). We have previously shown that post-extinction stress leads to a more context-dependent extinction memory in a predictive learning task. Yet as stress prior to learning can impair the integration of contextual cues, here we aim to create a more generalized extinction memory by inducing stress prior to extinction. Forty-nine men and women learned the associations between stimuli and outcomes in a predictive learning task (day 1), extinguished them shortly after an exposure to a stress/control condition (day 2), and were tested for renewal (day 3). No group differences were seen in acquisition and extinction learning, and a renewal effect was present in both groups. However, the groups differed in the strength and context-dependency of the extinction memory. Compared to the control group, the stress group showed an overall reduced recovery of responding to the extinguished stimuli, in particular in the acquisition context. These results, together with our previous findings, demonstrate that the effects of stress exposure on extinction memory depend on its timing. While post-extinction stress makes the memory more context-bound, pre-extinction stress strengthens its consolidation for the acquisition context as well, making it potentially more resistant to relapse. These results have implications for the use of glucocorticoids as extinction-enhancers in exposure therapy. Copyright © 2017 Elsevier Inc. All rights reserved.
Carreira, Junko Matsuzaki
2011-01-01
This study investigated children's motivation for learning English as a foreign language (EFL) and intrinsic motivation for learning in general. The participants were 268 third-sixth graders in a public school in Japan. Data were collected using two questionnaires, one measuring motivation for learning EFL and the other investigating intrinsic…
Cohen-Schotanus, Janke; Muijtjens, Arno M. M.; Schonrock-Adema, Johanna; Geertsma, Jelle; van der Vleuten, Cees P. M.
OBJECTIVE: To test hypotheses regarding the longitudinal effects of problem-based learning (PBL) and conventional learning relating to students' appreciation of the curriculum, self-assessment of general competencies, summative assessment of clinical competence and indicators of career development.
Censor, N
2013-10-10
In both perceptual and motor learning, numerous studies have shown specificity of learning to the trained eye or hand and to the physical features of the task. However, generalization of learning is possible in both perceptual and motor domains. Here, I review evidence for perceptual and motor learning generalization, suggesting that generalization patterns are affected by the way in which the original memory is encoded and consolidated. Generalization may be facilitated during fast learning, with possible engagement of higher-order brain areas recurrently interacting with the primary visual or motor cortices encoding the stimuli or movements' memories. Such generalization may be supported by sleep, involving functional interactions between low and higher-order brain areas. Repeated exposure to the task may alter generalization patterns of learning and overall offline learning. Development of unifying frameworks across learning modalities and better understanding of the conditions under which learning can generalize may enable to gain insight regarding the neural mechanisms underlying procedural learning and have useful clinical implications. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.
Sleep restores loss of generalized but not rote learning of synthetic speech.
Fenn, Kimberly M; Margoliash, Daniel; Nusbaum, Howard C
2013-09-01
Sleep-dependent consolidation has been demonstrated for declarative and procedural memory but few theories of consolidation distinguish between rote and generalized learning, suggesting similar consolidation should occur for both. However, studies using rote and generalized learning have suggested different patterns of consolidation may occur, although different tasks have been used across studies. Here we directly compared consolidation of rote and generalized learning using a single speech identification task. Training on a large set of novel stimuli resulted in substantial generalized learning, and sleep restored performance that had degraded after 12 waking hours. Training on a small set of repeated stimuli primarily resulted in rote learning and performance also degraded after 12 waking hours but was not restored by sleep. Moreover performance was significantly worse 24-h after rote training. Our results suggest a functional dissociation between the mechanisms of consolidation for rote and generalized learning which has broad implications for memory models. Copyright © 2013 Elsevier B.V. All rights reserved.
Systems control with generalized probabilistic fuzzy-reinforcement learning
Hinojosa, J.; Nefti, S.; Kaymak, U.
2011-01-01
Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input-output data are not available. In most combinations of fuzzy systems and RL, the environment is considered to be
Johnson, Robin R.; And Others
1995-01-01
Supportive learning activities were implemented in a multiple-baseline time series design across four fifth-grade classrooms to evaluate the effects of a cooperative teaching alternative (supportive learning) on teaching behavior, the behavior and grades of general and special education students, and the opinions of general education teachers.…
de Gara Chris; Engels Paul T
2010-01-01
Abstract Background Surgical education is evolving under the dual pressures of an enlarging body of knowledge required during residency and mounting work-hour restrictions. Changes in surgical residency training need to be based on available educational models and research to ensure successful training of surgeons. Experiential learning theory, developed by David Kolb, demonstrates the importance of individual learning styles in improving learning. This study helps elucidate the way in which ...
Cognitive Learning Strategy as a Partial Effect on Major Field Test in Business Results
Strang, Kenneth David
2014-01-01
An experiment was developed to determine if cognitive learning strategies improved standardized university business exam results. Previous studies revealed that factors such as prior ability, age, gender, and culture predicted a student's Major Field Test in Business (MFTB) score better than course content. The experiment control consisted of…
Learning to Read Empirical Articles in General Psychology
Sego, Sandra A.; Stuart, Anne E.
2016-01-01
Many students, particularly underprepared students, struggle to identify the essential information in empirical articles. We describe a set of assignments for instructing general psychology students to dissect the structure of such articles. Students in General Psychology I read empirical articles and answered a set of general, factual questions…
A Fast Optimization Method for General Binary Code Learning.
Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng
2016-09-22
Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.
Domain-specific and domain-general constraints on word and sequence learning.
Archibald, Lisa M D; Joanisse, Marc F
2013-02-01
The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.
Ruffing, Stephanie; Wach, F-Sophie; Spinath, Frank M; Brünken, Roland; Karbach, Julia
2015-01-01
Recent research has revealed that learning behavior is associated with academic achievement at the college level, but the impact of specific learning strategies on academic success as well as gender differences therein are still not clear. Therefore, the aim of this study was to investigate gender differences in the incremental contribution of learning strategies over general cognitive ability in the prediction of academic achievement. The relationship between these variables was examined by correlation analyses. A set of t-tests was used to test for gender differences in learning strategies, whereas structural equation modeling as well as multi-group analyses were applied to investigate the incremental contribution of learning strategies for male and female students' academic performance. The sample consisted of 461 students (mean age = 21.2 years, SD = 3.2). Correlation analyses revealed that general cognitive ability as well as the learning strategies effort, attention, and learning environment were positively correlated with academic achievement. Gender differences were found in the reported application of many learning strategies. Importantly, the prediction of achievement in structural equation modeling revealed that only effort explained incremental variance (10%) over general cognitive ability. Results of multi-group analyses showed no gender differences in this prediction model. This finding provides further knowledge regarding gender differences in learning research and the specific role of learning strategies for academic achievement. The incremental assessment of learning strategy use as well as gender-differences in their predictive value contributes to the understanding and improvement of successful academic development.
van der Zwet, J; Zwietering, P J; Teunissen, P W; van der Vleuten, C P M; Scherpbier, A J J A
2011-08-01
Workplace learning in undergraduate medical education has predominantly been studied from a cognitive perspective, despite its complex contextual characteristics, which influence medical students' learning experiences in such a way that explanation in terms of knowledge, skills, attitudes and single determinants of instructiveness is unlikely to suffice. There is also a paucity of research which, from a perspective other than the cognitive or descriptive one, investigates student learning in general practice settings, which are often characterised as powerful learning environments. In this study we took a socio-cultural perspective to clarify how students learn during a general practice clerkship and to construct a conceptual framework that captures this type of learning. Our analysis of group interviews with 44 fifth-year undergraduate medical students about their learning experiences in general practice showed that students needed developmental space to be able to learn and develop their professional identity. This space results from the intertwinement of workplace context, personal and professional interactions and emotions such as feeling respected and self-confident. These forces framed students' participation in patient consultations, conversations with supervisors about consultations and students' observation of supervisors, thereby determining the opportunities afforded to students to mind their learning. These findings resonate with other conceptual frameworks and learning theories. In order to refine our interpretation, we recommend that further research from a socio-cultural perspective should also explore other aspects of workplace learning in medical education.
Generalization of Supervised Learning for Binary Mask Estimation
DEFF Research Database (Denmark)
May, Tobias; Gerkmann, Timo
2014-01-01
This paper addresses the problem of speech segregation by es- timating the ideal binary mask (IBM) from noisy speech. Two methods will be compared, one supervised learning approach that incorporates a priori knowledge about the feature distri- bution observed during training. The second method...
General Education: Learning from the Past, Preparing for the Future
Gersten, Karen S.
2012-01-01
This article explores the widening gap between business and societal needs and current general education curricula. Research is presented that documents gaps between projected needs of industry and current practices in postsecondary education, especially in the general education areas. Positive efforts to close the gap are highlighted. Changing…
Dorren, H.J.S.
1998-01-01
It is shown that the Korteweg–de Vries (KdV) equation can be transformed into an ordinary linear partial differential equation in the wave number domain. Explicit solutions of the KdV equation can be obtained by subsequently solving this linear differential equation and by applying a cascade of
DEFF Research Database (Denmark)
Arreskov, Anne Beiter; Graungaard, Anette Hauskov; Nielsen, Kirsten Lykke
the paper using the method of critical appraisal. Session content The didactic method used in the workshop is mostly small group activities with eight participants and two tutors in each group. The participants will receive two scientific papers: the BMJ-version of the Cochrane review about general health......Abstract title: Benefits and harms of general health checks - lifelong learning in general practice: how to read and use scientific literature Objectives After this workshop the participants will know the basics of how to read a systematic literature review and interpret a meta-analysis and be able......, assesses, and implements methods of diagnosis and treatment on the basis of the best available current research, clinical expertise, and combines this with the needs and preferences of the patient, is termed evidence-based medicine. By learning and practising the principles of evidence-based medicine, GPs...
Energy Technology Data Exchange (ETDEWEB)
Lee, Youngrok [Iowa State Univ., Ames, IA (United States)
2013-05-15
Heterogeneity exists on a data set when samples from di erent classes are merged into the data set. Finite mixture models can be used to represent a survival time distribution on heterogeneous patient group by the proportions of each class and by the survival time distribution within each class as well. The heterogeneous data set cannot be explicitly decomposed to homogeneous subgroups unless all the samples are precisely labeled by their origin classes; such impossibility of decomposition is a barrier to overcome for estimating nite mixture models. The expectation-maximization (EM) algorithm has been used to obtain maximum likelihood estimates of nite mixture models by soft-decomposition of heterogeneous samples without labels for a subset or the entire set of data. In medical surveillance databases we can find partially labeled data, that is, while not completely unlabeled there is only imprecise information about class values. In this study we propose new EM algorithms that take advantages of using such partial labels, and thus incorporate more information than traditional EM algorithms. We particularly propose four variants of the EM algorithm named EM-OCML, EM-PCML, EM-HCML and EM-CPCML, each of which assumes a specific mechanism of missing class values. We conducted a simulation study on exponential survival trees with five classes and showed that the advantages of incorporating substantial amount of partially labeled data can be highly signi cant. We also showed model selection based on AIC values fairly works to select the best proposed algorithm on each specific data set. A case study on a real-world data set of gastric cancer provided by Surveillance, Epidemiology and End Results (SEER) program showed a superiority of EM-CPCML to not only the other proposed EM algorithms but also conventional supervised, unsupervised and semi-supervised learning algorithms.
Active Learning in a Large General Physics Classroom.
Trousil, Rebecca
2008-04-01
In 2004, we launched a new calculus-based, introductory physics sequence at Washington University. Designed as an alternative to our traditional lecture-based sequence, the primary objectives for this new course were to actively engage students in the learning process, to significantly strengthen students' conceptual reasoning skills, to help students develop higher level quantitative problem solving skills necessary for analyzing ``real world'' problems, and to integrate modern physics into the curriculum. This talk will describe our approach, using The Six Ideas That Shaped Physics text by Thomas Moore, to creating an active learning environment in large classes as well as share our perspective on key elements for success and challenges that we face in the large class environment.
Progressive paradoxical sleep deprivation impairs partial memory following learning tasks in rats
Institute of Scientific and Technical Information of China (English)
Chunmin Zhu; Xiangrong Yao; Weisheng Zhang; Yanfeng Song; Yiping Hou
2008-01-01
BACKGROUND: Complex learning tasks result in a greater number of paradoxical sleep phases, which can improve memory. The effect of paradoxical sleep deprivation, induced by "flower pot" technique, on spatial reference memory and working memory require further research. OBJECTIVE: To observe the effect of progressive paradoxical sleep deprivation in rats, subsequent to learning, on memory using the Morris Water Maze. DESIGN, TIME AND SETTING: Controlled observation experiment. The experiment was performed at the Laboratory of Neurobiology, Department of Anatomy, Histology and Embryology, School of Basic Medical Sciences, Lanzhou University from December 2006 to October 2007. MATERIALS: Twenty-eight, male, Wistar rats, 3-4 months old, were provided by the Experimental Animal Center of Lanzhou University. The Morris Water Maze and behavioral analyses system was purchased from Genheart Company, Beijing, China. METHODS: All animals, according to a random digits table, were randomly divided into paradoxical sleep deprivation, tank control, and home cage control groups. Paradoxical sleep deprivation was induced by the "flower pot" technique for 72 hours, housing the rats on small platforms over water. Rats in the "tank control" and "home cage control" groups were housed either in a tank with large platforms over the water or in normal cages without paradoxical sleep deprivation. MAIN OUTCOME MEASURES: Morris Water Maze was employed for task learning and spatial memory testing. Rats in all groups were placed at six random starting points each day for four consecutive days. Each placement was repeated for two trials; the first trial represented reference memory and the second working memory. Rats in the first trial were allowed to locate the submerged platform within 120 seconds. Data, including swimming distance, escape latency, swimming velocity, percentage of time in correct quarter, and memory scores were recorded and analyzed automatically by behavioral analyses
Dick, Marie-Louise B; King, David B; Mitchell, Geoffrey K; Kelly, Glynn D; Buckley, John F; Garside, Susan J
2007-07-16
There is increasing demand to provide clinical and teaching experiences in the general practice setting. Vertical integration in teaching and learning, whereby teaching and learning roles are shared across all learner stages, has the potential to decrease time demands and stress on general practitioners, to provide teaching skills and experience to GP registrars, and to improve the learning experience for medical students, and may also help meet the increased demand for teaching in general practice. We consider potential advantages and barriers to vertical integration of teaching in general practice, and provide results of focus group discussions with general practice principals and registrars about vertical integration. We recommend further research into the feasibility of using vertical integration to enhance the capacity to teach medical students in general practice.
Bao, Yukun; Xiong, Tao; Hu, Zhongyi; Kibelloh, Mboni
2014-01-01
Reasons for contradictory findings regarding the gender moderate effect on computer self-efficacy in the adoption of e-learning/mobile learning are limited. Recognizing the multilevel nature of the computer self-efficacy (CSE), this study attempts to explore gender differences in the adoption of mobile learning, by extending the Technology Acceptance Model (TAM) with general and specific CSE. Data collected from 137 university students were tested against the research model using the structur...
In-Course Instructor-Guided Service Learning in a Community College General Psychology Class
Goomas, David T.; Weston, Melissa B.
2012-01-01
Students enrolled in two general psychology classes at El Centro College (ECC) of the Dallas County Community College District (DCCCD) were offered the opportunity to earn extra credit by performing up to 20 hours of service learning. Benefits of service learning were observed in student development, including exploration of career possibilities,…
A Learning Trajectory in 6-Year-Olds' Thinking about Generalizing Functional Relationships
Blanton, Maria; Brizuela, Bárbara M.; Gardiner, Angela Murphy; Sawrey, Katie; Newman-Owens, Ashley
2015-01-01
The study of functions is a critical route into teaching and learning algebra in the elementary grades, yet important questions remain regarding the nature of young children's understanding of functions. This article reports an empirically developed learning trajectory in first-grade children's (6-year-olds') thinking about generalizing functional…
A Vowel Is a Vowel: Generalizing Newly Learned Phonotactic Constraints to New Contexts
Chambers, Kyle E.; Onishi, Kristine H.; Fisher, Cynthia
2010-01-01
Adults can learn novel phonotactic constraints from brief listening experience. We investigated the representations underlying phonotactic learning by testing generalization to syllables containing new vowels. Adults heard consonant-vowel-consonant study syllables in which particular consonants were artificially restricted to the onset or coda…
Team-Based Learning Reduces Attrition in a First-Semester General Chemistry Course
Comeford, Lorrie
2016-01-01
Team-based learning (TBL) is an instructional method that has been shown to reduce attrition and increase student learning in a number of disciplines. TBL was implemented in a first-semester general chemistry course, and its effect on attrition was assessed. Attrition from sections before implementing TBL (fall 2008 to fall 2009) was compared with…
Habib, H. S.
A professor involved with the HELDS project (Higher Education for Learning Disabled Students) describes modifications in a general chemistry course. A syllabus lists program objectives for eight text chapters, evaluation components, and course rules. Two units are described in detail, with information presented on modifications made for LD…
Design and validation of general biology learning program based on scientific inquiry skills
Cahyani, R.; Mardiana, D.; Noviantoro, N.
2018-03-01
Scientific inquiry is highly recommended to teach science. The reality in the schools and colleges is that many educators still have not implemented inquiry learning because of their lack of understanding. The study aims to1) analyze students’ difficulties in learning General Biology, 2) design General Biology learning program based on multimedia-assisted scientific inquiry learning, and 3) validate the proposed design. The method used was Research and Development. The subjects of the study were 27 pre-service students of general elementary school/Islamic elementary schools. The workflow of program design includes identifying learning difficulties of General Biology, designing course programs, and designing instruments and assessment rubrics. The program design is made for four lecture sessions. Validation of all learning tools were performed by expert judge. The results showed that: 1) there are some problems identified in General Biology lectures; 2) the designed products include learning programs, multimedia characteristics, worksheet characteristics, and, scientific attitudes; and 3) expert validation shows that all program designs are valid and can be used with minor revisions. The first section in your paper.
How do general practice residents use social networking sites in asynchronous distance learning?
Maisonneuve, Hubert; Chambe, Juliette; Lorenzo, Mathieu; Pelaccia, Thierry
2015-09-21
Blended learning environments - involving both face-to-face and remote interactions - make it easier to adapt learning programs to constraints such as residents' location and low teacher-student ratio. Social networking sites (SNS) such as Facebook®, while not originally intended to be used as learning environments, may be adapted for the distance-learning part of training programs. The purpose of our study was to explore the use of SNS for asynchronous distance learning in a blended learning environment as well as its influence on learners' face-to-face interactions. We conducted a qualitative study and carried out semi-structured interviews. We performed purposeful sampling for maximal variation to include eight general practice residents in 2(nd) and 3(rd) year training. A thematic analysis was performed. The social integration of SNS facilitates the engagement of users in their learning tasks. This may also stimulate students' interactions and group cohesion when members meet up in person. Most of the general practice residents who work in the blended learning environment we studied had a positive appraisal on their use of SNS. In particular, we report a positive impact on their engagement in learning and their participation in discussions during face-to-face instruction. Further studies are needed in order to evaluate the effectiveness of SNS in blended learning environments and the appropriation of SNS by teachers.
Sleep Enhances a Spatially Mediated Generalization of Learned Values
Javadi, Amir-Homayoun; Tolat, Anisha; Spiers, Hugo J.
2015-01-01
Sleep is thought to play an important role in memory consolidation. Here we tested whether sleep alters the subjective value associated with objects located in spatial clusters that were navigated to in a large-scale virtual town. We found that sleep enhances a generalization of the value of high-value objects to the value of locally clustered…
CPD - The learning preferences of general practitioners | Van den ...
African Journals Online (AJOL)
Introduction: General Practitioners need to stay up to date and to maintain professional competence. The Health Professions Council of SA has introduced a mandatory recertification system starting in 1999. Insufficient research exists locally to reliably identify the continuing professional development (CPD) habits of GP's in ...
Learning in General Games with Nature’s Moves
Directory of Open Access Journals (Sweden)
Patrick L. Leoni
2014-01-01
Full Text Available This paper investigates simultaneous learning about both nature and others’ actions in repeated games and identifies a set of sufficient conditions for which Harsanyi’s doctrine holds. Players have a utility function over infinite histories that are continuous for the sup-norm topology. Nature’s drawing after any history may depend on any past actions. Provided that (1 every player maximizes her expected payoff against her own beliefs, (2 every player updates her beliefs in a Bayesian manner, (3 prior beliefs about both nature and other players’ strategies have a grain of truth, and (4 beliefs about nature are independent of actions chosen during the game, we construct a Nash equilibrium, that is, realization-equivalent to the actual plays, where Harsanyi’s doctrine holds. Those assumptions are shown to be tight.
Generalized query-based active learning to identify differentially methylated regions in DNA.
Haque, Md Muksitul; Holder, Lawrence B; Skinner, Michael K; Cook, Diane J
2013-01-01
Active learning is a supervised learning technique that reduces the number of examples required for building a successful classifier, because it can choose the data it learns from. This technique holds promise for many biological domains in which classified examples are expensive and time-consuming to obtain. Most traditional active learning methods ask very specific queries to the Oracle (e.g., a human expert) to label an unlabeled example. The example may consist of numerous features, many of which are irrelevant. Removing such features will create a shorter query with only relevant features, and it will be easier for the Oracle to answer. We propose a generalized query-based active learning (GQAL) approach that constructs generalized queries based on multiple instances. By constructing appropriately generalized queries, we can achieve higher accuracy compared to traditional active learning methods. We apply our active learning method to find differentially DNA methylated regions (DMRs). DMRs are DNA locations in the genome that are known to be involved in tissue differentiation, epigenetic regulation, and disease. We also apply our method on 13 other data sets and show that our method is better than another popular active learning technique.
Vlach, Haley A; Sandhofer, Catherine M
2012-01-01
The spacing effect describes the robust finding that long-term learning is promoted when learning events are spaced out in time rather than presented in immediate succession. Studies of the spacing effect have focused on memory processes rather than for other types of learning, such as the acquisition and generalization of new concepts. In this study, early elementary school children (5- to 7-year-olds; N = 36) were presented with science lessons on 1 of 3 schedules: massed, clumped, and spaced. The results revealed that spacing lessons out in time resulted in higher generalization performance for both simple and complex concepts. Spaced learning schedules promote several types of learning, strengthening the implications of the spacing effect for educational practices and curriculum. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.
Directory of Open Access Journals (Sweden)
М.М. Karimova
2017-05-01
Full Text Available A girl with partial gigantism (the increased I and II fingers of the left foot is being examined. This condition is a rare and unresolved problem, as the definite reason of its development is not determined. Wait-and-see strategy is recommended, as well as correcting operations after closing of growth zones, and forming of data pool for generalization and development of schemes of drug and radial therapeutic methods.
Attributional style and the generality of learned helplessness.
Alloy, L B; Peterson, C; Abramson, L Y; Seligman, M E
1984-03-01
According to the logic of the attribution reformulation of learned helplessness, the interaction of two factors influences whether helplessness experienced in one situation will transfer to a new situation. The model predicts that people who exhibit a style of attributing negative outcomes to global factors will show helplessness deficits in new situations that are either similar or dissimilar to the original situation in which they were helpless. In contrast, people who exhibit a style of attributing negative outcomes to only specific factors will show helplessness deficits in situations that are similar, but not dissimilar, to the original situation in which they were helpless. To test these predictions, we conducted two studies in which undergraduates with either a global or specific attributional style for negative outcomes were given one of three pretreatments in the typical helplessness triadic design: controllable bursts of noise, uncontrollable bursts of noise, or no noise. In Experiment 1, students were tested for helplessness deficits in a test situation similar to the pretreatment setting, whereas in Experiment 2, they were tested in a test situation dissimilar to the pretreatment setting. The findings were consistent with predictions of the reformulated helplessness theory.
General practitioners learning qualitative research: A case study of postgraduate education.
Hepworth, Julie; Kay, Margaret
2015-10-01
Qualitative research is increasingly being recognised as a vital aspect of primary healthcare research. Teaching and learning how to conduct qualitative research is especially important for general practitioners and other clinicians in the professional educational setting. This article examines a case study of postgraduate professional education in qualitative research for clinicians, for the purpose of enabling a robust discussion around teaching and learning in medicine and the health sciences. A series of three workshops was delivered for primary healthcare academics. The workshops were evaluated using a quantitative survey and qualitative free-text responses to enable descriptive analyses. Participants found qualitative philosophy and theory the most difficult areas to engage with, and learning qualitative coding and analysis was considered the easiest to learn. Key elements for successful teaching were identified, including the use of adult learning principles, the value of an experienced facilitator and an awareness of the impact of clinical subcultures on learning.
Flache, A.
2002-01-01
Concerns about models of cultural adaptation as analogs of genetic selection have led cognitive game theorists to explore learning-theoretic specifications. Two prominent examples, the Bush-Mosteller stochastic learning model and the Roth-Erev payoff-matching model, are aligned and integrated as
Pajak, Bozena; Creel, Sarah C.; Levy, Roger
2016-01-01
How are languages learned, and to what extent are learning mechanisms similar in infant native-language (L1) and adult second-language (L2) acquisition? In terms of vocabulary acquisition, we know from the infant literature that the ability to discriminate similar-sounding words at a particular age does not guarantee successful word-meaning…
[E-Learning--an important contribution to general medical training and continuing education?].
Ruf, D; Berner, M M; Kriston, L; Härter, M
2008-09-01
There is increasing activity in the development of e-learning modules for general medical training and continuing education. One of the central advantages of e-learning is flexibility regarding time and place of its use. The quality of the available e-learning opportunities varies quite considerably. For users it is often not easy to assess the quality of e-learning modules or to find offers of high quality. This could be a reason for the fact that despite the huge number of e-learning modules still only few students and physicians are using them. This is although e-learning has proven to be as effective as and even more efficient than learning in the classroom or with paper-based materials. This article summarizes the different models of e-learning, how and where to find offers of high quality, advantages of using e-learning, and the effectiveness and efficiency of such offers. In addition problems of e-learning and possibilities to overcome these problems are shown.
Contingency learning deficits and generalization in chronic unilateral hand pain patients.
Meulders, Ann; Harvie, Daniel S; Bowering, Jane K; Caragianis, Suzanne; Vlaeyen, Johan W S; Moseley, G Lorimer
2014-10-01
Contingency learning, in particular the formation of danger beliefs, underpins conditioned fear and avoidance behavior, yet equally important is the formation of safety beliefs. That is, when threat beliefs and accompanying fear/avoidance spread to technically safe cues, it might cause disability. Indeed, such over generalization has been advanced as a trans-diagnostic pathologic marker, but it has not been investigated in chronic pain. Using a novel hand pain scenario contingency learning task, we tested the hypotheses that chronic hand pain patients demonstrate less differential pain expectancy judgments because of poor safety learning and demonstrate broader generalization gradients than healthy controls. Participants viewed digitized 3-dimensional hands in different postures presented in random order (conditioned stimulus [CS]) and rated the likelihood that a fictive patient would feel pain when moving the hand into that posture. Subsequently, the outcome (pain/no pain) was presented on the screen. One hand posture was followed by pain (CS+), another was not (CS-). Generalization was tested using novel hand postures (generalization stimuli) that varied in how similar they were to the original conditioned stimuli. Patients, but not healthy controls, demonstrated a contingency learning deficit determined by impaired safety learning, but not by exaggerated pain expectancy toward the CS+. Patients showed flatter, asymmetric generalization gradients than the healthy controls did, with higher pain expectancy for novel postures that were more similar to the original CS-. The results clearly uphold our hypotheses and suggest that contingency learning deficits might be important in the development and maintenance of the chronic pain-related disability. Chronic hand pain patients demonstrate 1) reduced differential contingency learning determined by a lack of safety belief formation, but not by exaggerated threat belief formation, and 2) flatter, asymmetric
Kim, Roger H; Kurtzman, Scott H; Collier, Ashley N; Shabahang, Mohsen M
Learning styles theory posits that learners have distinct preferences for how they assimilate new information. The VARK model categorizes learners based on combinations of 4 learning preferences: visual (V), aural (A), read/write (R), and kinesthetic (K). A previous single institution study demonstrated that the VARK preferences of applicants who interview for general surgery residency are different from that of the general population and that learning preferences were associated with performance on standardized tests. This multiinstitutional study was conducted to determine the distribution of VARK preferences among interviewees for general surgery residency and the effect of those preferences on United States Medical Licensing Examination (USMLE) scores. The VARK learning inventory was administered to applicants who interviewed at 3 general surgery programs during the 2014 to 2015 academic year. The distribution of VARK learning preferences among interviewees was compared with that of the general population of VARK respondents. Performance on USMLE Step 1 and Step 2 Clinical Knowledge was analyzed for associations with VARK learning preferences. Chi-square, analysis of variance, and Dunnett's test were used for statistical analysis, with p learning modality. The distribution of VARK preferences of interviewees was different than that of the general population (p = 0.02). By analysis of variance, there were no overall differences in USMLE Step 1 and Step 2 Clinical Knowledge scores by VARK preference (p = 0.06 and 0.21, respectively). However, multiple comparison analysis using Dunnett's test revealed that interviewees with R preferences had significantly higher scores than those with multimodal preferences on USMLE Step 1 (239 vs. 222, p = 0.02). Applicants who interview for general surgery residency have a different pattern of VARK preferences than that of the general population. Interviewees with preferences for read/write learning modalities have higher scores
Energy Technology Data Exchange (ETDEWEB)
Ballester, E. Alsina; Bueno, J. Trujillo [Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife (Spain); Belluzzi, L., E-mail: ealsina@iac.es [Istituto Ricerche Solari Locarno, CH-6605 Locarno Monti (Switzerland)
2017-02-10
The spectral line polarization encodes a wealth of information about the thermal and magnetic properties of the solar atmosphere. Modeling the Stokes profiles of strong resonance lines is, however, a complex problem both from a theoretical and computational point of view, especially when partial frequency redistribution (PRD) effects need to be taken into account. In this work, we consider a two-level atom in the presence of magnetic fields of arbitrary intensity (Hanle–Zeeman regime) and orientation, both deterministic and micro-structured. Working within the framework of a rigorous PRD theoretical approach, we have developed a numerical code that solves the full non-LTE radiative transfer problem for polarized radiation, in one-dimensional models of the solar atmosphere, accounting for the combined action of the Hanle and Zeeman effects, as well as for PRD phenomena. After briefly discussing the relevant equations, we describe the iterative method of solution of the problem and the numerical tools that we have developed and implemented. We finally present some illustrative applications to two resonance lines that form at different heights in the solar atmosphere, and provide a detailed physical interpretation of the calculated Stokes profiles. We find that magneto-optical effects have a strong impact on the linear polarization signals that PRD effects produce in the wings of strong resonance lines. We also show that the weak-field approximation has to be used with caution when PRD effects are considered.
Effect of Formative Quizzes on Teacher Candidates’ Learning in General Chemistry
Yalaki, Yalcin; Bayram, Zeki
2015-01-01
Formative assessment or assessment for learning is one of the most emphasized educational innovations around the world. Two of the common strategies that could be used in formative assessment are use of summative tests for formative purposes and comment only marking. We utilized these strategies in the form of formative quizzes in a general chemistry course and measured its effect on students’ learning. The results of our weak-experimental design, which was conducted with 124 pre-service elem...
Kilfeather, G P; Lynch, C D; Sloan, A J; Youngson, C C
2010-04-01
The aim of this study was to investigate the quality of communication and master impressions for the fabrication of cobalt chromium removable partial dentures (RPDs) in general dental practice in England, Ireland and Wales in 2009. Two hundred and ten questionnaires were distributed to 21 laboratories throughout England, Ireland and Wales. Information was collected regarding the quality of written communication and selection of master impression techniques for cobalt chromium partial dentures in general dental practice. One hundred and forty-four questionnaires were returned (response rate = 68%). Alginate was the most popular impression material being used in 58% of cases (n = 84), while plastic stock trays were the most popular impression tray, being used in 31% of cases (n = 44). Twenty-four per cent (n = 35) of impressions were not adequately disinfected. Opposing casts were provided in 81% of cases (n = 116). Written instructions were described as being 'clear' in 31% of cases (n = 44). In 54% of cases (n = 76), the technician was asked to design the RPD. Based on the findings of this study, written communication for cobalt chromium RPDs by general dental practitioners is inadequate. This finding is in breach of relevant contemporary legal and ethical guidance. There are also concerns in relation to the fabrication process for this form of prosthesis, particularly, in relation to consideration of occlusal schemes.
Hibbard, Lisa; Sung, Shannon; Wells, Breche´
2016-01-01
Flipped learning has come to the forefront in education. It maximizes learning by moving content delivery online, where learning can be self-paced, allowing for class time to focus on student-centered active learning. This five-year cross-sectional study assessed student performance in a college general chemistry for majors sequence taught by a…
Ell, Shawn W; Smith, David B; Peralta, Gabriela; Hélie, Sébastien
2017-08-01
When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability are unclear. We report the results of three experiments investigating the impact of category structure and training methodology on the learning and generalization of within-category representations (i.e., correlational structure). Participants were trained on either rule-based or information-integration structures using classification (Is the stimulus a member of Category A or Category B?), concept (e.g., Is the stimulus a member of Category A, Yes or No?), or inference (infer the missing component of the stimulus from a given category) and then tested on either an inference task (Experiments 1 and 2) or a classification task (Experiment 3). For the information-integration structure, within-category representations were consistently learned, could be generalized to novel stimuli, and could be generalized to support inference at test. For the rule-based structure, extended inference training resulted in generalization to novel stimuli (Experiment 2) and inference training resulted in generalization to classification (Experiment 3). These data help to clarify the conditions under which within-category representations can be learned. Moreover, these results make an important contribution in highlighting the impact of category structure and training methodology on the generalization of categorical knowledge.
The relationship between learning mathematics and general cognitive ability in primary school.
Cowan, Richard; Hurry, Jane; Midouhas, Emily
2018-06-01
Three relationships between learning mathematics and general cognitive ability have been hypothesized: The educational hypothesis that learning mathematics develops general cognitive skills, the psychometric hypothesis that differences in general cognitive ability cause differences in mathematical attainment, and the reciprocal influence hypothesis that developments in mathematical ability and general cognitive ability influence each other. These hypotheses are assessed with a sample of 948 children from the Twins Early Development Study who were assessed at 7, 9, and 10 years on mathematics, English, and general cognitive ability. A cross-lagged path analysis with mathematics and general cognitive ability measures supports the reciprocal influence hypothesis between 7 and 9 and between 9 and 10. A second analysis including English assessments only provides evidence of a reciprocal relationship between 7 and 9. Statement of Contribution What is already known on this subject? The correlations between mathematical attainment, literacy, and measures of general cognitive skills are well established. The role of literacy in developing general cognitive skills is emerging. What the present study adds? Mathematics contributes to the development of general cognitive skills. General cognitive ability contributes to mathematical development between 7 and 10. These findings support the hypothesis of reciprocal influence between mathematics and general cognitive ability, at least between 7 and 9. © 2017 The British Psychological Society.
Generalization bounds of ERM-based learning processes for continuous-time Markov chains.
Zhang, Chao; Tao, Dacheng
2012-12-01
Many existing results on statistical learning theory are based on the assumption that samples are independently and identically distributed (i.i.d.). However, the assumption of i.i.d. samples is not suitable for practical application to problems in which samples are time dependent. In this paper, we are mainly concerned with the empirical risk minimization (ERM) based learning process for time-dependent samples drawn from a continuous-time Markov chain. This learning process covers many kinds of practical applications, e.g., the prediction for a time series and the estimation of channel state information. Thus, it is significant to study its theoretical properties including the generalization bound, the asymptotic convergence, and the rate of convergence. It is noteworthy that, since samples are time dependent in this learning process, the concerns of this paper cannot (at least straightforwardly) be addressed by existing methods developed under the sample i.i.d. assumption. We first develop a deviation inequality for a sequence of time-dependent samples drawn from a continuous-time Markov chain and present a symmetrization inequality for such a sequence. By using the resultant deviation inequality and symmetrization inequality, we then obtain the generalization bounds of the ERM-based learning process for time-dependent samples drawn from a continuous-time Markov chain. Finally, based on the resultant generalization bounds, we analyze the asymptotic convergence and the rate of convergence of the learning process.
Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants.
Werchan, Denise M; Collins, Anne G E; Frank, Michael J; Amso, Dima
2016-10-05
Recent research indicates that adults and infants spontaneously create and generalize hierarchical rule sets during incidental learning. Computational models and empirical data suggest that, in adults, this process is supported by circuits linking prefrontal cortex (PFC) with striatum and their modulation by dopamine, but the neural circuits supporting this form of learning in infants are largely unknown. We used near-infrared spectroscopy to record PFC activity in 8-month-old human infants during a simple audiovisual hierarchical-rule-learning task. Behavioral results confirmed that infants adopted hierarchical rule sets to learn and generalize spoken object-label mappings across different speaker contexts. Infants had increased activity over right dorsal lateral PFC when rule sets switched from one trial to the next, a neural marker related to updating rule sets into working memory in the adult literature. Infants' eye blink rate, a possible physiological correlate of striatal dopamine activity, also increased when rule sets switched from one trial to the next. Moreover, the increase in right dorsolateral PFC activity in conjunction with eye blink rate also predicted infants' generalization ability, providing exploratory evidence for frontostriatal involvement during learning. These findings provide evidence that PFC is involved in rudimentary hierarchical rule learning in 8-month-old infants, an ability that was previously thought to emerge later in life in concert with PFC maturation. Hierarchical rule learning is a powerful learning mechanism that allows rules to be selected in a context-appropriate fashion and transferred or reused in novel contexts. Data from computational models and adults suggests that this learning mechanism is supported by dopamine-innervated interactions between prefrontal cortex (PFC) and striatum. Here, we provide evidence that PFC also supports hierarchical rule learning during infancy, challenging the current dogma that PFC is an
Bouchard , Bruno; Dang , Ngoc Minh
2013-01-01
International audience; We consider a singular with state constraints version of the stochastic target problems studied in Soner and Touzi (2002) and more recently Bouchard, Elie and Touzi (2008), among others. This provides a general framework for the pricing of contingent claims under risk constraints. Our extended version perfectly suits to market models with proportional transaction costs and to order book liquidation issues. Our main result is a PDE characterization of the associated pri...
Generalization of motor learning depends on the history of prior action.
Directory of Open Access Journals (Sweden)
John W Krakauer
2006-10-01
Full Text Available Generalization of motor learning refers to our ability to apply what has been learned in one context to other contexts. When generalization is beneficial, it is termed transfer, and when it is detrimental, it is termed interference. Insight into the mechanism of generalization may be acquired from understanding why training transfers in some contexts but not others. However, identifying relevant contextual cues has proven surprisingly difficult, perhaps because the search has mainly been for cues that are explicit. We hypothesized instead that a relevant contextual cue is an implicit memory of action with a particular body part. To test this hypothesis we considered a task in which participants learned to control motion of a cursor under visuomotor rotation in two contexts: by moving their hand through motion of their shoulder and elbow, or through motion of their wrist. Use of these contextual cues led to three observations: First, in naive participants, learning in the wrist context was much faster than in the arm context. Second, generalization was asymmetric so that arm training benefited subsequent wrist training, but not vice versa. Third, in people who had prior wrist training, generalization from the arm to the wrist was blocked. That is, prior wrist training appeared to prevent both the interference and transfer that subsequent arm training should have caused. To explain the data, we posited that the learner collected statistics of contextual history: all upper arm movements also move the hand, but occasionally we move our hands without moving the upper arm. In a Bayesian framework, history of limb segment use strongly affects parameter uncertainty, which is a measure of the covariance of the contextual cues. This simple Bayesian prior dictated a generalization pattern that largely reproduced all three findings. For motor learning, generalization depends on context, which is determined by the statistics of how we have previously used
How do general practice registrars learn from their clinical experience? A critical incident study.
Holmwood, C
1997-01-01
This preliminary study of RACGP registrars in the period of subsequent general practice experience examines the types of clinical experiences from which registrars learn, what they learn from the experiences and the process of learning from such experiences. A critical incident method was used on a semi structured interview process. Registrars were asked to recall clinical incidents where they had learnt something of importance. Data were sorted and categorised manually. Nine registrars were interviewed before new categories of data ceased to develop. Registrars learnt from the opportunity to follow up patients. An emotional response to the interaction was an important part of the learning process. Learning from such experiences is haphazard and unstructured. Registrars accessed human resources in response to their clinical difficulties rather than text or electronic based information sources. Registrars should be aware of their emotional responses to interactions with patients; these emotional responses often indicate important learning opportunities. Clinical interactions and resultant learning could be made less haphazard by structuring consultations with patients with specific problems. These learning opportunities should be augmented by the promotion of follow up of patients.
Cochran, John K
2017-08-01
Recently, Robert Agnew introduced a new general theory of crime and delinquency in which he attempted to corral the vast array of theoretical "causes" of criminal conduct into a more parsimonious statement organized into one of five life domains: self, family, peers, school, and work as well as constraints against crime and motivation for it. These domains are depicted as the source of constraints and motivations and whose effects are, in part, mediated by these constraints and motivations. Based on self-report data on academic dishonesty from a sample of college students, the present study attempts to test this general theory. While several of the life domain variables had significant effects of cheating in the baseline model, all of these effects were fully mediated by constraints and motivations. In the final model, academic dishonesty was observed to be most significantly affected by the perceived severity of formal sanction threats, the number of credit hours enrolled, the frequency of skipping classes, and pressure from friends.
Riggs, Anne E.; Kalish, Charles W.; Alibali, Martha W.
2014-01-01
In any learning situation, children must decide the level of generality with which to encode information. Cues to generality may affect children's memory for different components of a learning episode. In this research, we investigated whether 1 cue to generality, generic language, affects children's memory for information about social categories…
Child first language and adult second language are both tied to general-purpose learning systems.
Hamrick, Phillip; Lum, Jarrad A G; Ullman, Michael T
2018-02-13
Do the mechanisms underlying language in fact serve general-purpose functions that preexist this uniquely human capacity? To address this contentious and empirically challenging issue, we systematically tested the predictions of a well-studied neurocognitive theory of language motivated by evolutionary principles. Multiple metaanalyses were performed to examine predicted links between language and two general-purpose learning systems, declarative and procedural memory. The results tied lexical abilities to learning only in declarative memory, while grammar was linked to learning in both systems in both child first language and adult second language, in specific ways. In second language learners, grammar was associated with only declarative memory at lower language experience, but with only procedural memory at higher experience. The findings yielded large effect sizes and held consistently across languages, language families, linguistic structures, and tasks, underscoring their reliability and validity. The results, which met the predicted pattern, provide comprehensive evidence that language is tied to general-purpose systems both in children acquiring their native language and adults learning an additional language. Crucially, if language learning relies on these systems, then our extensive knowledge of the systems from animal and human studies may also apply to this domain, leading to predictions that might be unwarranted in the more circumscribed study of language. Thus, by demonstrating a role for these systems in language, the findings simultaneously lay a foundation for potentially important advances in the study of this critical domain.
Pacton, Sébastien; Borchardt, Gaëlle; Treiman, Rebecca; Lété, Bernard; Fayol, Michel
2014-05-01
Adults often learn to spell words during the course of reading for meaning, without intending to do so. We used an incidental learning task in order to study this process. Spellings that contained double n, r and t which are common doublets in French, were learned more readily by French university students than spellings that contained less common but still legal doublets. When recalling or recognizing the latter, the students sometimes made transposition errors, doubling a consonant that often doubles in French rather than the consonant that was originally doubled (e.g., tiddunar recalled as tidunnar). The results, found in three experiments using different nonwords and different types of instructions, show that people use general knowledge about the graphotactic patterns of their writing system together with word-specific knowledge to reconstruct spellings that they learn from reading. These processes contribute to failures and successes in memory for spellings, as in other domains.
Directory of Open Access Journals (Sweden)
Caroline Lustenberger
Full Text Available EEG sleep spindle activity (SpA during non-rapid eye movement (NREM sleep has been reported to be associated with measures of intelligence and overnight performance improvements. The reticular nucleus of the thalamus is generating sleep spindles in interaction with thalamocortical connections. The same system enables efficient encoding and processing during wakefulness. Thus, we examined if the triangular relationship between SpA, measures of intelligence and declarative learning reflect the efficiency of the thalamocortical system. As expected, SpA was associated with general cognitive ability, e.g. information processing speed. SpA was also associated with learning efficiency, however, not with overnight performance improvement in a declarative memory task. SpA might therefore reflect the efficiency of the thalamocortical network and can be seen as a marker for learning during encoding in wakefulness, i.e. learning efficiency.
Dwyer, Karen Kangas; Davidson, Marlina M.
2013-01-01
As part of a yearly university mandated assessment of a large basic communication course that fulfills the oral communication general education requirement, this study examined student preferences for textbooks, reading, and learning. Specifically, basic course students ("N"=321) at a large state university in the Midwest were asked to…
Czech Academy of Sciences Publication Activity Database
Svádová, K.; Exnerová, A.; Štys, P.; Landová, E.; Valenta, J.; Fučíková, A.; Socha, Radomír
2009-01-01
Roč. 77, č. 2 (2009), s. 327-336 ISSN 0003-3472 Institutional research plan: CEZ:AV0Z50070508 Keywords : asymmetric generalization * avoidance learning * firebug Subject RIV: ED - Physiology Impact factor: 2.890, year: 2009
Low Complexity Sparse Bayesian Learning for Channel Estimation Using Generalized Mean Field
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri
2014-01-01
We derive low complexity versions of a wide range of algorithms for sparse Bayesian learning (SBL) in underdetermined linear systems. The proposed algorithms are obtained by applying the generalized mean field (GMF) inference framework to a generic SBL probabilistic model. In the GMF framework, we...
Bender, William N.
This book provides classroom-proven strategies designed to empower the teacher to target instructional modifications to the content, process, and products for students with learning disabilities in the general and special education classrooms. Chapter 1 presents the concept of differentiated instruction and how that concept translates into…
Ochterski, Joseph W.
2014-01-01
This article describes the results of using state-of-the-art, research-quality software as a learning tool in a general chemistry secondary school classroom setting. I present three activities designed to introduce fundamental chemical concepts regarding molecular shape and atomic orbitals to students with little background in chemistry, such as…
The Evaluation of Students' Written Reflection on the Learning of General Chemistry Lab Experiment
Han, Ng Sook; Li, Ho Ket; Sin, Lee Choy; Sin, Keng Pei
2014-01-01
Reflective writing is often used to increase understanding and analytical ability. The lack of empirical evidence on the effect of reflective writing interventions on the learning of general chemistry lab experiment supports the examination of this concept. The central goal of this exploratory study was to evaluate the students' written…
Safe from harm: learned, instructed, and symbolic generalization pathways of human threat-avoidance.
Directory of Open Access Journals (Sweden)
Simon Dymond
Full Text Available Avoidance of threatening or unpleasant events is usually an adaptive behavioural strategy. Sometimes, however, avoidance can become chronic and lead to impaired daily functioning. Excessive threat-avoidance is a central diagnostic feature of anxiety disorders, yet little is known about whether avoidance acquired in the absence of a direct history of conditioning with a fearful event differs from directly learned avoidance. In the present study, we tested whether avoidance acquired indirectly via verbal instructions and symbolic generalization result in similar levels of avoidance behaviour and threat-beliefs to avoidance acquired after direct learning. Following fear conditioning in which one conditioned stimulus was paired with shock (CS+ and another was not (CS-, participants either learned or were instructed to make a response that cancelled impending shock. Three groups were then tested with a learned CS+ and CS- (learned group, instructed CS+ (instructed group, and generalized CS+ (derived group presentations. Results showed similar levels of avoidance behaviour and threat-belief ratings about the likelihood of shock across each of the three pathways despite the different mechanisms by which they were acquired. Findings have implications for understanding the aetiology of clinical avoidance in anxiety.
Directory of Open Access Journals (Sweden)
Guoqing Tang
2004-02-01
Full Text Available In this paper we present an approach of incorporating interactive and media-enhanced lectures to promote active learning in Calculus and General Physics courses. The pedagogical practice of using interactive techniques in lectures to require "heads-on" and "hands-on" learning, and involve students more as active participants than passive receivers is a part of academic curricular reform efforts undertaken currently by the mathematics, physics and chemistry departments at North Carolina A&T State University under the NSF funded project "Talent-21: Gateway for Advancing Science and Mathematics Talents."
International Nuclear Information System (INIS)
Ustinov, Eugene A.
2005-01-01
An approach to formulation of inversion algorithms for remote sensing in the thermal spectral region in the case of a scattering planetary atmosphere, based on the adjoint equation of radiative transfer (Ustinov (JQSRT 68 (2001) 195; JQSRT 73 (2002) 29); referred to as Papers 1 and 2, respectively, in the main text), is applied to the general case of retrievals of atmospheric and surface parameters for the scattering atmosphere with nadir viewing geometry. Analytic expressions for corresponding weighting functions for atmospheric parameters and partial derivatives for surface parameters are derived. The case of pure atmospheric absorption with a scattering underlying surface is considered and convergence to results obtained for the non-scattering atmospheres (Ustinov (JQSRT 74 (2002) 683), referred to as Paper 3 in the main text) is demonstrated
Noppel, M; Vehkamäki, H; Winkler, P M; Kulmala, M; Wagner, P E
2013-10-07
Based on the results of a previous paper [M. Noppel, H. Vehkamäki, P. M. Winkler, M. Kulmala, and P. E. Wagner, J. Chem. Phys. 139, 134107 (2013)], we derive a thermodynamically consistent expression for reversible or minimal work needed to form a dielectric liquid nucleus of a new phase on a charged insoluble conducting sphere within a uniform macroscopic one- or multicomponent mother phase. The currently available model for ion-induced nucleation assumes complete spherical symmetry of the system, implying that the seed ion is immediately surrounded by the condensing liquid from all sides. We take a step further and treat more realistic geometries, where a cap-shaped liquid cluster forms on the surface of the seed particle. We derive the equilibrium conditions for such a cluster. The equalities of chemical potentials of each species between the nucleus and the vapor represent the conditions of chemical equilibrium. The generalized Young equation that relates contact angle with surface tensions, surface excess polarizations, and line tension, also containing the electrical contribution from triple line excess polarization, expresses the condition of thermodynamic equilibrium at three-phase contact line. The generalized Laplace equation gives the condition of mechanical equilibrium at vapor-liquid dividing surface: it relates generalized pressures in neighboring bulk phases at an interface with surface tension, excess surface polarization, and dielectric displacements in neighboring phases with two principal radii of surface curvature and curvatures of equipotential surfaces in neighboring phases at that point. We also re-express the generalized Laplace equation as a partial differential equation, which, along with electrostatic Laplace equations for bulk phases, determines the shape of a nucleus. We derive expressions that are suitable for calculations of the size and composition of a critical nucleus (generalized version of the classical Kelvin-Thomson equation).
Kolata, Stefan; Light, Kenneth; Grossman, Henya C.; Hale, Gregory; Matzel, Louis D.
2007-01-01
A single factor (i.e., general intelligence) can account for much of an individuals' performance across a wide variety of cognitive tests. However, despite this factor's robustness, the underlying process is still a matter of debate. To address this question, we developed a novel battery of learning tasks to assess the general learning abilities…
A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.
Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua
2016-01-01
Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.
A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction
Directory of Open Access Journals (Sweden)
Hongyang Lu
2016-01-01
Full Text Available Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV approach and adaptive dictionary learning (DL. In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.
Robinson, Geoffrey
2002-01-01
US studies have shown that a clinician's risk-taking propensity significantly predicts clinical behaviour. Other US studies examining relationships between family practice doctors' preferences for CME and their Kolb learning style have described conflicting findings. The aim of the present study was to investigate GPs' learning styles, risk-taking propensities and CME preferences, and to explore links between them. A descriptive confidential cross-sectional postal questionnaire survey of the 304 general practitioner principals within Portsmouth and South East Hampshire Health Authority was conducted. Two hundred and seventy-four GPs returned questionnaires, a response rate of 90.1%. The Kolb learning style types were assimilators 43.8% (predominant learning abilities watching and thinking), divergers 21.1% (feeling and watching), convergers 18.3% (doing and thinking), and accommodators 16.8% (doing and feeling). The Pearson risk-taking propensities were 65.8% risk neutral, 19.4% risk seeking and 14.8% risk averse. Risk-seeking GPs were significantly more likely to be accommodators or convergers than divergers or assimilators (p = 0.006). Majorities of 54.9% stated that the present PGEA system works well, 85% welcomed feedback from their peers, and 76.8% stated that learning should be an activity for all the practice team. Further majorities would welcome help to decide their learning needs (63.8%) and are looking to judge CME effectiveness by changes in GP performance or patient care (54.8%). Further significant correlations and cross-tabulations were found between learning style and risk-taking and CME attitudes, experiences and preferences. It is concluded that risk seekers and accommodators (doing and feeling) prefer feedback, interaction and practical hands-on learning, and assimilators (watching and thinking) and the risk averse tend towards lectures, theoretical learning formats and less interactive activities. Sharing feelings in groups may be difficult for
MRSA model of learning and adaptation: a qualitative study among the general public
2012-01-01
Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA) infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1) a common model of MRSA learning and adaptation; 2) the self-directed nature of adult learning; 3) the focus on general MRSA information, care and prevention, and antibiotic
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Phrachakrapol Pongsir
2017-06-01
Full Text Available The objectives of this research were to study: 1 the former and present conditions, problem, expectations, possible alternative solutions to solve problems, achieve expectations and the choices made in formulating an action plan for development of learning activity. 2 the results of both expected and unexpected changes from individual, group and organization, also the new knowledge created from learning by doing processes with participatory action research. The 17 participants consist of administrators, teachers, school committee and 5 stakeholders. Such as administrative officer, caretaker, community leader and representative alumni. Research instruments included an observation form, in-depth interview, and document examination. The research finding were as follows: Srijanwittaya general buddhist scripture school lack of equipment for teaching and learning and modern teaching aids. Teachers have not been development for 21st century learning skills. These were the cause of: bored lesson, low student achievement and school has not passed the third quality evaluation by the office for National Education Standards and Quality Assessment (Public Organization Researcher focus on solving problem by 4 projects were Follows: 1 promotion and development of teacher project 2 developing school environment project. 3 encourage collaboration for school development project and 4 improving manage potential for school based management project. After improving found that Srijanwittaya general buddhist scripture school, Loei province passed the quality evaluation and higher students achievement. Moreover, researcher and participants were learnt from research practice such as knowledge and experience. The new knowledge had 3 characteristics as follows: 1 new knowledge on participatory performance of school context 2 new knowledge by 5 steps of participle learning principal and 3 new knowledge by lesson learned visualizing from “SRIJAN Model”.
MRSA model of learning and adaptation: a qualitative study among the general public
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Rohde Rodney E
2012-04-01
Full Text Available Abstract Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1 a common model of MRSA learning and adaptation; 2 the self-directed nature of adult learning; 3 the focus on general MRSA information, care and
Macellini, S.; Maranesi, M.; Bonini, L.; Simone, L.; Rozzi, S.; Ferrari, P. F.; Fogassi, L.
2012-01-01
Macaques can efficiently use several tools, but their capacity to discriminate the relevant physical features of a tool and the social factors contributing to their acquisition are still poorly explored. In a series of studies, we investigated macaques' ability to generalize the use of a stick as a tool to new objects having different physical features (study 1), or to new contexts, requiring them to adapt the previously learned motor strategy (study 2). We then assessed whether the observation of a skilled model might facilitate tool-use learning by naive observer monkeys (study 3). Results of study 1 and study 2 showed that monkeys trained to use a tool generalize this ability to tools of different shape and length, and learn to adapt their motor strategy to a new task. Study 3 demonstrated that observing a skilled model increases the observers' manipulations of a stick, thus facilitating the individual discovery of the relevant properties of this object as a tool. These findings support the view that in macaques, the motor system can be modified through tool use and that it has a limited capacity to adjust the learnt motor skills to a new context. Social factors, although important to facilitate the interaction with tools, are not crucial for tool-use learning. PMID:22106424
Van Nuland, Marc; Thijs, Gaby; Van Royen, Paul; Van Den Noortgate, Wim; Goedhuys, Jo
2010-01-01
Objective: To explore the views and experiences of general practice (GP) vocational trainees regarding communication skills (CS) and the teaching and learning of these skills. METHODS: A purposive sample of second and third (final) year GP trainees took part in six focus group (FG) discussions. Transcripts were coded and analysed in accordance with a grounded theory approach by two investigators using Alas-ti software. Finally results were triangulated by means of semi-structured telephone in...
An application of programmatic assessment for learning (PAL) system for general practice training.
Schuwirth, Lambert; Valentine, Nyoli; Dilena, Paul
2017-01-01
Aim: Programmatic assessment for learning (PAL) is becoming more and more popular as a concept but its implementation is not without problems. In this paper we describe the design principles behind a PAL program in a general practice training context. Design principles: The PAL program was designed to optimise the meaningfulness of assessment information for the registrar and to make him/her use that information to self regulate their learning. The main principles in the program were cognitivist and transformative. The main cognitive principles we used were fostering the understanding of deep structures and stimulating transfer by making registrars constantly connect practice experiences with background knowledge. Ericsson's deliberate practice approach was built in with regard to the provision of feedback combined with Pintrich's model of self regulation. Mezirow's transformative learning and insights from social network theory on collaborative learning were used to support the registrars in their development to become GP professionals. Finally the principal of test enhanced learning was optimised. Epilogue: We have provided this example explain the design decisions behind our program, but not want to present our program as the solution to any given situation.
Van Nuland, Marc; Thijs, Gabie; Van Royen, Paul; Van den Noortgate, Wim; Goedhuys, Jo
2010-01-01
To explore the views and experiences of general practice (GP) vocational trainees regarding communication skills (CS) and the teaching and learning of these skills. A purposive sample of second and third (final) year GP trainees took part in six focus group (FG) discussions. Transcripts were coded and analysed in accordance with a grounded theory approach by two investigators using Alas-ti software. Finally results were triangulated by means of semi-structured telephone interviews. The analysis led to three thematic clusters: (1) trainees acknowledge the essential importance of communication skills and identified contextual factors influencing the learning and application of these skills; (2) trainees identified preferences for learning and receiving feedback on their communication skills; and (3) trainees perceived that the assessment of communication skills is subjective. These themes are organised into a framework for a better understanding of trainees' communication skills as part of their vocational training. The framework helps in leading to a better understanding of the way in which trainees learn and apply communication skills. The unique context of vocational training should be taken into account when trainees' communication skills are assessed. The teaching and learning should be guided by a learner-centred approach. The framework is valuable for informing curricular reform and future research.
Zheng, Xueying; Qin, Guoyou; Tu, Dongsheng
2017-05-30
Motivated by the analysis of quality of life data from a clinical trial on early breast cancer, we propose in this paper a generalized partially linear mean-covariance regression model for longitudinal proportional data, which are bounded in a closed interval. Cholesky decomposition of the covariance matrix for within-subject responses and generalized estimation equations are used to estimate unknown parameters and the nonlinear function in the model. Simulation studies are performed to evaluate the performance of the proposed estimation procedures. Our new model is also applied to analyze the data from the cancer clinical trial that motivated this research. In comparison with available models in the literature, the proposed model does not require specific parametric assumptions on the density function of the longitudinal responses and the probability function of the boundary values and can capture dynamic changes of time or other interested variables on both mean and covariance of the correlated proportional responses. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
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Francine Blanchet-Sadri
2011-08-01
Full Text Available Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match or are compatible with all letters; partial words without holes are said to be full words (or simply words. Given an infinite partial word w, the number of distinct full words over the alphabet that are compatible with factors of w of length n, called subwords of w, refers to a measure of complexity of infinite partial words so-called subword complexity. This measure is of particular interest because we can construct partial words with subword complexities not achievable by full words. In this paper, we consider the notion of recurrence over infinite partial words, that is, we study whether all of the finite subwords of a given infinite partial word appear infinitely often, and we establish connections between subword complexity and recurrence in this more general framework.
West, Eva; Wallin, Anita
2013-04-01
Learning abstract concepts such as sound often involves an ontological shift because to conceptualize sound transmission as a process of motion demands abandoning sound transmission as a transfer of matter. Thus, for students to be able to grasp and use a generalized model of sound transmission poses great challenges for them. This study involved 199 students aged 10-14. Their views about sound transmission were investigated before and after teaching by comparing their written answers about sound transfer in different media. The teaching was built on a research-based teaching-learning sequence (TLS), which was developed within a framework of design research. The analysis involved interpreting students' underlying theories of sound transmission, including the different conceptual categories that were found in their answers. The results indicated a shift in students' understandings from the use of a theory of matter before the intervention to embracing a theory of process afterwards. The described pattern was found in all groups of students irrespective of age. Thus, teaching about sound and sound transmission is fruitful already at the ages of 10-11. However, the older the students, the more advanced is their understanding of the process of motion. In conclusion, the use of a TLS about sound, hearing and auditory health promotes students' conceptualization of sound transmission as a process in all grades. The results also imply some crucial points in teaching and learning about the scientific content of sound.
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Michael E Berend
2016-09-01
Full Text Available The Oxford Partial Knee Replacement was approved for implantation in the US in 2004 after the surgeon completed an educational training requirement. Since then my knee practiced has expanded to over 50% partial knee. This experience coupled with refinement of surgical techniques, anesthesia protocols, and patient selection has facilitated the transformation to same day discharge for partial knee cases and has quickly transitioned to total hip, total knee, and selected revision surgeries. Patient selection has also expanded for outpatient joints and is now based on medical screening criteria and insurance access. Over a two-year period we have performed over 1,000 outpatient arthroplasty procedures with no readmissions for pain control. Overall readmission rate for all reasons was 2%. Patient satisfaction scores were 98% Great-Good for 2014-15. The combination of a partial knee replacement practice and an outpatient joint program brings the best VALUE to the patients, surgeons, and the arthroplasty system and represents the future of arthroplasty care.
Out-of-Sample Generalizations for Supervised Manifold Learning for Classification.
Vural, Elif; Guillemot, Christine
2016-03-01
Supervised manifold learning methods for data classification map high-dimensional data samples to a lower dimensional domain in a structure-preserving way while increasing the separation between different classes. Most manifold learning methods compute the embedding only of the initially available data; however, the generalization of the embedding to novel points, i.e., the out-of-sample extension problem, becomes especially important in classification applications. In this paper, we propose a semi-supervised method for building an interpolation function that provides an out-of-sample extension for general supervised manifold learning algorithms studied in the context of classification. The proposed algorithm computes a radial basis function interpolator that minimizes an objective function consisting of the total embedding error of unlabeled test samples, defined as their distance to the embeddings of the manifolds of their own class, as well as a regularization term that controls the smoothness of the interpolation function in a direction-dependent way. The class labels of test data and the interpolation function parameters are estimated jointly with an iterative process. Experimental results on face and object images demonstrate the potential of the proposed out-of-sample extension algorithm for the classification of manifold-modeled data sets.
Generalization of Auditory Sensory and Cognitive Learning in Typically Developing Children.
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Cristina F B Murphy
research is required to investigate the effects of various stimuli and lengths of training on the generalization of sensory and cognitive learning to literacy skills.
Generalization of Auditory Sensory and Cognitive Learning in Typically Developing Children.
Murphy, Cristina F B; Moore, David R; Schochat, Eliane
2015-01-01
is required to investigate the effects of various stimuli and lengths of training on the generalization of sensory and cognitive learning to literacy skills.
Kersting, Magdalena; Henriksen, Ellen Karoline; Bøe, Maria Vetleseter; Angell, Carl
2018-06-01
Because of its abstract nature, Albert Einstein's theory of general relativity is rarely present in school physics curricula. Although the educational community has started to investigate ways of bringing general relativity to classrooms, field-tested educational material is rare. Employing the model of educational reconstruction, we present a collaborative online learning environment that was introduced to final year students (18-19 years old) in six Norwegian upper secondary physics classrooms. Design-based research methods guided the development of the learning resources, which were based on a sociocultural view of learning and a historical-philosophical approach to teaching general relativity. To characterize students' learning from and interaction with the learning environment we analyzed focus group interviews and students' oral and written responses to assigned problems and discussion tasks. Our findings show how design choices on different levels can support or hinder understanding of general relativity, leading to the formulation of design principles that help to foster qualitative understanding and encourage collaborative learning. The results indicate that upper secondary students can obtain a qualitative understanding of general relativity when provided with appropriately designed learning resources and sufficient scaffolding of learning through interaction with teacher and peers.
McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.
2017-06-01
Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.
Li, Yuelin; Baser, Ray
2012-08-15
The US Food and Drug Administration recently announced the final guidelines on the development and validation of patient-reported outcomes (PROs) assessments in drug labeling and clinical trials. This guidance paper may boost the demand for new PRO survey questionnaires. Henceforth, biostatisticians may encounter psychometric methods more frequently, particularly item response theory (IRT) models to guide the shortening of a PRO assessment instrument. This article aims to provide an introduction on the theory and practical analytic skills in fitting a generalized partial credit model (GPCM) in IRT. GPCM theory is explained first, with special attention to a clearer exposition of the formal mathematics than what is typically available in the psychometric literature. Then, a worked example is presented, using self-reported responses taken from the international personality item pool. The worked example contains step-by-step guides on using the statistical languages r and WinBUGS in fitting the GPCM. Finally, the Fisher information function of the GPCM model is derived and used to evaluate, as an illustrative example, the usefulness of assessment items by their information contents. This article aims to encourage biostatisticians to apply IRT models in the re-analysis of existing data and in future research. Copyright © 2012 John Wiley & Sons, Ltd.
Martins, H H; Alonso, N B; Vidal-Dourado, M; Carbonel, T D; de Araújo Filho, G M; Caboclo, L O; Yacubian, E M; Guilhoto, L M
2011-11-01
We report the results of administration of the Portuguese-Brazilian translation of the Liverpool Adverse Events Profile (LAEP) to 100 patients (mean age=34.5, SD=12.12; 56 females), 61 with symptomatic partial epilepsy (SPE) and 39 with idiopathic generalized epilepsy (IGE) (ILAE, 1989) who were on a stable antiepileptic drug (AED) regimen and being treated in a Brazilian tertiary epilepsy center. Carbamazepine was the most commonly used AED (43.0%), followed by valproic acid (32.0%). Two or more AEDs were used by 69.0% of patients. The mean LAEP score (19 questions) was 37.6 (SD=13.35). The most common adverse effects were sleepiness (35.0%), memory problems (35.0%), and difficulty in concentrating (25.0%). Higher LAEP scores were associated with polytherapy with three or more AEDs (P=0.005), female gender (P0.001) and Hospital Anxiety and Depression Scale (Depression: r=0.637, P<0.001; Anxiety: r=0.621, P<0.001) dimensions. LAEP overall scores were similar in people with SPE and IGE and were not helpful in differentiating adverse effects in these two groups. Clinical variables that influenced global LAEP were seizure frequency (P=0.050) and generalized tonic-clonic seizures in the last month (P=0.031) in the IGE group, and polytherapy with three or more AEDs (P=0.003 and P=0.003) in both IGE and SPE groups. Copyright Â© 2011 Elsevier Inc. All rights reserved.
Behmer, Lawrence P; Fournier, Lisa R
2016-11-01
Questions regarding the malleability of the mirror neuron system (MNS) continue to be debated. MNS activation has been reported when people observe another person performing biological goal-directed behaviors, such as grasping a cup. These findings support the importance of mapping goal-directed biological behavior onto one's motor repertoire as a means of understanding the actions of others. Still, other evidence supports the Associative Sequence Learning (ASL) model which predicts that the MNS responds to a variety of stimuli after sensorimotor learning, not simply biological behavior. MNS activity develops as a consequence of developing stimulus-response associations between a stimulus and its motor outcome. Findings from the ideomotor literature indicate that stimuli that are more ideomotor compatible with a response are accompanied by an increase in response activation compared to less compatible stimuli; however, non-compatible stimuli robustly activate a constituent response after sensorimotor learning. Here, we measured changes in the mu-rhythm, an EEG marker thought to index MNS activity, predicting that stimuli that differ along dimensions of ideomotor compatibility should show changes in mirror neuron activation as participants learn the respective stimulus-response associations. We observed robust mu-suppression for ideomotor-compatible hand actions and partially compatible dot animations prior to learning; however, compatible stimuli showed greater mu-suppression than partially or non-compatible stimuli after explicit learning. Additionally, non-compatible abstract stimuli exceeded baseline only after participants explicitly learned the motor responses associated with the stimuli. We conclude that the empirical differences between the biological and ASL accounts of the MNS can be explained by Ideomotor Theory. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Observations Of General Learning Patterns In An Upper-Level Thermal Physics Course
Meltzer, David E.
2009-11-01
I discuss some observations from using interactive-engagement instructional methods in an upper-level thermal physics course over a two-year period. From the standpoint of the subject matter knowledge of the upper-level students, there was a striking persistence of common learning difficulties previously observed in students enrolled in the introductory course, accompanied, however, by some notable contrasts between the groups. More broadly, I comment on comparisons and contrasts regarding general pedagogical issues among different student sub-populations, for example: differences in the receptivity of lower- and upper-level students to diagrammatic representations; varying receptivity to tutorial-style instructional approach within the upper-level population; and contrasting approaches to learning among physics and engineering sub-populations in the upper-level course with regard to use of symbolic notation, mathematical equations, and readiness to employ verbal explanations.
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Jian Ding
2014-01-01
Full Text Available This paper addresses the problem of P-type iterative learning control for a class of multiple-input multiple-output linear discrete-time systems, whose aim is to develop robust monotonically convergent control law design over a finite frequency range. It is shown that the 2 D iterative learning control processes can be taken as 1 D state space model regardless of relative degree. With the generalized Kalman-Yakubovich-Popov lemma applied, it is feasible to describe the monotonically convergent conditions with the help of linear matrix inequality technique and to develop formulas for the control gain matrices design. An extension to robust control law design against systems with structured and polytopic-type uncertainties is also considered. Two numerical examples are provided to validate the feasibility and effectiveness of the proposed method.
Motlan; Sinulinggga, Karya; Siagian, Henok
2016-01-01
The aim of this research is to determine if inquiry and blended learning based materials can improve student's achievement. The learning materials are: book, worksheet, and test, website, etc. The type of this research is quasi experiment using two-group pretest posttest design. The population is all students of first year who take general physics…
The influence of experiential learning on medical equipment adoption in general practices.
Bourke, Jane; Roper, Stephen
2014-10-01
The benefits of the availability and use of medical equipment for medical outcomes are understood by physicians and policymakers alike. However, there is limited understanding of the decision-making processes involved in adopting and using new technologies in health care organisations. Our study focuses on the adoption of medical equipment in Irish general practices which are marked by considerable autonomy in terms of commercial practice and the range of medical services they provide. We examine the adoption of six items of medical equipment taking into account commercial, informational and experiential stimuli. Our analysis is based on primary survey data collected from a sample of 601 general practices in Ireland on practice characteristics and medical equipment use. We use a multivariate Probit to identify commonalities in the determinants of the adoption. Many factors, such as GP and practice characteristics, influence medical equipment adoption. In addition, we find significant and consistent evidence of the influence of learning-by-using effects on the adoption of medical equipment in a general practice setting. Knowledge generated by experiential or applied learning can have commercial, organisational and health care provision benefits in small health care organisations. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex.
Byers, Anna; Serences, John T
2014-09-01
Learning to better discriminate a specific visual feature (i.e., a specific orientation in a specific region of space) has been associated with plasticity in early visual areas (sensory modulation) and with improvements in the transmission of sensory information from early visual areas to downstream sensorimotor and decision regions (enhanced readout). However, in many real-world scenarios that require perceptual expertise, observers need to efficiently process numerous exemplars from a broad stimulus class as opposed to just a single stimulus feature. Some previous data suggest that perceptual learning leads to highly specific neural modulations that support the discrimination of specific trained features. However, the extent to which perceptual learning acts to improve the discriminability of a broad class of stimuli via the modulation of sensory responses in human visual cortex remains largely unknown. Here, we used functional MRI and a multivariate analysis method to reconstruct orientation-selective response profiles based on activation patterns in the early visual cortex before and after subjects learned to discriminate small offsets in a set of grating stimuli that were rendered in one of nine possible orientations. Behavioral performance improved across 10 training sessions, and there was a training-related increase in the amplitude of orientation-selective response profiles in V1, V2, and V3 when orientation was task relevant compared with when it was task irrelevant. These results suggest that generalized perceptual learning can lead to modified responses in the early visual cortex in a manner that is suitable for supporting improved discriminability of stimuli drawn from a large set of exemplars. Copyright © 2014 the American Physiological Society.
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Bohanec Marko
2017-08-01
Full Text Available Background and Purpose: The process of business to business (B2B sales forecasting is a complex decision-making process. There are many approaches to support this process, but mainly it is still based on the subjective judgment of a decision-maker. The problem of B2B sales forecasting can be modeled as a classification problem. However, top performing machine learning (ML models are black boxes and do not support transparent reasoning. The purpose of this research is to develop an organizational model using ML model coupled with general explanation methods. The goal is to support the decision-maker in the process of B2B sales forecasting.
rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning
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Miron B. Kursa
2014-11-01
Full Text Available Random ferns is a very simple yet powerful classification method originally introduced for specific computer vision tasks. In this paper, I show that this algorithm may be considered as a constrained decision tree ensemble and use this interpretation to introduce a series of modifications which enable the use of random ferns in general machine learning problems. Moreover, I extend the method with an internal error approximation and an attribute importance measure based on corresponding features of the random forest algorithm. I also present the R package rFerns containing an efficient implementation of this modified version of random ferns.
General Dimensional Multiple-Output Support Vector Regressions and Their Multiple Kernel Learning.
Chung, Wooyong; Kim, Jisu; Lee, Heejin; Kim, Euntai
2015-11-01
Support vector regression has been considered as one of the most important regression or function approximation methodologies in a variety of fields. In this paper, two new general dimensional multiple output support vector regressions (MSVRs) named SOCPL1 and SOCPL2 are proposed. The proposed methods are formulated in the dual space and their relationship with the previous works is clearly investigated. Further, the proposed MSVRs are extended into the multiple kernel learning and their training is implemented by the off-the-shelf convex optimization tools. The proposed MSVRs are applied to benchmark problems and their performances are compared with those of the previous methods in the experimental section.
And Others; Dweck, Carol S.
1980-01-01
Two experiments were conducted to examine the role of sex differences in learned helplessness in the generalization of failure experience. Subjects in experiment 1 were fifth graders and subjects in experiment 2 were fourth, fifth, and sixth graders. (MP)
Grenier, Michelle; Miller, Nancy; Black, Ken
2017-01-01
General physical education (GPE) affords many opportunities for students with and without disabilities to interact and develop positive peer relationships. This case study describes one teacher's use of collaborative practices, universal design for learning (UDL), and the inclusion spectrum to create an accessible learning environment in which the…
Bao, Wan-Ning; Haas, Ain; Chen, Xiaojin; Pi, Yijun
2014-01-01
In Agnew's general strain theory, repeated strains can generate crime and delinquency by reducing social control and fostering social learning of crime. Using a sample of 615 middle-and high-school students in China, this study examines how social control and social learning variables mediate the effect of repeated strains in school and at home on…
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.
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.
Hacisalihoglu, Gokhan; Stephens, Desmond; Johnson, Lewis; Edington, Maurice
2018-01-01
Active learning is a pedagogical approach that involves students engaging in collaborative learning, which enables them to take more responsibility for their learning and improve their critical thinking skills. While prior research examined student performance at majority universities, this study focuses on specifically Historically Black Colleges and Universities (HBCUs) for the first time. Here we present work that focuses on the impact of active learning interventions at Florida A&M University, where we measured the impact of active learning strategies coupled with a SCALE-UP (Student Centered Active Learning Environment with Upside-down Pedagogies) learning environment on student success in General Biology. In biology sections where active learning techniques were employed, students watched online videos and completed specific activities before class covering information previously presented in a traditional lecture format. In-class activities were then carefully planned to reinforce critical concepts and enhance critical thinking skills through active learning techniques such as the one-minute paper, think-pair-share, and the utilization of clickers. Students in the active learning and control groups covered the same topics, took the same summative examinations and completed identical homework sets. In addition, the same instructor taught all of the sections included in this study. Testing demonstrated that these interventions increased learning gains by as much as 16%, and students reported an increase in their positive perceptions of active learning and biology. Overall, our results suggest that active learning approaches coupled with the SCALE-UP environment may provide an added opportunity for student success when compared with the standard modes of instruction in General Biology.
Development of a general learning algorithm with applications in nuclear reactor systems
International Nuclear Information System (INIS)
Brittain, C.R.; Otaduy, P.J.; Perez, R.B.
1989-12-01
The objective of this study was development of a generalized learning algorithm that can learn to predict a particular feature of a process by observation of a set of representative input examples. The algorithm uses pattern matching and statistical analysis techniques to find a functional relationship between descriptive attributes of the input examples and the feature to be predicted. The algorithm was tested by applying it to a set of examples consisting of performance descriptions for 277 fuel cycles of Oak Ridge National Laboratory's High Flux Isotope Reactor (HFIR). The program learned to predict the critical rod position for the HFIR from core configuration data prior to reactor startup. The functional relationship bases its predictions on initial core reactivity, the number of certain targets placed in the center of the reactor, and the total exposure of the control plates. Twelve characteristic fuel cycle clusters were identified. Nine fuel cycles were diagnosed as having noisy data, and one could not be predicted by the functional relationship. 13 refs., 6 figs
Development of a general learning algorithm with applications in nuclear reactor systems
Energy Technology Data Exchange (ETDEWEB)
Brittain, C.R.; Otaduy, P.J.; Perez, R.B.
1989-12-01
The objective of this study was development of a generalized learning algorithm that can learn to predict a particular feature of a process by observation of a set of representative input examples. The algorithm uses pattern matching and statistical analysis techniques to find a functional relationship between descriptive attributes of the input examples and the feature to be predicted. The algorithm was tested by applying it to a set of examples consisting of performance descriptions for 277 fuel cycles of Oak Ridge National Laboratory's High Flux Isotope Reactor (HFIR). The program learned to predict the critical rod position for the HFIR from core configuration data prior to reactor startup. The functional relationship bases its predictions on initial core reactivity, the number of certain targets placed in the center of the reactor, and the total exposure of the control plates. Twelve characteristic fuel cycle clusters were identified. Nine fuel cycles were diagnosed as having noisy data, and one could not be predicted by the functional relationship. 13 refs., 6 figs.
Students' Perceptions and Emotions Toward Learning in a Flipped General Science Classroom
Jeong, Jin Su; González-Gómez, David; Cañada-Cañada, Florentina
2016-10-01
Recently, the inverted instruction methodologies are gaining attentions in higher educations by claiming that flipping the classroom engages more effectively students with the learning process. Besides, students' perceptions and emotions involved in their learning process must be assessed in order to gauge the usability of this relatively new instruction methodology, since it is vital in the educational formation. For this reason, this study intends to evaluate the students' perceptions and emotions when a flipped classroom setting is used as instruction methodology. This research was conducted in a general science course, sophomore of the Primary Education bachelor degree in the Training Teaching School of the University of Extremadura (Spain). The results show that the students have the overall positive perceptions to a flipped classroom setting. Particularly, over 80 % of them considered that the course was a valuable learning experience. They also found this course more interactive and were willing to have more courses following a flipped model. According to the students' emotions toward a flipped classroom course, the highest scores were given to the positive emotions, being fun and enthusiasm along with keyword frequency test. Then, the lowest scores were corresponded to negative emotions, being boredom and fear. Therefore, the students attending to a flipped course demonstrated to have more positive and less negative emotions. The results obtained in this study allow drawing a promising tendency about the students' perceptions and emotions toward the flipped classroom methodology and will contribute to fully frame this relatively new instruction methodology.
Directory of Open Access Journals (Sweden)
Nielsen Bente
2008-04-01
Full Text Available Abstract Background We were unable to identify studies that have considered the diffusion of an e-learning programme among a large population of general practitioners. The aim of this study was to investigate the uptake of an e-learning programme introduced to General Practitioners as part of a nation-wide disseminated dementia guideline. Methods A prospective study among all 3632 Danish GPs. The GPs were followed from the launching of the e-learning programme in November 2006 and 6 months forward. Main outcome measures: Use of the e-learning programme. A logistic regression model (GEE was used to identify predictors for use of the e-learning programme. Results In the study period, a total of 192 different GPs (5.3% were identified as users, and 17% (32 had at least one re-logon. Among responders at first login most have learnt about the e-learning programme from written material (41% or from the internet (44%. A total of 94% of the users described their ability of conducting a diagnostic evaluation as good or excellent. Most of the respondents used the e-learning programme due to general interest (90%. Predictors for using the e-learning programme were Males (OR = 1.4, 95% CI 1.1; 2.0 and members of Danish College of General Practice (OR = 2.2, 95% CI 1.5; 3.1, whereas age, experience and working place did not seem to be influential. Conclusion Only few Danish GPs used the e-learning programme in the first 6 months after the launching. Those using it were more often males and members of Danish College of General Practice. Based on this study we conclude, that an active implementation is needed, also when considering electronic formats of CME like e-learning. Trial Registration ClinicalTrials.gov Identifier: NCT00392483.
Transferring and generalizing deep-learning-based neural encoding models across subjects.
Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming
2018-08-01
Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or encoding models), requires measuring cortical responses to large and diverse sets of natural visual stimuli from single subjects. This requirement limits prior studies to few subjects, making it difficult to generalize findings across subjects or for a population. In this study, we developed new methods to transfer and generalize encoding models across subjects. To train encoding models specific to a target subject, the models trained for other subjects were used as the prior models and were refined efficiently using Bayesian inference with a limited amount of data from the target subject. To train encoding models for a population, the models were progressively trained and updated with incremental data from different subjects. For the proof of principle, we applied these methods to functional magnetic resonance imaging (fMRI) data from three subjects watching tens of hours of naturalistic videos, while a deep residual neural network driven by image recognition was used to model visual cortical processing. Results demonstrate that the methods developed herein provide an efficient and effective strategy to establish both subject-specific and population-wide predictive models of cortical representations of high-dimensional and hierarchical visual features. Copyright © 2018 Elsevier Inc. All rights reserved.
Improved probabilistic inference as a general learning mechanism with action video games.
Green, C Shawn; Pouget, Alexandre; Bavelier, Daphne
2010-09-14
Action video game play benefits performance in an array of sensory, perceptual, and attentional tasks that go well beyond the specifics of game play [1-9]. That a training regimen may induce improvements in so many different skills is notable because the majority of studies on training-induced learning report improvements on the trained task but limited transfer to other, even closely related, tasks ([10], but see also [11-13]). Here we ask whether improved probabilistic inference may explain such broad transfer. By using a visual perceptual decision making task [14, 15], the present study shows for the first time that action video game experience does indeed improve probabilistic inference. A neural model of this task [16] establishes how changing a single parameter, namely the strength of the connections between the neural layer providing the momentary evidence and the layer integrating the evidence over time, captures improvements in action-gamers behavior. These results were established in a visual, but also in a novel auditory, task, indicating generalization across modalities. Thus, improved probabilistic inference provides a general mechanism for why action video game playing enhances performance in a wide variety of tasks. In addition, this mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. Copyright © 2010 Elsevier Ltd. All rights reserved.
Working memory training mostly engages general-purpose large-scale networks for learning.
Salmi, Juha; Nyberg, Lars; Laine, Matti
2018-03-21
The present meta-analytic study examined brain activation changes following working memory (WM) training, a form of cognitive training that has attracted considerable interest. Comparisons with perceptual-motor (PM) learning revealed that WM training engages domain-general large-scale networks for learning encompassing the dorsal attention and salience networks, sensory areas, and striatum. Also the dynamics of the training-induced brain activation changes within these networks showed a high overlap between WM and PM training. The distinguishing feature for WM training was the consistent modulation of the dorso- and ventrolateral prefrontal cortex (DLPFC/VLPFC) activity. The strongest candidate for mediating transfer to similar untrained WM tasks was the frontostriatal system, showing higher striatal and VLPFC activations, and lower DLPFC activations after training. Modulation of transfer-related areas occurred mostly with longer training periods. Overall, our findings place WM training effects into a general perception-action cycle, where some modulations may depend on the specific cognitive demands of a training task. Copyright © 2018 Elsevier Ltd. All rights reserved.
2011-01-01
Background Identifying patients with learning disabilities within primary care is central to initiatives for improving the health of this population. UK general practitioners (GPs) receive additional income for maintaining registers of patients with learning disabilities as part of the Quality and Outcomes Framework (QOF), and may opt to provide Directed Enhanced Services (DES), which requires practices to maintain registers of patients with moderate or severe learning disabilities and offer them annual health checks. Objectives This paper describes the development of a register of patients with moderate or severe learning disabilities at one UK general practice. Methods A Read code search of one UK general practice's electronic medical records was conducted in order to identify patients with learning disabilities. Confirmation of diagnoses was sought by scrutinising records and GP verification. Cross-referencing with the practice QOF register of patients with learning disabilities of any severity, and the local authority's list of clients with learning disabilities, was performed. Results Of 15 001 patients, 229 (1.5%) were identified by the Read code search as possibly having learning disabilities. Scrutiny of records and GP verification confirmed 64 had learning disabilities and 24 did not, but the presence or absence of learning disability remained unclear in 141 cases. Cross-referencing with the QOF register (n=81) and local authority list (n=49) revealed little overlap. Conclusion Identifying learning disability and assessing its severity are tasks GPs may be unfamiliar with, and relying on Read code searches may result in under-detection. Further research is needed to define optimum strategies for identifying, cross-referencing and validating practice-based registers of patients with learning disabilities. PMID:22479290
Lodge, Keri-Michèle; Milnes, David; Gilbody, Simon M
2011-03-01
Background Identifying patients with learning disabilities within primary care is central to initiatives for improving the health of this population. UK general practitioners (GPs) receive additional income for maintaining registers of patients with learning disabilities as part of the Quality and Outcomes Framework (QOF), and may opt to provide Directed Enhanced Services (DES), which requires practices to maintain registers of patients with moderate or severe learning disabilities and offer them annual health checks.Objectives This paper describes the development of a register of patients with moderate or severe learning disabilities at one UK general practice.Methods A Read code search of one UK general practice's electronic medical records was conducted in order to identify patients with learning disabilities. Confirmation of diagnoses was sought by scrutinising records and GP verification. Cross-referencing with the practice QOF register of patients with learning disabilities of any severity, and the local authority's list of clients with learning disabilities, was performed.Results Of 15 001 patients, 229 (1.5%) were identified by the Read code search as possibly having learning disabilities. Scrutiny of records and GP verification confirmed 64 had learning disabilities and 24 did not, but the presence or absence of learning disability remained unclear in 141 cases. Cross-referencing with the QOF register (n=81) and local authority list (n=49) revealed little overlap.Conclusion Identifying learning disability and assessing its severity are tasks GPs may be unfamiliar with, and relying on Read code searches may result in under-detection. Further research is needed to define optimum strategies for identifying, cross-referencing and validating practice-based registers of patients with learning disabilities.
Rosenkrantz, Andrew B; Doshi, Ankur M; Ginocchio, Luke A; Aphinyanaphongs, Yindalon
2016-12-01
This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature. Copyright © 2016 The Association of University
Design and Assessment of a General Science STEM Course with a Blended Learning Approach
Courtier, A. M.; Liu, J. C.; St John, K. K.
2015-12-01
Blended learning, a combination of classroom- and computer-mediated teaching and learning, is becoming prominent in higher education, and structured assessment is necessary to determine pedagogical costs and benefits. Assessment of a blended general education science class at James Madison University used a mixed-method causal-comparative design: in Spring 2014, two classes with identical content and similar groups of non-science majors were taught by the same instructor in either blended or full face-to-face formats. The learning experience of 160 students in the two classes was compared based on course and exam grades, classroom observation, and student survey results. Student acquisition of content in both classes was measured with pre-post tests using published concept inventories, and surveys, quizzes, and grade reports in the Blackboard learning management system were additionally used for data collection. Exams were identical between the two sections, and exam questions were validated in advance by a faculty member who teaches other sections of the same course. A course experience questionnaire was administered to measure students' personal experiences in both classes, addressing dimensions of good teaching, clear goals and standards, generic skills, appropriate assessment and workload, and emphasis on independence. Using a STEM classroom observation checklist, two researchers conducted in-class observations for four 75-minute face-to-face meetings with similar content focus in both classes, which allowed assessment of student engagement and participation. We will present details of the course design and research plan, as well as assessment results from both quantitative and qualitative analysis. The preliminary findings include slightly higher average grade distribution and more ready responses to in-class activities in the blended class.
Directory of Open Access Journals (Sweden)
Mohammad Madallh Alhabahba
2014-01-01
Full Text Available A rigorous understanding of the use of Smartphones for foreign language vocabulary acquisition is crucial. Employing the technology acceptance model, this study aims to investigate students’ behavioural factors affecting Saudi students’ attitudes towards employing Smartphones for foreign vocabulary acquisition. Two hundred and seventy-three students studying in a preparatory year programme were surveyed. SmartPLS was employed to analyse the data obtained from the study’s sample. The results revealed that perceived usefulness and attitude proved to be significantly and positively related to vocabulary development. In addition, perceived usefulness and perceived ease of use proved to be significant predictors of students’ attitudes towards the use of Smartphone for vocabulary learning. However, the study showed that the relationship between perceived ease of use and vocabulary development is not significant. Thus, publishers of dictionaries may find it necessary to take into account the important role played by the design of dictionaries interfaces in facilitating the use of dictionaries in Smartphones. Furthermore, teachers and educators are encouraged to employ creative activities (e.g., word guessing games that invest students’ use of Smartphones to learn vocabularies. Using Smartphones in learning improves interaction among students and teachers. Discussion and conclusions are also provided.
Directory of Open Access Journals (Sweden)
Senyue Zhang
2016-01-01
Full Text Available According to the characteristics that the kernel function of extreme learning machine (ELM and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. First, the generalized triangle Hermitian kernel function was constructed by using the product of triangular kernel and generalized Hermite Dirichlet kernel, and the proposed kernel function was proved as a valid kernel function of extreme learning machine. Then, the learning methodology of the extreme learning machine based on the proposed kernel function was presented. The biggest advantage of the proposed kernel is its kernel parameter values only chosen in the natural numbers, which thus can greatly shorten the computational time of parameter optimization and retain more of its sample data structure information. Experiments were performed on a number of binary classification, multiclassification, and regression datasets from the UCI benchmark repository. The experiment results demonstrated that the robustness and generalization performance of the proposed method are outperformed compared to other extreme learning machines with different kernels. Furthermore, the learning speed of proposed method is faster than support vector machine (SVM methods.
Kitiashvili, Anastasia
2014-01-01
The aim of this article is to study teachers' attitudes toward assessment of students' learning and their assessment practices in Georgia's general educational institutions. Georgia is a country in the South Caucasus with a population of 4.5 million people, with 2300 general educational institutions and about 559,400 students. The research…
International Nuclear Information System (INIS)
Rabin, B.M.; Hunt, W.A.; Lee, J.
1984-01-01
The effect of area postrema lesions on the acquisition of a conditioned taste aversion following partial body exposure to ionizing radiation was investigated in rats exposed to head-only irradiation at 100, 200 and 300 rad or to body-only irradiation at 100 and 200 rad. Following head-only irradiation area postrema lesions produced a significant attenuation of the radiation-induced taste aversion at all dose levels, although the rats still showed a significant reduction in sucrose preference. Following body-only exposure, area postrema lesions completely disrupted the acquisition of the conditioned taste aversion. The results are interpreted as indicating that: (a) the acquisition of a conditioned taste aversion following body-only exposure is mediated by the area postrema; and (b) taste aversion learning following radiation exposure to the head-only is mediated by both the area postrema and a mechanism which is independent of the area postrema
Santhana Vannan, S. K.; Ramachandran, R.; Deb, D.; Beaty, T.; Wright, D.
2017-12-01
This paper summarizes the workflow challenges of curating and publishing data produced from disparate data sources and provides a generalized workflow solution to efficiently archive data generated by researchers. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biogeochemical dynamics and the Global Hydrology Resource Center (GHRC) DAAC have been collaborating on the development of a generalized workflow solution to efficiently manage the data publication process. The generalized workflow presented here are built on lessons learned from implementations of the workflow system. Data publication consists of the following steps: Accepting the data package from the data providers, ensuring the full integrity of the data files. Identifying and addressing data quality issues Assembling standardized, detailed metadata and documentation, including file level details, processing methodology, and characteristics of data files Setting up data access mechanisms Setup of the data in data tools and services for improved data dissemination and user experience Registering the dataset in online search and discovery catalogues Preserving the data location through Digital Object Identifiers (DOI) We will describe the steps taken to automate, and realize efficiencies to the above process. The goals of the workflow system are to reduce the time taken to publish a dataset, to increase the quality of documentation and metadata, and to track individual datasets through the data curation process. Utilities developed to achieve these goal will be described. We will also share metrics driven value of the workflow system and discuss the future steps towards creation of a common software framework.
Selected chapters from general chemistry in physics teaching with the help of e - learning
Feszterová, Melánia
2017-01-01
Education in the field of natural disciplines - Mathematics, Physics, Chemistry, Ecology and Biology takes part in general education at all schools on the territory of Slovakia. Its aim is to reach the state of balanced development of all personal characteristics of pupils, to teach them correctly identify and analyse problems, propose solutions and above all how to solve the problem itself. High quality education can be reached only through the pedagogues who have a good expertise knowledge, practical experience and high level of pedagogical abilities. The teacher as a disseminator of natural-scientific knowledge should be not only well-informed about modern tendencies in the field, but he/she also should actively participate in project tasks This is the reason why students of 1st year of study (bachelor degree) at the Department of Physics of Constantine the Philosopher University in Nitra attend lectures in the frame of subject General Chemistry. In this paper we present and describe an e - learning course called General Chemistry that is freely accessible to students. One of the aims of this course is to attract attention towards the importance of cross-curricular approach which seems to be fundamental in contemporary natural-scientific education (e.g. between Physics and Chemistry). This is why it is so important to implement a set of new topics and tasks that support development of abilities to realise cross-curricular goals into the process of preparation of future teachers of Physics.
Falmagne, Jean-Claude
2011-01-01
Learning spaces offer a rigorous mathematical foundation for practical systems of educational technology. Learning spaces generalize partially ordered sets and are special cases of knowledge spaces. The various structures are investigated from the standpoints of combinatorial properties and stochastic processes. Leaning spaces have become the essential structures to be used in assessing students' competence of various topics. A practical example is offered by ALEKS, a Web-based, artificially intelligent assessment and learning system in mathematics and other scholarly fields. At the heart of A
International Nuclear Information System (INIS)
Azoury, Fares; Heymann, Steve; Acevedo, Catalina; Spielmann, Marc; Vielh, Philippe; Garbay, Jean-Rémi; Taghian, Alphonse G.; Marsiglia, Hugo; Bourgier, Céline
2012-01-01
Introduction: The present study prospectively reported both physicians’ and patients’ assessment for toxicities, cosmetic assessment and patients’ satisfaction after 3D-conformal accelerated partial breast irradiation (APBI). Materials and Methods: From October 2007 to September 2009, 30 early breast cancer patients were enrolled in a 3D-conformal APBI Phase II trial (40 Gy/10 fractions/5 days). Treatment related toxicities and cosmetic results were assessed by both patients and physicians at each visit (at 1, 2, 6 months, and then every 6 months). Patient satisfaction was also scored. Results: After a median follow-up of 27.7 months, all patients were satisfied with APBI treatment, regardless of cosmetic results or late adverse events. Good/excellent cosmetic results were noticed by 80% of patients versus 92% of cases by radiation oncologists. Breast pain was systematically underestimated by physicians (8–20% vs. 16.6–26.2%; Kappa coefficient KC = 0.16–0.44). Grade 1 and 2 fibrosis and/or breast retraction occurred in 7–12% of patients and were overestimated by patients (KC = 0.14–0.27). Conclusions: Present results have shown discrepancies between patient and physician assessments. In addition to the assessment of efficacy and toxicity after 3D-conformal APBI, patients’ cosmetic results consideration and satisfaction should be also evaluated.
DEFF Research Database (Denmark)
Mikkelsen, Thorbjørn H.; Sokolowski, Ineta; Olesen, Frede
2006-01-01
, and circumstances under which such exchange is accepted. SUBJECTS: A structured questionnaire sent to 1198 GPs of whom 61% responded. RESULTS. GPs had a positive attitude towards discussing adverse events in the clinic with colleagues and staff and in their continuing medical education groups. The GPs had...... a positive attitude to reporting adverse events to a database if the system granted legal and administrative immunity to reporters. The majority preferred a reporting system located at a research institute. CONCLUSION: GPs have a very positive attitude towards discussing and reporting adverse events......OBJECTIVE: To investigate GPs' attitudes to and willingness to report and learn from adverse events and to study how a reporting system should function. DESIGN: Survey. SETTING: General practice in Denmark. MAIN OUTCOME MEASURES: GPs' attitudes to exchange of experience with colleagues and others...
Spierings, Michelle J.; ten Cate, Carel
2016-01-01
The ability to abstract a regularity that underlies strings of sounds is a core mechanism of the language faculty but might not be specific to language learning or even to humans. It is unclear whether and to what extent nonhuman animals possess the ability to abstract regularities defining the relation among arbitrary auditory items in a string and to generalize this abstraction to strings of acoustically novel items. In this study we tested these abilities in a songbird (zebra finch) and a parrot species (budgerigar). Subjects were trained in a go/no-go design to discriminate between two sets of sound strings arranged in an XYX or an XXY structure. After this discrimination was acquired, each subject was tested with test strings that were structurally identical to the training strings but consisted of either new combinations of known elements or of novel elements belonging to other element categories. Both species learned to discriminate between the two stimulus sets. However, their responses to the test strings were strikingly different. Zebra finches categorized test stimuli with previously heard elements by the ordinal position that these elements occupied in the training strings, independent of string structure. In contrast, the budgerigars categorized both novel combinations of familiar elements as well as strings consisting of novel element types by their underlying structure. They thus abstracted the relation among items in the XYX and XXY structures, an ability similar to that shown by human infants and indicating a level of abstraction comparable to analogical reasoning. PMID:27325756
Directory of Open Access Journals (Sweden)
Leonova O.I.,
2014-11-01
Full Text Available At the moment the question of how to create and maintain the psychological safety of the educational environment of the school is not sufficiently studied. Meanwhile, there has been proved its positive effect on the psychological health of students, their emotional and personal well-being, the formation of a meta-subjective and personal educational outcomes. This paper describes a study the purpose of which was to examine and verify empiricaly the features of management activities in the educational organization to create a psychologically safe learning environment. We studied personality traits of the Head of an educational organization by the procedure "Troubleshooting leadership abilities" (E. Zharikova, E. Krushelnytsky, techniques "Diagnosis of the level of burnout" (V.V. Boyko, methods of self-management style assessment (A.V. Agrashenkova, modified by E.P. Ilyin, and methods for rapid assessment of health, activity, mood (SAN. We proposed mechanisms to solve the problem of creating a comfortable and safe learning environment in the educational organization of general education
Li, D.; Fang, N. Z.
2017-12-01
Dallas-Fort Worth Metroplex (DFW) has a population of over 7 million depending on many water supply reservoirs. The reservoir inflow plays a vital role in water supply decision making process and long-term strategic planning for the region. This paper demonstrates a method of utilizing deep learning algorithms and multi-general circulation model (GCM) platform to forecast reservoir inflow for three reservoirs within the DFW: Eagle Mountain Lake, Lake Benbrook and Lake Arlington. Ensemble empirical mode decomposition was firstly employed to extract the features, which were then represented by the deep belief networks (DBNs). The first 75 years of the historical data (1940 -2015) were used to train the model, while the last 2 years of the data (2016-2017) were used for the model validation. The weights of each DBN gained from the training process were then applied to establish a neural network (NN) that was able to forecast reservoir inflow. Feature predictors used for the forecasting model were generated from weather forecast results of the downscaled multi-GCM platform for the North Texas region. By comparing root mean square error (RMSE) and mean bias error (MBE) with the observed data, the authors found that the deep learning with downscaled multi-GCM platform is an effective approach in the reservoir inflow forecasting.
Teach Astronomy: An Online Resource for General Education and Informal Learning
Hardegree-Ullman, Kevin; Impey, C.; Patikkal, A.; Srinathan, A.; Collaboration of Astronomy Teaching Scholars CATS
2012-01-01
Teach Astronomy is a website developed for students and informal learners who would like to learn more general astronomy knowledge. This learning tool aggregates content from a myriad of sources, including: an introductory astronomy text book by C. D. Impey and W. K. Hartmann, astronomy related articles on Wikipedia, images from the Astronomy Picture of the Day, two to three minute video clips by C. D. Impey, podcasts from 365 Days of Astronomy, and news from Science Daily. In addition, Teach Astronomy utilizes a novel technology to cluster and display search results called a Wikimap. We present an overview of the website's features and suggestions for making the best use of Teach Astronomy in the classroom or at home. This material is based in part upon work supported by the National Science Foundation under Grant No. 0715517, a CCLI Phase III Grant for the Collaboration of Astronomy Teaching Scholars (CATS). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Stensrud, Tonje L; Mjaaland, Trond A; Finset, Arnstein
2012-01-01
Background General practitioners (GPs) often see patients presenting with mental health problems, but their training regarding mental health treatment varies. GPs' communication skills are of particular importance in these consultations, and communication skills training of GPs has been found to improve patients' mental health. To tailor a communication skills training by basing it on GPs' learning needs and self-efficacy, thereby maximising learning, we conducted a questionnaire study.
Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm
Wong, Ka Chun
2011-02-05
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm
Wong, Ka Chun; Peng, Chengbin; Wong, Manhon; Leung, Kwongsak
2011-01-01
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs. © 2011 Springer-Verlag.
Kondo, Shuhei; Shibata, Tadashi; Ohmi, Tadahiro
1995-02-01
We have investigated the learning performance of the hardware backpropagation (HBP) algorithm, a hardware-oriented learning algorithm developed for the self-learning architecture of neural networks constructed using neuron MOS (metal-oxide-semiconductor) transistors. The solution to finding a mirror symmetry axis in a 4×4 binary pixel array was tested by computer simulation based on the HBP algorithm. Despite the inherent restrictions imposed on the hardware-learning algorithm, HBP exhibits equivalent learning performance to that of the original backpropagation (BP) algorithm when all the pertinent parameters are optimized. Very importantly, we have found that HBP has a superior generalization capability over BP; namely, HBP exhibits higher performance in solving problems that the network has not yet learnt.
Directory of Open Access Journals (Sweden)
Therdsak Maitaouthong
2011-11-01
Full Text Available This article presents the factors affecting the integration of information literacy in the teaching and learning processes of general education courses at an undergraduate level, where information literacy is used as a tool in the student-centered teaching approach. The research was divided into two phases: (1 The study of factors affecting at a policy level – a qualitative research method conducted through an in-depth interview of the vice president for academic affairs and the Director of the General Education Management Center, and (2 The survey of factors affecting in the teaching and learning processes, which is concluded through the questioning of lecturers of general education courses, and librarians. The qualitative data was analyzed on content, and the quantitative data was analyzed through the use of descriptive statistics, weight of score prioritization and percentage. Two major categories were found to have an impact on integrating information literacy in the teaching and learning of general education courses at an undergraduate level. (1 Six factors at a policy level, namely, institutional policy, administrative structure and system, administrators’ roles, resources and infrastructures, learning resources and supporting programs, and teacher evaluation and development. (2 There are eleven instructional factors: roles of lecturers, roles of librarians, roles of learners, knowledge and understanding of information literacy of lecturers and librarians, cooperation between librarians and lecturers, learning outcomes, teaching plans, teaching methods, teaching activities, teaching aids, and student assessment and evaluation.
MacArthur, Juliet; Brown, Michael; McKechanie, Andrew; Mack, Siobhan; Hayes, Matthew; Fletcher, Joan
2015-07-01
To examine the role of learning disability liaison nurses in facilitating reasonable and achievable adjustments to support access to general hospital services for people with learning disabilities. Mixed methods study involving four health boards in Scotland with established Learning Disability Liaison Nurses (LDLN) Services. Quantitative data of all liaison nursing referrals over 18 months and qualitative data collected from stakeholders with experience of using the liaison services within the previous 3-6 months. Six liaison nurses collected quantitative data of 323 referrals and activity between September 2008-March 2010. Interviews and focus groups were held with 85 participants included adults with learning disabilities (n = 5), carers (n = 16), primary care (n = 39), general hospital (n = 19) and liaison nurses (n = 6). Facilitating reasonable and achievable adjustments was an important element of the LDLNs' role and focussed on access to information; adjustments to care; appropriate environment of care; ensuring equitable care; identifying patient need; meeting patient needs; and specialist tools/resources. Ensuring that reasonable adjustments are made in the general hospital setting promotes person-centred care and equal health outcomes for people with a learning disability. This view accords with 'Getting it right' charter produced by the UK Charity Mencap which argues that healthcare professionals need support, encouragement and guidance to make reasonable adjustments for this group. LDLNs have an important and increasing role to play in advising on and establishing adjustments that are both reasonable and achievable. © 2015 John Wiley & Sons Ltd.
Indian Academy of Sciences (India)
First page Back Continue Last page Overview Graphics. Partial Cancellation. Full Cancellation is desirable. But complexity requirements are enormous. 4000 tones, 100 Users billions of flops !!! Main Idea: Challenge: To determine which cross-talker to cancel on what “tone” for a given victim. Constraint: Total complexity is ...
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.
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
A general picture of the learning communities: characteristics, similarities and differences.
Verkleij, K.A.M.; Francke, A.L.; Voordouw, I.; Albers, M.; Gobbens, R.J.J.
2016-01-01
Background: Because learning communities of community care nurses and nursing lectures are a new phenomenon, it is of interest to evaluate en monitor the learning communities. the Netherlands Institute for Health Services Research, NIVEL, was commissioned to monitor the realization of the learning
Kalish, Michael L.; Newell, Ben R.; Dunn, John C.
2017-01-01
It is sometimes supposed that category learning involves competing explicit and procedural systems, with only the former reliant on working memory capacity (WMC). In 2 experiments participants were trained for 3 blocks on both filtering (often said to be learned explicitly) and condensation (often said to be learned procedurally) category…
Evaluation of the Learning Process of Students Reinventing the General Law of Energy Conservation
Logman, Paul; Kaper, Wolter; Ellermeijer, Ton
2015-01-01
To investigate the relationship between context and concept we have constructed a conceptual learning path in which students reinvent the concept of energy conservation and embedded this path in two authentic practices. A comparison of the expected learning outcome with actual student output for the most important steps in the learning path gives…
Galloway, Kelli R.; Bretz, Stacey Lowery
2015-01-01
Understanding how students learn in the undergraduate chemistry teaching laboratory is an essential component to developing evidence-based laboratory curricula. The Meaningful Learning in the Laboratory Instrument (MLLI) was developed to measure students' cognitive and affective expectations and experiences for learning in the chemistry…
Toledo, Santiago; Dubas, Justin M.
2016-01-01
An emphasis on higher-order thinking within the curriculum has been a subject of interest in the chemical and STEM literature due to its ability to promote meaningful, transferable learning in students. The systematic use of learning taxonomies could be a practical way to scaffold student learning in order to achieve this goal. This work proposes…
Teaching and learning the geological knowledge as a part of the science education general field
Aguirre-Pérez, Constancio
2010-05-01
Since the early 50s of last century the Teaching of Science has undergone a process of continuous development, (Gutiérrez, 1987; Aliberas, Gutierrez and Izquierdo, 1989) to become a scientific discipline largely accepted as such by many different universities worldwide. Besides, the proliferation of publications, magazines, conferences, symposia, meetings, and so on, proves this assertion. In these publications and meetings the Teaching of Science (or Science Education in more general terms) is addressed as a new field of research, teaching and educational innovation focused on the processes of teaching and learning of the experimental sciences (all of them: Physics, Chemistry, Biology and Geology). The study of this discipline is undertaken from different pedagogical, epistemological, psychological and sociological approaches. From this general perspective we can say that over the last two decades each of the sciences has developed specific characteristics so that, today, we could speak about specific didactics for each one of them. In the case of Geology (or Geoscience) Teaching there have been significant contributions from the following fields of research: the students' prior ideas (constructivist approach), the history of geology (as a subject-specific field) and from epistemology (Pedrinaci, E. 2000). The body of geoscience knowledge has an internal logic (as happens with the other science subjects) that allows us to organize the contents to teach, selecting, arranging and establishing proper relations between them. Still geology has a central, transverse, inter-and transdisciplinary character for its relationship with the other sciences. This character makes it appear as one of the disciplines with a huge potential to combine different methodologies of teaching and learning and different learning models already tested in the research field of Physics, Chemistry or Biology Education. Moreover, the most recent term coined for it "geosciences or earth and
General and Specific Culture Learning in EFL Textbooks Aimed at Adult Learners in Spain
Directory of Open Access Journals (Sweden)
Rodríguez Antonio R. Raigón
2015-03-01
Full Text Available Since language teaching in modern-day society is closely linked to cultural instruction, this study employs the model of a cultural learning analysis based on the earlier work of Paige and Lee. Using this model, the authors analysed the cultural content of six B1 and B2-level textbooks for teaching English to adults in Spain, and carried out a comparative study of the results, contrasting the two levels. Findings show that the subjective aspects of culture receive less coverage in textbooks, despite being fundamental to an understanding of the values of a society. Regarding the comparison between B1 and B2 levels, the data indicate that the number of big “C” Culture occurrences is similar for both levels, although there are differences in other cultural aspects. So, for example, culture in general is dealt with more at the B1 level, whereas small “c” culture is dealt with more at the B2 level.
Starting a robotic program in general thoracic surgery: why, how, and lessons learned.
Cerfolio, Robert J; Bryant, Ayesha S; Minnich, Douglas J
2011-06-01
We report our experience in starting a robotic program in thoracic surgery. We retrospectively reviewed our experience in starting a robotic program in general thoracic surgery on a consecutive series of patients. Between February 2009 and September 2010, 150 patients underwent robotic operations. Types of procedures were lobectomy in 62, thymectomy in 30, and benign esophageal procedures in 6. No thymectomy or esophageal procedures required conversion. One conversion was needed for suspected bleeding for a mediastinal mass. Twelve patients were converted for lobectomy (none for bleeding, 1 in the last 24). Median operative time for robotic thymectomy was 119 minutes, and median length of stay was 1 day. The median time for robotic lobectomy was 185 minutes, and median length of stay was 2 days. There were no operative deaths. Morbidity occurred in 23 patients (15%). All patients with cancer had R0 resections and resection of all visible mediastinal and hilar lymph nodes. Robotic surgery is safe and oncologically sound. It requires training of the entire operating room team. The learning curve is steep, involving port placement, availability of the proper instrumentation, use of the correct robotic arms, and proper patient positioning. The robot provides an ideal surgical approach for thymectomy and other mediastinal tumors. Its advantage over thoracoscopy for pulmonary resection is unproven; however, we believe complete thoracic lymph node dissection and teaching is easier. Importantly, defined credentialing for surgeons and cost analysis studies are needed. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
1978-11-01
This discussion paper considers the possibility of applying to the recycle of plutonium in thermal reactors a particular method of partial processing based on the PUREX process but named CIVEX to emphasise the differences. The CIVEX process is based primarily on the retention of short-lived fission products. The paper suggests: (1) the recycle of fission products with uranium and plutonium in thermal reactor fuel would be technically feasible; (2) it would, however, take ten years or more to develop the CIVEX process to the point where it could be launched on a commercial scale; (3) since the majority of spent fuel to be reprocessed this century will have been in storage for ten years or more, the recycling of short-lived fission products with the U-Pu would not provide an effective means of making refabrication fuel ''inaccessible'' because the radioactivity associated with the fission products would have decayed. There would therefore be no advantage in partial processing
Lo, Hao-Chang
2013-01-01
The objective of this study was to develop an online report writing activity that was a constructive and cooperative learning process for a course on traditional general physics experiments. Wiki, a CMC authoring tool, was used to construct the writing platform. Fifty-eight undergraduate students (33 men and 25 women), working in randomly assigned…
Keovilay, Sisavath
2015-01-01
This phenomenological research study explored the lived experiences of culinary arts students learning general education online while enrolled in a face-to-face (f2f) culinary arts class. This research used Interpretative Phenomenological Analysis (IPA) to analyze how culinary arts students, in a not-for-profit Florida University, made sense of…
Danner, Daniel; Hagemann, Dirk; Schankin, Andrea; Hager, Marieke; Funke, Joachim
2011-01-01
The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed…
Zhang, Xiao; Räsänen, Pekka; Koponen, Tuire; Aunola, Kaisa; Lerkkanen, Marja-Kristiina; Nurmi, Jari-Erik
2017-01-01
The longitudinal relations of domain-general and numerical skills at ages 6-7 years to 3 cognitive domains of arithmetic learning, namely knowing (written computation), applying (arithmetic word problems), and reasoning (arithmetic reasoning) at age 11, were examined for a representative sample of 378 Finnish children. The results showed that…
Cowan, Richard; Powell, Daisy
2014-01-01
Explanations of the marked individual differences in elementary school mathematical achievement and mathematical learning disability (MLD or dyscalculia) have involved domain-general factors (working memory, reasoning, processing speed, and oral language) and numerical factors that include single-digit processing efficiency and multidigit skills…
Gadbois, Shannon A.; Sturgeon, Ryan D.
2011-01-01
Background: Academic self-handicapping (ASH) tendencies, strategies students employ that increase their chances of failure on assessments while protecting self-esteem, are correlated with classroom goal structures and to learners' general self-perceptions and learning strategies. In particular, greater ASH is related to poorer academic performance…
Ranga, Jayashree S.
2017-01-01
Videos are an integral part of online courses. In this study, customized YouTube videos were explored as teaching and learning materials in place of face-to-face discussion sessions in General Chemistry courses. The videos were created using a budget-friendly and interactive app on an iPad. The customized YouTube videos were available to students…
van Velzen, Joke H.
2018-01-01
There were two purposes for this mixed methods study: to investigate (a) the realistic meaning of awareness and understanding as the underlying constructs of general knowledge of the learning process and (b) a procedure for data consolidation. The participants were 11th-grade high school and first-year university students. Integrated data…
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.
Stephens, Ana; Fonger, Nicole L.; Blanton, Maria; Knuth, Eric
2016-01-01
In this paper, we describe our learning progressions approach to early algebra research that involves the coordination of a curricular framework, an instructional sequence, written assessments, and levels of sophistication describing the development of students' thinking. We focus in particular on what we have learning through this approach about…
Scaffolded Semi-Flipped General Chemistry Designed to Support Rural Students' Learning
Lenczewski, Mary S.
2016-01-01
Students who lack academic maturity can sometimes feel overwhelmed in a fully flipped classroom. Here an alternative, the Semi-Flipped method, is discussed. Rural students, who face unique challenges in transitioning from high school learning to college-level learning, can particularly profit from the use of the Semi-Flipped method in the General…
Textbook-Bundled Metacognitive Tools: A Study of LearnSmart's Efficacy in General Chemistry
Thadani, Vandana; Bouvier-Brown, Nicole C.
2016-01-01
College textbook publishers increasingly bundle sophisticated technology-based study tools with their texts. These tools appear promising, but empirical work on their efficacy is needed. We examined whether LearnSmart, a study tool bundled with McGraw-Hill's textbook "Chemistry" (Chang & Goldsby, 2013), improved learning in an…
Bloom, Elana; Heath, Nancy
2010-01-01
Children with nonverbal learning disabilities (NVLD) have been found to be worse at recognizing facial expressions than children with verbal learning disabilities (LD) and without LD. However, little research has been done with adolescents. In addition, expressing and understanding facial expressions is yet to be studied among adolescents with LD…
Yadav, Ram Bharos; Srivastava, Subodh; Srivastava, Rajeev
2016-01-01
The proposed framework is obtained by casting the noise removal problem into a variational framework. This framework automatically identifies the various types of noise present in the magnetic resonance image and filters them by choosing an appropriate filter. This filter includes two terms: the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimizing the negative log likelihood of the corresponding probability density functions: Gaussian or Rayleigh or Rician. Further, due to the ill-posedness of the likelihood term, a prior function is needed. This paper examines three partial differential equation based priors which include total variation based prior, anisotropic diffusion based prior, and a complex diffusion (CD) based prior. A regularization parameter is used to balance the trade-off between data fidelity term and prior. The finite difference scheme is used for discretization of the proposed method. The performance analysis and comparative study of the proposed method with other standard methods is presented for brain web dataset at varying noise levels in terms of peak signal-to-noise ratio, mean square error, structure similarity index map, and correlation parameter. From the simulation results, it is observed that the proposed framework with CD based prior is performing better in comparison to other priors in consideration.
Vannoy, Steven D; Mauer, Barbara; Kern, John; Girn, Kamaljeet; Ingoglia, Charles; Campbell, Jeannie; Galbreath, Laura; Unützer, Jürgen
2011-07-01
Integration of general medical and mental health services is a growing priority for safety-net providers. The authors describe a project that established a one-year learning collaborative focused on integration of services between community health centers (CHCs) and community mental health centers (CMHCs). Specific targets were treatment for general medical and psychiatric symptoms related to depression, bipolar disorder, alcohol use disorders, and metabolic syndrome. This observational study used mixed methods. Quantitative measures included 15 patient-level health indicators, practice self-assessment of resources and support for chronic disease self-management, and participant satisfaction. Sixteen CHC-CMHC pairs were selected for the learning collaborative series. One pair dropped out because of personnel turnover. All teams increased capacity on one or more patient health indicators. CHCs scored higher than CMHCs on support for chronic disease self-management. Participation in the learning collaborative increased self-assessment scores for CHCs and CMHCs. Participant satisfaction was high. Observations by faculty indicate that quality improvement challenges included tracking patient-level outcomes, workforce issues, and cross-agency communication. Even though numerous systemic barriers were encountered, the findings support existing literature indicating that the learning collaborative is a viable quality improvement approach for enhancing integration of general medical and mental health services between CHCs and CMHCs. Real-world implementation of evidence-based guidelines presents challenges often absent in research. Technical resources and support, a stable workforce with adequate training, and adequate opportunities for collaborator communications are particular challenges for integrating behavioral and general medical services across CHCs and CMHCs.
2016-09-01
Dunleavy M, Dede C. Augmented reality teaching and learning. Handbook of research on educational communications and technology . New York (NY): Springer...taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems. 1994;77(12):1321–1329. Noordzij ML, Scholten P, Laroy-Noordzij...Generalized Intelligent Framework for Tutoring (GIFT) and Augmented REality Sandtable (ARES) by Michael W Boyce, Ramsamooj J Reyes, Deeja E Cruz, Charles
Yuan, Robin K; Hebert, Jenna C; Thomas, Arthur S; Wann, Ellen G; Muzzio, Isabel A
2015-01-01
Although predator odors are ethologically relevant stimuli for rodents, the molecular pathways and contribution of some brain regions involved in predator odor conditioning remain elusive. Inhibition of histone deacetylases (HDACs) in the dorsal hippocampus has been shown to enhance shock-induced contextual fear learning, but it is unknown if HDACs have differential effects along the dorso-ventral hippocampal axis during predator odor fear learning. We injected MS-275, a class I HDAC inhibitor, bilaterally in the dorsal or ventral hippocampus of mice and found that it had no effects on innate anxiety in either region. We then assessed the effects of MS-275 at different stages of fear learning along the longitudinal hippocampal axis. Animals were injected with MS-275 or vehicle after context pre-exposure (pre-conditioning injections), when a representation of the context is first formed, or after exposure to coyote urine (post-conditioning injections), when the context becomes associated with predator odor. When MS-275 was administered after context pre-exposure, dorsally injected animals showed enhanced fear in the training context but were able to discriminate it from a neutral environment. Conversely, ventrally injected animals did not display enhanced learning in the training context but generalized the fear response to a neutral context. However, when MS-275 was administered after conditioning, there were no differences between the MS-275 and vehicle control groups in either the dorsal or ventral hippocampus. Surprisingly, all groups displayed generalization to a neutral context, suggesting that predator odor exposure followed by a mild stressor such as restraint leads to fear generalization. These results may elucidate distinct functions of the dorsal and ventral hippocampus in predator odor-induced fear conditioning as well as some of the molecular mechanisms underlying fear generalization.
Directory of Open Access Journals (Sweden)
Amelia S Knopf
Full Text Available AIDS-related illness is the leading cause of mortality for adolescents in sub-Saharan Africa. Together, Kenya, Tanzania, and Uganda account for 21% of HIV-infected adolescents in sub-Saharan Africa. The United Nations framework for addressing the epidemic among adolescents calls for comprehensive sexual and reproductive health education. These HIV prevention efforts could be informed by a synthesis of existing research about the formal and informal sexual education of adolescents in countries experiencing generalized epidemics. The purpose of this study was to describe the process of sexual learning among East African adolescents living in the context of generalized HIV epidemics.Qualitative metasynthesis, a systematic procedure for integrating the results of multiple qualitative studies addressing a similar phenomenon, was used. Thirty-two research reports met study inclusion criteria. The reports were assessed in a four-step analytic process: appraisal, classification of findings, synthesis of findings, and construction of a framework depicting the process of sexual learning in this population.The framework includes three phases of sexual learning: 1 being primed for sex, 2 making sense of sex, and 3 having sexual experiences. Adolescents were primed for sex through gender norms, cultural practices, and economic structures as well as through conversations and formal instruction. They made sense of sex by acquiring information about sexual intercourse, reproduction and pregnancy, sexually transmitted infections, and relationships and by developing a variety of beliefs and attitudes about these topics. Some adolescents described having sexual experiences that met wants or needs, but many experienced sex that was coerced or violent. Whether sex was wanted, coerced, or violent, adolescents experienced worry about sexually transmitted infections or premarital pregnancy.The three phases of sexual learning interact to shape adolescents' sexual lives
Robert, Jenay; Lewis, Scott E.; Oueini, Razanne; Mapugay, Andrea
2016-01-01
The research-based pedagogical strategy of flipped classes has been shown to be effective for increasing student achievement and retention in postsecondary chemistry classes. The purpose of flipped classes is to move content delivery (e.g., lecture) outside of the classroom, freeing more face-to-face time for active learning strategies. The…
Illicit Drug Use Among South Korean Offenders: Assessing the Generality of Social Learning Theory.
Yun, Minwoo; Kim, Eunyoung
2015-10-01
Since the mid-1990s, illicit drug use has become a problem in Korean society. This trend is likely due to the rapid globalization and expansion that occurred with the Internet revolution, which led to greater numbers of people socially learning about drug culture. The current study attempts to uncover criminogenic causality of such social learning about drug use by studying adult felony drug offenders in South Korea. The data used for the study were obtained from self-reported surveys, originally collected by the Korean Institution of Criminology (KIC). The final sample comprised 1,452 felony offenders convicted of illicit drug use, and their responses were analyzed with a set of multiple logistic regression tests. The current study found supportive evidence for the generalizability of social learning theory from the sample of the South Korean adult drug offenders. We argue that the current study provides additional empirical evidence that supports the generalizability of social learning theory. © The Author(s) 2014.
Brembs, Bjorn; de Ibarra, Natalie Hempel
2006-01-01
We have used a genetically tractable model system, the fruit fly "Drosophila melanogaster" to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning…
Nyce, Peggy A.; And Others
1977-01-01
Forty-four third graders were given a two-choice conceptual discrimination learning task. The two major factors were (1) four treatment groups varying at the extremes on two personality measures, approval motivation and locus of control and (2) sex. (MS)
Effect of Formative Quizzes on Teacher Candidates' Learning in General Chemistry
Yalaki, Yalcin; Bayram, Zeki
2015-01-01
Formative assessment or assessment for learning is one of the most emphasized educational innovations around the world. Two of the common strategies that could be used in formative assessment are use of summative tests for formative purposes and comment only marking. We utilized these strategies in the form of formative quizzes in a general…
Pavesi, Eloisa; Gooch, Allison; Lee, Elizabeth; Fletcher, Max L.
2013-01-01
We investigated the role of cholinergic neurotransmission in olfactory fear learning. Mice receiving pairings of odor and foot shock displayed fear to the trained odor the following day. Pretraining injections of the nicotinic antagonist mecamylamine had no effect on subsequent freezing, while the muscarinic antagonist scopolamine significantly…
Using supervised machine learning to code policy issues: Can classifiers generalize across contexts?
Burscher, B.; Vliegenthart, R.; de Vreese, C.H.
2015-01-01
Content analysis of political communication usually covers large amounts of material and makes the study of dynamics in issue salience a costly enterprise. In this article, we present a supervised machine learning approach for the automatic coding of policy issues, which we apply to news articles
de Premorel, Géraud; Giurfa, Martin; Andraud, Christine; Gomez, Doris
2017-10-25
Iridescence-change of colour with changes in the angle of view or of illumination-is widespread in the living world, but its functions remain poorly understood. The presence of iridescence has been suggested in flowers where diffraction gratings generate iridescent colours. Such colours have been suggested to serve plant-pollinator communication. Here we tested whether a higher iridescence relative to corolla pigmentation would facilitate discrimination, learning and retention of iridescent visual targets. We conditioned bumblebees ( Bombus terrestris ) to discriminate iridescent from non-iridescent artificial flowers and we varied iridescence detectability by varying target iridescent relative to pigment optical effect. We show that bees rewarded on targets with higher iridescent relative to pigment effect required fewer choices to complete learning, showed faster generalization to novel targets exhibiting the same iridescence-to-pigment level and had better long-term memory retention. Along with optical measurements, behavioural results thus demonstrate that bees can learn iridescence-related cues as bona fide signals for flower reward. They also suggest that floral advertising may be shaped by competition between iridescence and corolla pigmentation, a fact that has important evolutionary implications for pollinators. Optical measurements narrow down the type of cues that bees may have used for learning. Beyond pollinator-plant communication, our experiments help understanding how receivers influence the evolution of iridescence signals generated by gratings. © 2017 The Author(s).
Hadadgar, Arash; Changiz, Tahereh; Masiello, Italo; Dehghani, Zahra; Mirshahzadeh, Nahidossadat; Zary, Nabil
2016-08-22
General practitioners (GP) update their knowledge and skills by participating in continuing medical education (CME) programs either in a traditional or an e-Learning format. GPs' beliefs about electronic format of CME have been studied but without an explicit theoretical framework which makes the findings difficult to interpret. In other health disciplines, researchers used theory of planned behavior (TPB) to predict user's behavior. In this study, an instrument was developed to investigate GPs' intention to use e-Learning in CME based on TPB. The goodness of fit of TPB was measured using confirmatory factor analysis and the relationship between latent variables was assessed using structural equation modeling. A total of 148 GPs participated in the study. Most of the items in the questionnaire related well to the TPB theoretical constructs, and the model had good fitness. The perceived behavioral control and attitudinal constructs were included, and the subjective norms construct was excluded from the structural model. The developed questionnaire could explain 66 % of the GPs' intention variance. The TPB could be used as a model to construct instruments that investigate GPs' intention to participate in e-Learning programs in CME. The findings from the study will encourage CME managers and researchers to explore the developed instrument as a mean to explain and improve the GPs' intentions to use eLearning in CME.
Ye, Li; Oueini, Razanne; Dickerson, Austin P.; Lewis, Scott E.
2015-01-01
This study used a series of text message inquiries sent to General Chemistry students asking: "Have you studied for General Chemistry I in the past 48 hours? If so, how did you study?" This method for collecting data is novel to chemistry education research so the first research goals were to investigate the feasibility of the technique…
Garth, Belinda; Kirby, Catherine; Silberberg, Peter; Brown, James
2016-08-19
Learning plans are a compulsory component of the training and assessment requirements of general practice (GP) registrars in Australia. There is a small but growing number of studies reporting that learning plans are not well accepted or utilised in general practice training. There is a lack of research examining this apparent contradiction. The aim of this study was to examine use and perceived utility of formal learning plans in GP vocational training. This mixed-method Australian national research project utilised online learning plan usage data from 208 GP registrars and semi-structured focus groups and telephone interviews with 35 GP registrars, 12 recently fellowed GPs, 16 supervisors and 17 medical educators across three Regional Training Providers (RTPs). Qualitative data were analysed thematically using template analysis. Learning plans were used mostly as a log of activities rather than as a planning tool. Most learning needs were entered and ticked off as complete on the same day. Learning plans were perceived as having little value for registrars in their journey to becoming a competent GP, and as a bureaucratic hurdle serving as a distraction rather than an aid to learning. The process of learning planning was valued more so than the documentation of learning planning. This study provides creditable evidence that mandated learning plans are broadly considered by users to be a bureaucratic impediment with little value as a learning tool. It is more important to support registrars in planning their learning than to enforce documentation of this process in a learning plan. If learning planning is to be an assessed competence, methods of assessment other than the submission of a formal learning plan should be explored.
International Nuclear Information System (INIS)
Guisasola, Jenaro; Zuza, Kristina; Almudi, José-Manuel
2013-01-01
Textbooks are a very important tool in the teaching–learning process and influence important aspects of the process. This paper presents an analysis of the chapter on electromagnetic induction and Faraday's law in 19 textbooks on general physics for first-year university courses for scientists and engineers. This analysis was based on criteria formulated from the theoretical framework of electromagnetic induction in classical physics and students' learning difficulties concerning these concepts. The aim of the work presented here is not to compare a textbook against the ideal book, but rather to try and find a series of explanations, examples, questions, etc that provide evidence on how the topic is presented in relation to the criteria above. It concludes that despite many aspects being covered properly, there are others that deserve greater attention. (paper)
2017-01-01
Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions—a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process—the generation, on the basis of semantic memory, of a novel episodic representation—is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872378
Altmann, Gerry T M
2017-01-05
Statistical approaches to emergent knowledge have tended to focus on the process by which experience of individual episodes accumulates into generalizable experience across episodes. However, there is a seemingly opposite, but equally critical, process that such experience affords: the process by which, from a space of types (e.g. onions-a semantic class that develops through exposure to individual episodes involving individual onions), we can perceive or create, on-the-fly, a specific token (a specific onion, perhaps one that is chopped) in the absence of any prior perceptual experience with that specific token. This article reviews a selection of statistical learning studies that lead to the speculation that this process-the generation, on the basis of semantic memory, of a novel episodic representation-is itself an instance of a statistical, in fact associative, process. The article concludes that the same processes that enable statistical abstraction across individual episodes to form semantic memories also enable the generation, from those semantic memories, of representations that correspond to individual tokens, and of novel episodic facts about those tokens. Statistical learning is a window onto these deeper processes that underpin cognition.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).
Hennessy, M J; Binnie, C D
2000-01-01
To establish the incidence and symptoms of partial seizures in a cohort of patients investigated on account of known sensitivity to intermittent photic stimulation and/or precipitation of seizures by environmental visual stimuli such as television (TV) screens or computer monitors. We report 43 consecutive patients with epilepsy, who had exhibited a significant EEG photoparoxysmal response or who had seizures precipitated by environmental visual stimuli and underwent detailed assessment of their photosensitivity in the EEG laboratory, during which all were questioned concerning their ictal symptoms. All patients were considered on clinical grounds to have an idiopathic epilepsy syndrome. Twenty-eight (65%) patients reported visually precipitated attacks occurring initially with maintained consciousness, in some instances evolving to a period of confusion or to a secondarily generalized seizure. Visual symptoms were most commonly reported and included positive symptoms such as coloured circles or spots, but also blindness and subjective symptoms such as "eyes going funny." Other symptoms described included nonspecific cephalic sensations, deja-vu, auditory hallucinations, nausea, and vomiting. No patient reported any clear spontaneous partial seizures, and there were no grounds for supposing that any had partial epilepsy excepting the ictal phenomenology of some or all of the visually induced attacks. These findings provide clinical support for the physiological studies that indicate that the trigger mechanism for human photosensitivity involves binocularly innervated cells located in the visual cortex. Thus the visual cortex is the seat of the primary epileptogenic process, and the photically triggered discharges and seizures may be regarded as partial with secondary generalization.
Murray, E.; Jolly, B.; Modell, M.
1997-01-01
OBJECTIVE: To determine whether students acquired clinical skills as well in general practice as in hospital and whether there was any difference in the acquisition of specific skills in the two environments. DESIGN: Randomised crossover trial. SUBJECTS AND SETTING: Annual intake of first year clinical students at one medical school. INTERVENTION: A 10 week block of general internal medicine, one half taught in general practice, the other in hospital. Students started at random in one location and crossed over after five weeks. OUTCOME MEASURES: Students' performance in two equivalent nine station objective structured clinical examinations administered at the mid and end points of the block: a direct comparison of the two groups' performance at five weeks; analysis of covariance, using their first examination scores as a covariate, to determine students' relative improvement over the second five weeks of their attachment. RESULTS: 225 students rotated through the block; all took at least one examination and 208 (92%) took both. For the first half of the year there was no significant difference in the students' acquisition of clinical skills in the two environments; later, however, students taught in general practice improved slightly more than those taught in hospital (P = 0.007). CONCLUSIONS: Students can learn clinical skills as well in general practice as in hospital; more work is needed to clarify where specific skills, knowledge, and attitudes are best learnt to allow rational planning of the undergraduate curriculum. PMID:9361543
Partial twisting for scalar mesons
International Nuclear Information System (INIS)
Agadjanov, Dimitri; Meißner, Ulf-G.; Rusetsky, Akaki
2014-01-01
The possibility of imposing partially twisted boundary conditions is investigated for the scalar sector of lattice QCD. According to the commonly shared belief, the presence of quark-antiquark annihilation diagrams in the intermediate state generally hinders the use of the partial twisting. Using effective field theory techniques in a finite volume, and studying the scalar sector of QCD with total isospin I=1, we however demonstrate that partial twisting can still be performed, despite the fact that annihilation diagrams are present. The reason for this are delicate cancellations, which emerge due to the graded symmetry in partially quenched QCD with valence, sea and ghost quarks. The modified Lüscher equation in case of partial twisting is given
Target size matters: target errors contribute to the generalization of implicit visuomotor learning.
Reichenthal, Maayan; Avraham, Guy; Karniel, Amir; Shmuelof, Lior
2016-08-01
The process of sensorimotor adaptation is considered to be driven by errors. While sensory prediction errors, defined as the difference between the planned and the actual movement of the cursor, drive implicit learning processes, target errors (e.g., the distance of the cursor from the target) are thought to drive explicit learning mechanisms. This distinction was mainly studied in the context of arm reaching tasks where the position and the size of the target were constant. We hypothesize that in a dynamic reaching environment, where subjects have to hit moving targets and the targets' dynamic characteristics affect task success, implicit processes will benefit from target errors as well. We examine the effect of target errors on learning of an unnoticed perturbation during unconstrained reaching movements. Subjects played a Pong game, in which they had to hit a moving ball by moving a paddle controlled by their hand. During the game, the movement of the paddle was gradually rotated with respect to the hand, reaching a final rotation of 25°. Subjects were assigned to one of two groups: The high-target error group played the Pong with a small ball, and the low-target error group played with a big ball. Before and after the Pong game, subjects performed open-loop reaching movements toward static targets with no visual feedback. While both groups adapted to the rotation, the postrotation reaching movements were directionally biased only in the small-ball group. This result provides evidence that implicit adaptation is sensitive to target errors. Copyright © 2016 the American Physiological Society.
Learning about light and optics in on-line general education classes using at-home experimentation
Millspaw, Jacob; Wang, Gang; Masters, Mark F.
2014-07-01
College students are facing a constantly evolving educational system. Some still see mostly the traditional face to face lecture type classes where as others may never set foot on campus thanks to distance learning programs. In between they may enroll in a mix of face-to-face, two-way broadcasted interactive courses, streaming lecture courses, hybrid face-to-face/ on-line courses and the ominous MOOC! A large number of these non-traditional courses are general education courses and play an important role in developing non-science majors' understanding of science in general, and of physics in particular. We have been keeping pace with theses modern modes of instruction by offering several on-line courses such as Physics for Computer Graphics and Animation and Light and Color. These courses cover basic concepts in light, color and optics.
Menard, Lauren A.
2011-01-01
A contextual analysis of the general education default and student benefit is presented from the perspective of school-based compliance with federal mandates from IDEIA [Individuals with Disabilities Education Improvement Act] of 2004. A goal was to inform school administrators striving to develop and maintain effective, inclusive learning…
Kazlauskiene, Ausra; Gaucaite, Ramute; Poceviciene, Rasa
2016-01-01
Implementation of the result-oriented (self-)education paradigm in the general education school requires sustainable changes in didactics not only on the strategic document plane but also in educational practice. However, its implementation in practice is complicated. The success of the interaction between theory and practice largely depends on…
Researching Student Learning in a Two-Tiered General Education Program
Csomay, Eniko; Pollard, Elizabeth; Bordelon, Suzanne; Beck, Audrey
2015-01-01
Despite the desire of employers to hire those with the critical-thinking and communication skills a general education (GE) program can offer, the value of GE programs is often questioned due to concerns about four-year graduation rates, perceived low immediate economic payoff, and a dearth of evidence to support their efficacy. This article…
Nilsen, Line Lundvoll
2011-01-01
Purpose: Videoconferencing between general practitioners and hospitals has been developed to provide higher quality health care services in Norway by promoting interaction between levels of care. This article aims to explore the use of videoconferencing for information exchange and consultation throughout the patient trajectory and to investigate…
Assessing Expressive Movement: Measuring Student Learning Outcomes in the General Music Classroom
Butke, Marla A.
2014-01-01
Expressive movement, created by students to demonstrate musical elements and artistry, provides a valid assessment opportunity for general music teachers. This purposeful movement, "plastique animée", was developed by Swiss composer, Émile Jaques-Dalcroze, in the early 20th century. "Plastique animée" can serve as a useful…
Menard, Elizabeth
2013-01-01
Creativity can be experienced in many roles of musicianship: performing, improvising, and composing. Yet, activities that encourage creative thought in our music classrooms can be a challenge to implement. A strong music education curriculum for middle school general music is important; as this may be the last time we reach students who do not…
Objective Function and Learning Algorithm for the General Node Fault Situation.
Xiao, Yi; Feng, Rui-Bin; Leung, Chi-Sing; Sum, John
2016-04-01
Fault tolerance is one interesting property of artificial neural networks. However, the existing fault models are able to describe limited node fault situations only, such as stuck-at-zero and stuck-at-one. There is no general model that is able to describe a large class of node fault situations. This paper studies the performance of faulty radial basis function (RBF) networks for the general node fault situation. We first propose a general node fault model that is able to describe a large class of node fault situations, such as stuck-at-zero, stuck-at-one, and the stuck-at level being with arbitrary distribution. Afterward, we derive an expression to describe the performance of faulty RBF networks. An objective function is then identified from the formula. With the objective function, a training algorithm for the general node situation is developed. Finally, a mean prediction error (MPE) formula that is able to estimate the test set error of faulty networks is derived. The application of the MPE formula in the selection of basis width is elucidated. Simulation experiments are then performed to demonstrate the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Víctor Tadeo Pérez Martínez
2011-12-01
Full Text Available Introducción: Las necesidades de aprendizaje o capacitación se dan a partir del contraste entre el desempeño ideal y el real, bien sea para un individuo o un grupo determinado. Constituyen el punto de partida para la búsqueda de una solución pedagógica que capacite y contribuya a la transformación cualitativa de los servicios de salud. Su oportuna identificación, es una herramienta de la educación permanente. Objetivo: Identificar las necesidades de aprendizaje de los médicos que laboran en los equipos de atención primaria de salud, acerca de la conducta suicida, en tres policlínicos del municipio Playa. Métodos: Se realizó la identificación de las necesidades de aprendizaje mediante un cuestionario escrito, que se aplicó de forma colectiva y anónima a 20 especialistas de Medicina General Integral, seleccionados al azar, que laboran en tres policlínicos del extremo Este, del municipio Playa. Resultados: Se puntualizaron las deficiencias e insuficiencias de los conocimientos y habilidades profesionales acerca del comportamiento suicida, sobre todo en lo que se refiere a la perspectiva clínica de este complejo y multidimensional fenómeno. Conclusiones: A pesar de que la conducta suicida constituye, en el primer nivel de atención, uno de los programas priorizados, en lo que a salud mental se refiere, la mayoría de los especialistas presenta dificultades en la atención integral de estos pacientes, lo cual constituye un riesgo poco explorado. En ocasiones, su evaluación adolece, de elementos de indagación y análisis, lo que afecta el adecuado seguimiento de estos.Introduction: Learning needs or training appear from the contrast between the ideal and real performance whether for an subject or a determined group, being the start point for search of a educational solution training and contributing to qualitative transformation of health services. Its timely identification is a tool of the permanent education. Objectives: To
Gubkin, M. K.; Ivanov, D. A.; Ivanova, I. V.; Spivak, V. S.
2017-11-01
The Department of General physics and nuclear fusion, National Research University “Moscow Power Engineering Institute”, developed a set of tests (over 1000 questions) for the current control of knowledge of students in the section “Electricity and magnetism” of the General physics course using the internet distance learning system “Prometheus” (fourth generation). Under this section of the proposed test tasks are divided into sections corresponding to the topics section. These tasks include quality issues, design tasks, tasks with a choice of answers (one of many, many of many), the job with the selection region in the figure, tasks with detailed answer. The variety of tasks allows the teacher not only to objectively assess the student acquired knowledge but also to develop his problem-solving skills, to learn to be fluent in theory. The results of testing conducted for several years, show the high interest of students in the repeated independent execution of tasks and correlate well with the results of intermediate certification (exams).
Shen, C.; Fang, K.
2017-12-01
Deep Learning (DL) methods have made revolutionary strides in recent years. A core value proposition of DL is that abstract notions and patterns can be extracted purely from data, without the need for domain expertise. Process-based models (PBM), on the other hand, can be regarded as repositories of human knowledge or hypotheses about how systems function. Here, through computational examples, we argue that there is merit in integrating PBMs with DL due to the imbalance and lack of data in many situations, especially in hydrology. We trained a deep-in-time neural network, the Long Short-Term Memory (LSTM), to learn soil moisture dynamics from Soil Moisture Active Passive (SMAP) Level 3 product. We show that when PBM solutions are integrated into LSTM, the network is able to better generalize across regions. LSTM is able to better utilize PBM solutions than simpler statistical methods. Our results suggest PBMs have generalization value which should be carefully assessed and utilized. We also emphasize that when properly regularized, the deep network is robust and is of superior testing performance compared to simpler methods.
Human mate-choice copying is domain-general social learning.
Street, Sally E; Morgan, Thomas J H; Thornton, Alex; Brown, Gillian R; Laland, Kevin N; Cross, Catharine P
2018-01-29
Women appear to copy other women's preferences for men's faces. This 'mate-choice copying' is often taken as evidence of psychological adaptations for processing social information related to mate choice, for which facial information is assumed to be particularly salient. No experiment, however, has directly investigated whether women preferentially copy each other's face preferences more than other preferences. Further, because prior experimental studies used artificial social information, the effect of real social information on attractiveness preferences is unknown. We collected attractiveness ratings of pictures of men's faces, men's hands, and abstract art given by heterosexual women, before and after they saw genuine social information gathered in real time from their peers. Ratings of faces were influenced by social information, but no more or less than were images of hands and abstract art. Our results suggest that evidence for domain-specific social learning mechanisms in humans is weaker than previously suggested.
Robotics as a resource to facilitate the learning and general skills development
Directory of Open Access Journals (Sweden)
Flor Ángela Bravo Sánchez
2012-07-01
Full Text Available Normal.dotm 0 0 1 127 729 Universidad de Salamanca 6 1 895 12.0 0 false 18 pt 18 pt 0 0 false false false /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} The growing importance of technology in the world today and its continuous development, makes the technology becomes an integral part of the formation process in childhood and youth. For this reason is important to develop proposals that are offered to children and young people to come into contact with new technologies, that is possible through the use of software and hardware tools, such as robotic prototypes and specialized programs for educational purposes This paper shows the importance of the use of robotics as a learning tool and presents the typical stages that must be confronted in implementing educational robotics projects in the classroom. It also presents an educational robotics project called "Mundo Robotica" which seeks to involve robotics in the classroom through practical activities and learning resources, all this is articulated from a virtual platform.
Beckley, Scott
Many college students struggle with first-semester general chemistry. Prior studies have shown that a student's prior knowledge of chemistry, a cognitive factor, does not account for the total variance when measured by examination scores. This study explored the role of self-regulated learning (SRL) to identify the degree of success or failure of students with two outcome variables (i.e., American Chemical Society Comprehensive First-Term General Chemistry Examination (Form 2009) and hour-examination averages). The SRL construct consists of three interrelated components (i.e., cognitive, metacognitive, and motivational). SRL theory focuses on the idea of reciprocal determinism, in which the impact of one component of self-regulation affects the other two components. In the quantitative portion of this mixed methods study, eight measures of SRL were used to determine the `level' of self-regulation for each student. SRL variables were used in regression analysis and provided additional and unique variances. Cluster analysis techniques identified two distinct groups of students (i.e., adaptive and maladaptive). Generally, adaptive learners were associated with higher levels of SRL and success in the course; maladaptive learners had lower levels of SRL and struggled with the course demands. For the qualitative portion of the study, student volunteers (n = 8) were interviewed to gauge their views on the role of instruction in influencing their examination performances. The findings indicated that perceptions of teaching methods, demands of the course, course structure, feedback, and assessments were associated with the students' levels of self-regulation. Interviews revealed four SRL styles. Rote memorizers tended to fragment instruction and then memorize each fragment, while algorithmic memorizers tended to imitate the step-by-step problem-solving strategies of the instructor or the textbook. Globalizers were intrinsically motivated to learn the material but tended to
Directory of Open Access Journals (Sweden)
Merav Parter
2008-11-01
Full Text Available One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV. The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions.
Buchs, Nicolas C; Addeo, Pietro; Bianco, Francesco M; Gorodner, Veronica; Ayloo, Subhashini M; Elli, Enrique F; Oberholzer, José; Benedetti, Enrico; Giulianotti, Pier C
2012-08-01
To assess factors associated with morbidity and mortality following the use of robotics in general surgery. Case series. University of Illinois at Chicago. Eight hundred eighty-four consecutive patients who underwent a robotic procedure in our institution between April 2007 and July 2010. Perioperative morbidity and mortality. During the study period, 884 patients underwent a robotic procedure. The conversion rate was 2%, the mortality rate was 0.5%, and the overall postoperative morbidity rate was 16.7%. The reoperation rate was 2.4%. Mean length of stay was 4.5 days (range, 0.2-113 days). In univariate analysis, several factors were associated with increased morbidity and included either patient-related (cardiovascular and renal comorbidities, American Society of Anesthesiologists score ≥ 3, body mass index [calculated as weight in kilograms divided by height in meters squared] surgery, malignant disease, body mass index of less than 30, hypertension, and transfusion were factors significantly associated with a higher risk for complications. American Society of Anesthesiologists score of 3 or greater, age 70 years or older, cardiovascular comorbidity, and blood loss of 500 mL or more were also associated with increased risk for mortality. Use of the robotic approach for general surgery can be achieved safely with low morbidity and mortality. Several risk factors have been identified as independent causes for higher morbidity and mortality. These can be used to identify patients at risk before and during the surgery and, in the future, to develop a scoring system for the use of robotic general surgery
Directory of Open Access Journals (Sweden)
Alma D. Agero
2016-11-01
Full Text Available This study explores the academe-industry partnership of Cebu Technological University Bachelor of Science in Hospitality Management and Bachelor of Science in Industrial Technology major in Food Preparation and Services courses, SY 2014-2015 to improve the quality of course offering. It takes on the feedback received from supervisors of 50 different hotels and restaurants of Cebu province, as well as the self-rating of 185 OJTs of the two courses as regard to OJTs' level of functional and science-based core competencies. This descriptive research utilizes Likert-type research-made survey questionnaire which was previously tested for validity and reliability. The findings revealed that industry supervisors evaluated the trainees as Competent in core competencies (Bartending, Bread and pastry products, Cookery, Customer services, Front office services, food and beverages as well as functional skills (Problem solving, Leadership, Communication, Independent work, Creativity, Negotiation, Teamwork, Time management and Initiative. However, they found the students need of strengthening their problem solving and communication skills. The researchers therefore developed an enhanced learning guide for the New Science GE course to address the gaps based on the industry feedback.
The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning
Energy Technology Data Exchange (ETDEWEB)
Caron, Sascha [Radboud Universiteit, Institute for Mathematics, Astro- and Particle Physics IMAPP, Nijmegen (Netherlands); Nikhef, Amsterdam (Netherlands); Kim, Jong Soo [UAM/CSIC, Instituto de Fisica Teorica, Madrid (Spain); Rolbiecki, Krzysztof [UAM/CSIC, Instituto de Fisica Teorica, Madrid (Spain); University of Warsaw, Faculty of Physics, Warsaw (Poland); Ruiz de Austri, Roberto [IFIC-UV/CSIC, Instituto de Fisica Corpuscular, Valencia (Spain); Stienen, Bob [Radboud Universiteit, Institute for Mathematics, Astro- and Particle Physics IMAPP, Nijmegen (Netherlands)
2017-04-15
A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets - each tested against 200 signal regions by ATLAS - have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/. (orig.)
The BSM-AI project: SUSY-AI-generalizing LHC limits on supersymmetry with machine learning
International Nuclear Information System (INIS)
Caron, Sascha; Kim, Jong Soo; Rolbiecki, Krzysztof; Ruiz de Austri, Roberto; Stienen, Bob
2017-01-01
A key research question at the Large Hadron Collider is the test of models of new physics. Testing if a particular parameter set of such a model is excluded by LHC data is a challenge: it requires time consuming generation of scattering events, simulation of the detector response, event reconstruction, cross section calculations and analysis code to test against several hundred signal regions defined by the ATLAS and CMS experiments. In the BSM-AI project we approach this challenge with a new idea. A machine learning tool is devised to predict within a fraction of a millisecond if a model is excluded or not directly from the model parameters. A first example is SUSY-AI, trained on the phenomenological supersymmetric standard model (pMSSM). About 300, 000 pMSSM model sets - each tested against 200 signal regions by ATLAS - have been used to train and validate SUSY-AI. The code is currently able to reproduce the ATLAS exclusion regions in 19 dimensions with an accuracy of at least 93%. It has been validated further within the constrained MSSM and the minimal natural supersymmetric model, again showing high accuracy. SUSY-AI and its future BSM derivatives will help to solve the problem of recasting LHC results for any model of new physics. SUSY-AI can be downloaded from http://susyai.hepforge.org/. An on-line interface to the program for quick testing purposes can be found at http://www.susy-ai.org/. (orig.)
Quitadamo, Ian J; Kurtz, Martha J
2007-01-01
Increasingly, national stakeholders express concern that U.S. college graduates cannot adequately solve problems and think critically. As a set of cognitive abilities, critical thinking skills provide students with tangible academic, personal, and professional benefits that may ultimately address these concerns. As an instructional method, writing has long been perceived as a way to improve critical thinking. In the current study, the researchers compared critical thinking performance of students who experienced a laboratory writing treatment with those who experienced traditional quiz-based laboratory in a general education biology course. The effects of writing were determined within the context of multiple covariables. Results indicated that the writing group significantly improved critical thinking skills whereas the non-writing group did not. Specifically, analysis and inference skills increased significantly in the writing group but not the non-writing group. Writing students also showed greater gains in evaluation skills; however, these were not significant. In addition to writing, prior critical thinking skill and instructor significantly affected critical thinking performance, whereas other covariables such as gender, ethnicity, and age were not significant. With improved critical thinking skill, general education biology students will be better prepared to solve problems as engaged and productive citizens.
Real-time traffic sign recognition based on a general purpose GPU and deep-learning.
Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran
2017-01-01
We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).
Mandal, Shyamapada; Santhi, B.; Sridhar, S.; Vinolia, K.; Swaminathan, P.
2017-06-01
In this paper, an online fault detection and classification method is proposed for thermocouples used in nuclear power plants. In the proposed method, the fault data are detected by the classification method, which classifies the fault data from the normal data. Deep belief network (DBN), a technique for deep learning, is applied to classify the fault data. The DBN has a multilayer feature extraction scheme, which is highly sensitive to a small variation of data. Since the classification method is unable to detect the faulty sensor; therefore, a technique is proposed to identify the faulty sensor from the fault data. Finally, the composite statistical hypothesis test, namely generalized likelihood ratio test, is applied to compute the fault pattern of the faulty sensor signal based on the magnitude of the fault. The performance of the proposed method is validated by field data obtained from thermocouple sensors of the fast breeder test reactor.
Allen, Emily Christine
Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being "[loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about
Towards General Evaluation of Intelligent Systems: Lessons Learned from Reproducing AIQ Test Results
Vadinský, Ondřej
2018-03-01
This paper attempts to replicate the results of evaluating several artificial agents using the Algorithmic Intelligence Quotient test originally reported by Legg and Veness. Three experiments were conducted: One using default settings, one in which the action space was varied and one in which the observation space was varied. While the performance of freq, Q0, Qλ, and HLQλ corresponded well with the original results, the resulting values differed, when using MC-AIXI. Varying the observation space seems to have no qualitative impact on the results as reported, while (contrary to the original results) varying the action space seems to have some impact. An analysis of the impact of modifying parameters of MC-AIXI on its performance in the default settings was carried out with the help of data mining techniques used to identifying highly performing configurations. Overall, the Algorithmic Intelligence Quotient test seems to be reliable, however as a general artificial intelligence evaluation method it has several limits. The test is dependent on the chosen reference machine and also sensitive to changes to its settings. It brings out some differences among agents, however, since they are limited in size, the test setting may not yet be sufficiently complex. A demanding parameter sweep is needed to thoroughly evaluate configurable agents that, together with the test format, further highlights computational requirements of an agent. These and other issues are discussed in the paper along with proposals suggesting how to alleviate them. An implementation of some of the proposals is also demonstrated.
Ghatty, Sundara L.
Over the past decade, there has been a dramatic rise in online delivery of higher education in the United States. Recent developments in web technology and access to the internet have led to a vast increase in online courses. For people who work during the day and whose complicated lives prevent them from taking courses on campus, online courses are the only alternatives by which they may achieve their goals in education. The laboratory courses are the major requirements for college and university students who want to pursue degree and certification programs in science. It is noted that there is a lack of laboratory courses in online physics courses. The present study addressed the effectiveness of a virtual science laboratory in physics instruction in terms of learning outcomes, attitudes, and self-efficacy of students in a Historically Black University College. The study included fifty-eight students (36 male and 22 female) of different science majors who were enrolled in a general physics laboratory course. They were divided into virtual and traditional groups. Three experiments were selected from the syllabus. The traditional group performed one experiment in a traditional laboratory, while the virtual group performed the same experiment in a virtual laboratory. For the second experiment, the use of laboratories by both groups was exchanged. Learner's Assessment Test (LAT), Attitudes Toward Physics Laboratories (ATPL), and Self-Efficacy Survey (SES) instruments were used. Additionally, quantitative methods such as an independent t-test, a paired t-test, and correlation statistics were used to analyze the data. The results of the first experiment indicated the learning outcomes were higher in the Virtual Laboratory than in the traditional laboratory, whereas there was no significant difference in learning outcomes with either type of lab instruction. However, significant self-efficacy gains were observed. Students expressed positive attitudes in terms of liking
Hsu, Liwei
2016-01-01
This study examines EFL (English as a foreign Language) teachers' technological pedagogical content knowledge (TPACK) and how such knowledge affects the adoption of mobile-assisted language learning (MALL). A total of 158 in-service Taiwanese English teachers were surveyed. Two frameworks were employed to examine latent constructs: TPACK and the…
Yao, Lihua; Schwarz, Richard D.
2006-01-01
Multidimensional item response theory (IRT) models have been proposed for better understanding the dimensional structure of data or to define diagnostic profiles of student learning. A compensatory multidimensional two-parameter partial credit model (M-2PPC) for constructed-response items is presented that is a generalization of those proposed to…
A 5-year perspective over robotic general surgery: indications, risk factors and learning curves.
Sgarbură, O; Tomulescu, V; Blajut, C; Popescu, I
2013-01-01
Robotic surgery has opened a new era in several specialties but the diffusion of medical innovation is slower indigestive surgery than in urology due to considerations related to cost and cost-efficiency. Studies often discuss the launching of the robotic program as well as the technical or clinical data related to specific procedures but there are very few articles evaluating already existing robotic programs. The aims of the present study are to evaluate the results of a five-year robotic program and to assess the evolution of indications in a center with expertise in a wide range of thoracic and abdominal robotic surgery. All consecutive robotic surgery cases performed in our center since the beginning of the program and prior to the 31st of December 2012 were included in this study, summing up to 734 cases throughout five years of experience in the field. Demographic, clinical, surgical and postoperative variables were recorded and analyzed.Comparative parametric and non-parametric tests, univariate and multivariate analyses and CUSUM analysis were performed. In this group, the average age was 50,31 years. There were 60,9% females and 39,1% males. 55,3% of all interventions were indicated for oncological disease. 36% of all cases of either benign or malignant etiology were pelvic conditions whilst 15,4% were esogastric conditions. Conversion was performed in 18 cases (2,45%). Mean operative time was 179,4Â+-86,06 min. Mean docking time was 11,16Â+-2,82 min.The mean hospital length of stay was 8,54 (Â+-5,1) days. There were 26,2% complications of all Clavien subtypes but important complications (Clavien III-V) only represented 6,2%.Male sex, age over 65 years old, oncological cases and robotic suturing were identified as risk factors for unfavorable outcomes. The present data support the feasibility of different and complex procedures in a general surgery department as well as the ascending evolution of a well-designed and well-conducted robotic program. From
Azer, Nader; Shi, Xinzhe; de Gara, Chris; Karmali, Shahzeer; Birch, Daniel W
2014-04-01
The increased use of information technology supports a resident- centred educational approach that promotes autonomy, flexibility and time management and helps residents to assess their competence, promoting self-awareness. We established a web-based e-learning tool to introduce general surgery residents to bariatric surgery and evaluate them to determine the most appropriate implementation strategy for Internet-based interactive modules (iBIM) in surgical teaching. Usernames and passwords were assigned to general surgery residents at the University of Alberta. They were directed to the Obesity101 website and prompted to complete a multiple-choice precourse test. Afterwards, they were able to access the interactive modules. Residents could review the course material as often as they wanted before completing a multiple-choice postcourse test and exit survey. We used paired t tests to assess the difference between pre- and postcourse scores. Out of 34 residents who agreed to participate in the project, 12 completed the project (35.3%). For these 12 residents, the precourse mean score was 50 ± 17.3 and the postcourse mean score was 67 ± 14 (p = 0.020). Most residents who participated in this study recommended using the iBIMs as a study tool for bariatric surgery. Course evaluation scores suggest this novel approach was successful in transferring knowledge to surgical trainees. Further development of this tool and assessment of implementation strategies will determine how iBIM in bariatric surgery may be integrated into the curriculum.
Wenzel, Thomas J
2006-01-01
The laboratory component of a first-semester general chemistry course for science majors is described. The laboratory involves a semester-long project undertaken in a small-group format. Students are asked to examine whether plants grown in soil contaminated with lead take up more lead than those grown in uncontaminated soil. They are also asked to examine whether the acidity of the rainwater affects the amount of lead taken up by the plants. Groups are then given considerable independence in the design and implementation of the experiment. Once the seeds are planted, which takes about 4 wk into the term, several shorter experiments are integrated in before it is time to harvest and analyze the plants. The use of a project and small working groups allows for the development of a broader range of learning outcomes than occurs in a "traditional" general chemistry laboratory. The nature of these outcomes and some of the student responses to the laboratory experience are described. This particular project also works well at demonstrating the connections among chemistry, biology, geology, and environmental studies.
Grant, Andrew J; Vermunt, Jan D; Kinnersley, Paul; Houston, Helen
2007-03-30
Portfolio learning enables students to collect evidence of their learning. Component tasks making up a portfolio can be devised that relate directly to intended learning outcomes. Reflective tasks can stimulate students to recognise their own learning needs. Assessment of portfolios using a rating scale relating to intended learning outcomes offers high content validity. This study evaluated a reflective portfolio used during a final-year attachment in general practice (family medicine). Students were asked to evaluate the portfolio (which used significant event analysis as a basis for reflection) as a learning tool. The validity and reliability of the portfolio as an assessment tool were also measured. 81 final-year medical students completed reflective significant event analyses as part of a portfolio created during a three-week attachment (clerkship) in general practice (family medicine). As well as two reflective significant event analyses each portfolio contained an audit and a health needs assessment. Portfolios were marked three times; by the student's GP teacher, the course organiser and by another teacher in the university department of general practice. Inter-rater reliability between pairs of markers was calculated. A questionnaire enabled the students' experience of portfolio learning to be determined. Benefits to learning from reflective learning were limited. Students said that they thought more about the patients they wrote up in significant event analyses but information as to the nature and effect of this was not forthcoming. Moderate inter-rater reliability (Spearman's Rho .65) was found between pairs of departmental raters dealing with larger numbers (20-60) of portfolios. Inter-rater reliability of marking involving GP tutors who only marked 1-3 portfolios was very low. Students rated highly their mentoring relationship with their GP teacher but found the portfolio tasks time-consuming. The inter-rater reliability observed in this study should
AUTHOR|(CDS)2243922; Ekelin, Svea Magdalena; Lund-Jensen, Bengt; Christiansen, Iben
2017-08-15
In 2016, the ATLAS experiment at CERN released data from 100 trillion proton-proton collisions to the general public. In connection to this release the ATLAS Outreach group has developed several tools for visualizing and analyzing the data, one of which is a Histogram analyzer. The focus of this project is to bridge the gap between the general public's knowledge in physics and what is needed to use this Histogram analyzer. The project consists of both the development and an evaluation of a learning resource that explains experimental particle physics for a general public audience. The learning resource is a website making use of analogies and two perspectives on learning: Variation Theory and Cognitive Load Theory. The evaluation of the website was done using a survey with 10 respondents and it focused on whether analogies and the perspectives on learning helped their understanding. In general the respondents found the analogies to be helpful for their learning, and to some degree they found the explanations ...
Directory of Open Access Journals (Sweden)
Minna Kumpu
2016-10-01
Full Text Available Background: Novel research training approaches are needed in global health, particularly in sub-Saharan African universities, to support strengthening of health systems and services. Blended learning (BL, combining face-to-face teaching with computer-based technologies, is also an accessible and flexible education method for teaching global health and related topics. When organised as inter-institutional collaboration, BL also has potential for sharing teaching resources. However, there is insufficient data on the costs of BL in higher education. Objective: Our goal was to evaluate the total provider costs of BL in teaching health research methods in a three-university collaboration. Design: A retrospective evaluation was performed on a BL course on randomised controlled trials, which was led by Stellenbosch University (SU in South Africa and joined by Swedish and Ugandan universities. For all three universities, the costs of the BL course were evaluated using activity-based costing with an ingredients approach. For SU, the costs of the same course delivered with a classroom learning (CL approach were also estimated. The learning outcomes of both approaches were explored using course grades as an intermediate outcome measure. Results: In this contextually bound pilot evaluation, BL had substantially higher costs than the traditional CL approach in South Africa, even when average per-site or per-student costs were considered. Staff costs were the major cost driver in both approaches, but total staff costs were three times higher for the BL course at SU. This implies that inter-institutional BL can be more time consuming, for example, due to use of new technologies. Explorative findings indicated that there was little difference in students’ learning outcomes. Conclusions: The total provider costs of the inter-institutional BL course were higher than the CL course at SU. Long-term economic evaluations of BL with societal perspective are
Kumpu, Minna; Atkins, Salla; Zwarenstein, Merrick; Nkonki, Lungiswa
2016-01-01
Novel research training approaches are needed in global health, particularly in sub-Saharan African universities, to support strengthening of health systems and services. Blended learning (BL), combining face-to-face teaching with computer-based technologies, is also an accessible and flexible education method for teaching global health and related topics. When organised as inter-institutional collaboration, BL also has potential for sharing teaching resources. However, there is insufficient data on the costs of BL in higher education. Our goal was to evaluate the total provider costs of BL in teaching health research methods in a three-university collaboration. A retrospective evaluation was performed on a BL course on randomised controlled trials, which was led by Stellenbosch University (SU) in South Africa and joined by Swedish and Ugandan universities. For all three universities, the costs of the BL course were evaluated using activity-based costing with an ingredients approach. For SU, the costs of the same course delivered with a classroom learning (CL) approach were also estimated. The learning outcomes of both approaches were explored using course grades as an intermediate outcome measure. In this contextually bound pilot evaluation, BL had substantially higher costs than the traditional CL approach in South Africa, even when average per-site or per-student costs were considered. Staff costs were the major cost driver in both approaches, but total staff costs were three times higher for the BL course at SU. This implies that inter-institutional BL can be more time consuming, for example, due to use of new technologies. Explorative findings indicated that there was little difference in students' learning outcomes. The total provider costs of the inter-institutional BL course were higher than the CL course at SU. Long-term economic evaluations of BL with societal perspective are warranted before conclusions on full costs and consequences of BL in teaching
Elements of partial differential equations
Sneddon, Ian Naismith
1957-01-01
Geared toward students of applied rather than pure mathematics, this volume introduces elements of partial differential equations. Its focus is primarily upon finding solutions to particular equations rather than general theory.Topics include ordinary differential equations in more than two variables, partial differential equations of the first and second orders, Laplace's equation, the wave equation, and the diffusion equation. A helpful Appendix offers information on systems of surfaces, and solutions to the odd-numbered problems appear at the end of the book. Readers pursuing independent st
Bernstein, Susan D; Horowitz, Allan J; Man, Martin; Wu, Hongyu; Foran, Denise; Vena, Donald A; Collie, Damon; Matthews, Abigail G; Curro, Frederick A; Thompson, Van P; Craig, Ronald G
2012-05-01
The authors undertook a study involving members of a dental practice-based research network to determine the outcome and factors associated with success and failure of endodontic therapy. Members in participating practices (practitioner-investigators [P-Is]) invited the enrollment of all patients seeking treatment in the practice who had undergone primary endodontic therapy and restoration in a permanent tooth three to five years previously. If a patient had more than one tooth so treated, the P-I selected as the index tooth the tooth treated earliest during the three- to five-year period. The authors excluded from the study any teeth that served as abutments for removable partial dentures or overdentures, third molars and teeth undergoing active orthodontic endodontic therapy. The primary outcome was retention of the index tooth. Secondary outcomes, in addition to extraction, that defined failure included clinical or radiographic evidence (or both) of periapical pathosis, endodontic retreatment or pain on percussion. P-Is in 64 network practices enrolled 1,312 patients with a mean (standard deviation) time to follow-up of 3.9 (0.6) years. During that period, 3.3 percent of the index teeth were extracted, 2.2 percent underwent retreatment, 3.6 percent had pain on percussion and 10.6 percent had periapical radiolucencies for a combined failure rate of 19.1 percent. The presence of preoperative periapical radiolucency with a diagnosis of either irreversible pulpitis or necrotic pulp was associated with failure after multivariate analysis, as were multiple canals, male sex and Hispanic/Latino ethnicity. These results suggest that failure rates for endodontic therapy are higher than previously reported in general practices, according to results of studies based on dental insurance claims data. The results of this study can help guide the practitioner in deciding the most appropriate course of therapy for teeth with irreversible pulpitis, necrotic pulp or periapical
Partial rectangular metric spaces and fixed point theorems.
Shukla, Satish
2014-01-01
The purpose of this paper is to introduce the concept of partial rectangular metric spaces as a generalization of rectangular metric and partial metric spaces. Some properties of partial rectangular metric spaces and some fixed point results for quasitype contraction in partial rectangular metric spaces are proved. Some examples are given to illustrate the observed results.
Vranish, John M. (Inventor)
2010-01-01
A partial gear bearing including an upper half, comprising peak partial teeth, and a lower, or bottom, half, comprising valley partial teeth. The upper half also has an integrated roller section between each of the peak partial teeth with a radius equal to the gear pitch radius of the radially outwardly extending peak partial teeth. Conversely, the lower half has an integrated roller section between each of the valley half teeth with a radius also equal to the gear pitch radius of the peak partial teeth. The valley partial teeth extend radially inwardly from its roller section. The peak and valley partial teeth are exactly out of phase with each other, as are the roller sections of the upper and lower halves. Essentially, the end roller bearing of the typical gear bearing has been integrated into the normal gear tooth pattern.
Ferrarese, Alessia; Gentile, Valentina; Bindi, Marco; Rivelli, Matteo; Cumbo, Jacopo; Solej, Mario; Enrico, Stefano; Martino, Valter
2016-01-01
A well-designed learning curve is essential for the acquisition of laparoscopic skills: but, are there risk factors that can derail the surgical method? From a review of the current literature on the learning curve in laparoscopic surgery, we identified learning curve components in video laparoscopic cholecystectomy; we suggest a learning curve model that can be applied to assess the progress of general surgical residents as they learn and master the stages of video laparoscopic cholecystectomy regardless of type of patient. Electronic databases were interrogated to better define the terms "surgeon", "specialized surgeon", and "specialist surgeon"; we surveyed the literature on surgical residency programs outside Italy to identify learning curve components, influential factors, the importance of tutoring, and the role of reference centers in residency education in surgery. From the definition of acceptable error, self-efficacy, and error classification, we devised a learning curve model that may be applied to training surgical residents in video laparoscopic cholecystectomy. Based on the criteria culled from the literature, the three surgeon categories (general, specialized, and specialist) are distinguished by years of experience, case volume, and error rate; the patients were distinguished for years and characteristics. The training model was constructed as a series of key learning steps in video laparoscopic cholecystectomy. Potential errors were identified and the difficulty of each step was graded using operation-specific characteristics. On completion of each procedure, error checklist scores on procedure-specific performance are tallied to track the learning curve and obtain performance indices of measurement that chart the trainee's progress. The concept of the learning curve in general surgery is disputed. The use of learning steps may enable the resident surgical trainee to acquire video laparoscopic cholecystectomy skills proportional to the instructor
Kantarci, T.
2012-01-01
The five essays in this dissertation address a range of topics in the micro-economic literature on partial retirement. The focus is on the labor market behavior of older age groups. The essays examine the economic and non-economic determinants of partial retirement behavior, the effect of partial
Wilson, Kenesha; Copeland-Solas, Eddia; Guthrie-Dixon, Natalie
2016-01-01
Mind mapping was introduced as a culturally relevant pedagogy aimed at enhancing the teaching and learning experience in a general education, Environmental Science class for mostly Emirati English Language Learners (ELL). Anecdotal evidence suggests that the students are very artistic and visual and enjoy group-based activities. It was decided to…
Directory of Open Access Journals (Sweden)
Luis Emilio Caro Betancourt
2008-09-01
Full Text Available This article approaches the theoretical referents that sustain the professional pedagogical behavior of the Entire General Professor of Secondary School, using computer science in the teaching learning process. Taking into account the introducti on of the scientific and technical developments (Computer science in education and the professional's role starting from the demands of the conceived model for Secondary School Education.
Chan, Julia Y. K.; Bauer, Christopher F.
2015-01-01
This study investigated exam achievement and affective characteristics of students in general chemistry in a fully-randomized experimental design, contrasting Peer-Led Team Learning (PLTL) participation with a control group balanced for time-on-task and study activity. This study population included two independent first-semester courses with…
Directory of Open Access Journals (Sweden)
Watson Tony
2009-04-01
Full Text Available Abstract Background Spectrophotometric intracutaneous analysis (SIAscopy™ is a multispectral imaging technique that is used to identify 'suspicious' (i.e. potentially malignant pigmented skin lesions for further investigation. The MoleMate™ system is a hand-held scanner that captures SIAscopy™ images that are then classified by the clinician using a computerized diagnostic algorithm designed for the primary health care setting. The objectives of this study were to test the effectiveness of a computer program designed to train health care workers to identify the diagnostic features of SIAscopy™ images and compare the results of a group of Australian and a group of English general practitioners (GPs. Methods Thirty GPs recruited from the Perth (Western Australia metropolitan area completed the training program at a workshop held in March 2008. The accuracy and speed of their pre- and post-test scores were then compared with those of a group of 18 GPs (including 10 GP registrars who completed a similar program at two workshops held in Cambridge (U.K. in March and April, 2007. Results The median test score of the Australian GPs improved from 79.5% to 86.5% (median increase 5.5%; p Conclusion Most of the SIAscopy™ features can be learnt to a reasonable degree of accuracy with this brief computer training program. Although the Australian GPs scored higher in the pre-test, both groups had similar levels of accuracy and speed in interpreting the SIAscopy™ features after completing the program. Scores were not affected by previous dermoscopy experience or dermatology training, which suggests that the MoleMate™ system is relatively easy to learn.
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Leila Roshangar
2014-05-01
Full Text Available Introduction: The basic medical sciences section requires 2.5 years in the medical education curriculum. Practical courses complement theoretical knowledge in this period to improve their appreciation. Despite spending lots of disbursement and time, this period’s efficacy is not clearly known. Methods: One hundred thirty-three General Practitioner (GP students have been included in this descriptive cross-sectional study and were asked by questionnaire about the positive impact of practical courses on learning theoretical knowledge. Data were analyzed by descriptive statistics. Result: The agreement in “Practical Head and Neck Anatomy” was 40.91% ± 29.45, in “Practical Trunk Anatomy” was 63.62% ± 2.32 and in “Practical Anatomy of Extremities” was 56.16% ± 2.57. In “Practical Histology”, agreement was 69.50%±2.19; “Practical Biophysics” was 45.97%±2.25, “Practical Physiology” 61.75%±2.17; “Practical Biochemistry” 36.28%±2.42; “Practical Pathology” 59.80%±2.53; “Practical Immunology” 56.25%±26.40; “Practical Microbiology and Virology” 60.39%±2.27 and “Practical Mycology and Parasitology” 68.2%± 2.16.Conclusion: GP students in Tabriz University of Medical Sciences are not optimistic about the applicability of practical courses of basic medical sciences lessons.
Hilbert, Kevin; Lueken, Ulrike; Muehlhan, Markus; Beesdo-Baum, Katja
2017-03-01
Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral data from a sample of GAD, MD and healthy subjects to differentiate subjects with a disorder from healthy subjects (case-classification) and to differentiate GAD from MD (disorder-classification). Subjects with GAD ( n = 19), MD without GAD ( n = 14), and healthy comparison subjects ( n = 24) were included. The sample was matched regarding age, sex, handedness and education and free of psychopharmacological medication. Binary support vector machines were used within a nested leave-one-out cross-validation framework. Clinical questionnaires, cortisol release, gray matter (GM), and white matter (WM) volumes were used as input data separately and in combination. Questionnaire data were well-suited for case-classification but not disorder-classification (accuracies: 96.40%, p .22). The opposite pattern was found for imaging data (case-classification GM/WM: 58.71%, p = .09/43.18%, p > .66; disorder-classification GM/WM: 68.05%, p = .034/58.27%, p > .15) and for cortisol data (38.02%, p = .84; 74.60%, p = .009). All data combined achieved 90.10% accuracy ( p < .001) for case-classification and 67.46% accuracy ( p = .0268) for disorder-classification. In line with previous evidence, classification of GAD was difficult using clinical questionnaire data alone. Particularly cortisol and GM volume data were able to provide incremental value for the classification of GAD. Findings suggest that neurobiological biomarkers are a useful target for further research to delineate their potential contribution to diagnostic processes.
Matching games with partial information
Laureti, Paolo; Zhang, Yi-Cheng
2003-06-01
We analyze different ways of pairing agents in a bipartite matching problem, with regard to its scaling properties and to the distribution of individual “satisfactions”. Then we explore the role of partial information and bounded rationality in a generalized Marriage Problem, comparing the benefits obtained by self-searching and by a matchmaker. Finally we propose a modified matching game intended to mimic the way consumers’ information makes firms to enhance the quality of their products in a competitive market.
DEFF Research Database (Denmark)
Waldorff, Frans Boch; Steenstrup, Annette Plesner; Nielsen, Bente
2008-01-01
predictors for use of the e-learning programme. RESULTS: In the study period, a total of 192 different GPs (5.3%) were identified as users, and 17% (32) had at least one re-logon. Among responders at first login most have learnt about the e-learning programme from written material (41%) or from the internet...
Partial differential equations for scientists and engineers
Farlow, Stanley J
1993-01-01
Most physical phenomena, whether in the domain of fluid dynamics, electricity, magnetism, mechanics, optics, or heat flow, can be described in general by partial differential equations. Indeed, such equations are crucial to mathematical physics. Although simplifications can be made that reduce these equations to ordinary differential equations, nevertheless the complete description of physical systems resides in the general area of partial differential equations.This highly useful text shows the reader how to formulate a partial differential equation from the physical problem (constructing th
Directory of Open Access Journals (Sweden)
Ольга Юрьевна Заславская
2018-12-01
Full Text Available The article considers the influence of the development of technical means of teaching on the effectiveness of educational and methodical resources. Modern opportunities of information and communication technologies allow creating electronic educational resources that represent educational information that automates the learning process, provide information assistance, if necessary, collect and process statistical information on the degree of development of the content of the school material by schoolchildren, set an individual trajectory of learning, and so on. The main principle of data organization is the division of the training course into separate sections on the thematic elements and components of the learning process. General regularities include laws that encompass the entire didactic system, and in specific (particular cases, those whose actions extend to a separate component (aspect of the system. From the standpoint of the existence of three types of electronic training modules in the aggregate content of the electronic learning resource - information, control and module of practical classes - the principles of the formation of the electronic learning resource, in our opinion, should regulate all these components. Each of the certain principles is considered in the groups: scientific orientation, methodological orientation, systemic nature, accounting of interdisciplinary connections, fundamentalization, systematic and dosage sequence, rational use of study time, accessibility, minimization, operationalization of goals, unified identification diagnosis.
Chein, Jason M; Schneider, Walter
2005-12-01
Functional magnetic resonance imaging and a meta-analysis of prior neuroimaging studies were used to characterize cortical changes resulting from extensive practice and to evaluate a dual-processing account of the neural mechanisms underlying human learning. Three core predictions of the dual processing theory are evaluated: 1) that practice elicits generalized reductions in regional activity by reducing the load on the cognitive control mechanisms that scaffold early learning; 2) that these control mechanisms are domain-general; and 3) that no separate processing pathway emerges as skill develops. To evaluate these predictions, a meta-analysis of prior neuroimaging studies and a within-subjects fMRI experiment contrasting unpracticed to practiced performance in a paired-associate task were conducted. The principal effect of practice was found to be a reduction in the extent and magnitude of activity in a cortical network spanning bilateral dorsal prefrontal, left ventral prefrontal, medial frontal (anterior cingulate), left insular, bilateral parietal, and occipito-temporal (fusiform) areas. These activity reductions are shown to occur in common regions across prior neuroimaging studies and for both verbal and nonverbal paired-associate learning in the present fMRI experiment. The implicated network of brain regions is interpreted as a domain-general system engaged specifically to support novice, but not practiced, performance.
Maldeghem, Hendrik
1998-01-01
This book is intended to be an introduction to the fascinating theory ofgeneralized polygons for both the graduate student and the specialized researcher in the field. It gathers together a lot of basic properties (some of which are usually referred to in research papers as belonging to folklore) and very recent and sometimes deep results. I have chosen a fairly strict geometrical approach, which requires some knowledge of basic projective geometry. Yet, it enables one to prove some typically group-theoretical results such as the determination of the automorphism groups of certain Moufang polygons. As such, some basic group-theoretical knowledge is required of the reader. The notion of a generalized polygon is a relatively recent one. But it is one of the most important concepts in incidence geometry. Generalized polygons are the building bricks of Tits buildings. They are the prototypes and precursors of more general geometries such as partial geometries, partial quadrangles, semi-partial ge ometries, near...
Hyperbolic partial differential equations
Witten, Matthew
1986-01-01
Hyperbolic Partial Differential Equations III is a refereed journal issue that explores the applications, theory, and/or applied methods related to hyperbolic partial differential equations, or problems arising out of hyperbolic partial differential equations, in any area of research. This journal issue is interested in all types of articles in terms of review, mini-monograph, standard study, or short communication. Some studies presented in this journal include discretization of ideal fluid dynamics in the Eulerian representation; a Riemann problem in gas dynamics with bifurcation; periodic M
Successful removable partial dentures.
Lynch, Christopher D
2012-03-01
Removable partial dentures (RPDs) remain a mainstay of prosthodontic care for partially dentate patients. Appropriately designed, they can restore masticatory efficiency, improve aesthetics and speech, and help secure overall oral health. However, challenges remain in providing such treatments, including maintaining adequate plaque control, achieving adequate retention, and facilitating patient tolerance. The aim of this paper is to review the successful provision of RPDs. Removable partial dentures are a successful form of treatment for replacing missing teeth, and can be successfully provided with appropriate design and fabrication concepts in mind.
Beginning partial differential equations
O'Neil, Peter V
2011-01-01
A rigorous, yet accessible, introduction to partial differential equations-updated in a valuable new edition Beginning Partial Differential Equations, Second Edition provides a comprehensive introduction to partial differential equations (PDEs) with a special focus on the significance of characteristics, solutions by Fourier series, integrals and transforms, properties and physical interpretations of solutions, and a transition to the modern function space approach to PDEs. With its breadth of coverage, this new edition continues to present a broad introduction to the field, while also addres
Ide, Jaime S; Nedic, Sanja; Wong, Kin F; Strey, Shmuel L; Lawson, Elizabeth A; Dickerson, Bradford C; Wald, Lawrence L; La Camera, Giancarlo; Mujica-Parodi, Lilianne R
2018-07-01
Oxytocin (OT) is an endogenous neuropeptide that, while originally thought to promote trust, has more recently been found to be context-dependent. Here we extend experimental paradigms previously restricted to de novo decision-to-trust, to a more realistic environment in which social relationships evolve in response to iterative feedback over twenty interactions. In a randomized, double blind, placebo-controlled within-subject/crossover experiment of human adult males, we investigated the effects of a single dose of intranasal OT (40 IU) on Bayesian expectation updating and reinforcement learning within a social context, with associated brain circuit dynamics. Subjects participated in a neuroeconomic task (Iterative Trust Game) designed to probe iterative social learning while their brains were scanned using ultra-high field (7T) fMRI. We modeled each subject's behavior using Bayesian updating of belief-states ("willingness to trust") as well as canonical measures of reinforcement learning (learning rate, inverse temperature). Behavioral trajectories were then used as regressors within fMRI activation and connectivity analyses to identify corresponding brain network functionality affected by OT. Behaviorally, OT reduced feedback learning, without bias with respect to positive versus negative reward. Neurobiologically, reduced learning under OT was associated with muted communication between three key nodes within the reward circuit: the orbitofrontal cortex, amygdala, and lateral (limbic) habenula. Our data suggest that OT, rather than inspiring feelings of generosity, instead attenuates the brain's encoding of prediction error and therefore its ability to modulate pre-existing beliefs. This effect may underlie OT's putative role in promoting what has typically been reported as 'unjustified trust' in the face of information that suggests likely betrayal, while also resolving apparent contradictions with regard to OT's context-dependent behavioral effects. Copyright
Hu, Danqing; Flick, Randall P; Zaccariello, Michael J; Colligan, Robert C; Katusic, Slavica K; Schroeder, Darrell R; Hanson, Andrew C; Buenvenida, Shonie L; Gleich, Stephen J; Wilder, Robert T; Sprung, Juraj; Warner, David O
2017-08-01
Exposure of young animals to general anesthesia causes neurodegeneration and lasting behavioral abnormalities; whether these findings translate to children remains unclear. This study used a population-based birth cohort to test the hypothesis that multiple, but not single, exposures to procedures requiring general anesthesia before age 3 yr are associated with adverse neurodevelopmental outcomes. A retrospective study cohort was assembled from children born in Olmsted County, Minnesota, from 1996 to 2000 (inclusive). Propensity matching selected children exposed and not exposed to general anesthesia before age 3 yr. Outcomes ascertained via medical and school records included learning disabilities, attention-deficit/hyperactivity disorder, and group-administered ability and achievement tests. Analysis methods included proportional hazard regression models and mixed linear models. For the 116 multiply exposed, 457 singly exposed, and 463 unexposed children analyzed, multiple, but not single, exposures were associated with an increased frequency of both learning disabilities and attention-deficit/hyperactivity disorder (hazard ratio for learning disabilities = 2.17 [95% CI, 1.32 to 3.59], unexposed as reference). Multiple exposures were associated with decreases in both cognitive ability and academic achievement. Single exposures were associated with modest decreases in reading and language achievement but not cognitive ability. These findings in children anesthetized with modern techniques largely confirm those found in an older birth cohort and provide additional evidence that children with multiple exposures are more likely to develop adverse outcomes related to learning and attention. Although a robust association was observed, these data do not determine whether anesthesia per se is causal.
Nobel, Michele Mcmahon
2005-07-01
This study investigated the effects of classwide peer tutoring (CWPT) on the acquisition, maintenance, and generalization of science vocabulary words and definitions. Participants were 14 seventh grade students at-risk for failure in a general education science course; 3 students had learning disabilities and 2 had a communication disorder. CWPT was conducted daily for 20 minutes during the last period of the school day. Procedures for CWPT were consistent with the Ohio State University CWPT model. Students were engaged in dyadic, reciprocal tutoring. Tutors presented word cards to tutees to identify the word and definition. Tutors praised correct responses and used a correction procedure for incorrect responses. After practicing their vocabulary words, students completed a daily testing procedure and recorded and plotted data. Many of the study's findings are consistent with previous studies using CWPT to teach word identification. Results of this study indicate a functional relationship between CWPT and acquisition of science vocabulary. All students were able to acquire words and definitions. Results for maintenance and generalization varied. When acquisition criterion was changed, maintenance and generalization scores increased for some students, while other students remained consistently high. All students reported that they enjoyed CWPT, and all but student stated it helped them learn science vocabulary.
Partial Deconvolution with Inaccurate Blur Kernel.
Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei
2017-10-17
Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning
Partial knee replacement - slideshow
... page: //medlineplus.gov/ency/presentations/100225.htm Partial knee replacement - series—Normal anatomy To use the sharing ... A.M. Editorial team. Related MedlinePlus Health Topics Knee Replacement A.D.A.M., Inc. is accredited ...
Beginning partial differential equations
O'Neil, Peter V
2014-01-01
A broad introduction to PDEs with an emphasis on specialized topics and applications occurring in a variety of fields Featuring a thoroughly revised presentation of topics, Beginning Partial Differential Equations, Third Edition provides a challenging, yet accessible,combination of techniques, applications, and introductory theory on the subjectof partial differential equations. The new edition offers nonstandard coverageon material including Burger's equation, the telegraph equation, damped wavemotion, and the use of characteristics to solve nonhomogeneous problems. The Third Edition is or
Pavesi, Eloisa; Heldt, Scott A.; Fletcher, Max L.
2013-01-01
Experience-induced changes associated with odor learning are mediated by a number of signaling molecules, including nitric oxide (NO), which is predominantly synthesized by neuronal nitric oxide synthase (nNOS) in the brain. In the current study, we investigated the role of nNOS in the acquisition and retention of conditioned olfactory fear. Mice…
Henry, Renee Monica
2017-01-01
Reported here is a study of an interactive component to General Chemistry I and General Chemistry II where a new pedagogy for taking notes in class was developed. These notes, called key word created class notes, prompted students to locate information using the Internet guided by a key word. Reference Web sites were added to a next generation of…
Synchronizing Strategies under Partial Observability
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Laursen, Simon; Srba, Jiri
2014-01-01
Embedded devices usually share only partial information about their current configurations as the communication bandwidth can be restricted. Despite this, we may wish to bring a failed device into a given predetermined configuration. This problem, also known as resetting or synchronizing words, has...... been intensively studied for systems that do not provide any information about their configurations. In order to capture more general scenarios, we extend the existing theory of synchronizing words to synchronizing strategies, and study the synchronization, short-synchronization and subset...
Chang, Hui-Chin; Wang, Ning-Yen; Ko, Wen-Ru; Yu, You-Tsz; Lin, Long-Yau; Tsai, Hui-Fang
2017-06-01
The effective education method of medico-jurisprudence for medical students is unclear. The study was designed to evaluate the effectiveness of problem-based learning (PBL) model teaching medico-jurisprudence in clinical setting on General Law Knowledge (GLK) for medical students. Senior medical students attending either campus-based law curriculum or Obstetrics/Gynecology (Ob/Gyn) clinical setting morning meeting from February to July in 2015 were enrolled. A validated questionnaire comprising 45 questions were completed before and after the law education. The interns attending clinical setting small group improvisation medico-jurisprudence problem-based learning education had significantly better GLK scores than the GLK of students attending campus-based medical law education course after the period studied. PBL teaching model of medico-jurisprudence is an ideal alternative pedagogy model in medical law education curriculum. Copyright © 2017. Published by Elsevier B.V.
Directory of Open Access Journals (Sweden)
Mohsen Laabidi
2014-01-01
Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.
Voorspoels, Wouter; Navarro, Daniel J; Perfors, Amy; Ransom, Keith; Storms, Gert
2015-09-01
A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sampled randomly from the environment. Copyright © 2015 Elsevier Inc. All rights reserved.
Partial differential equations
Evans, Lawrence C
2010-01-01
This text gives a comprehensive survey of modern techniques in the theoretical study of partial differential equations (PDEs) with particular emphasis on nonlinear equations. The exposition is divided into three parts: representation formulas for solutions; theory for linear partial differential equations; and theory for nonlinear partial differential equations. Included are complete treatments of the method of characteristics; energy methods within Sobolev spaces; regularity for second-order elliptic, parabolic, and hyperbolic equations; maximum principles; the multidimensional calculus of variations; viscosity solutions of Hamilton-Jacobi equations; shock waves and entropy criteria for conservation laws; and, much more.The author summarizes the relevant mathematics required to understand current research in PDEs, especially nonlinear PDEs. While he has reworked and simplified much of the classical theory (particularly the method of characteristics), he primarily emphasizes the modern interplay between funct...
O'Reilly-de Brún, Mary; MacFarlane, Anne; de Brún, Tomas; Okonkwo, Ekaterina; Bonsenge Bokanga, Jean Samuel; Manuela De Almeida Silva, Maria; Ogbebor, Florence; Mierzejewska, Aga; Nnadi, Lovina; van den Muijsenbergh, Maria; van Weel-Baumgarten, Evelyn; van Weel, Chris
2015-09-21
The aim of this research was to involve migrants and other key stakeholders in a participatory dialogue to develop a guideline for enhancing communication in cross-cultural general practice consultations. In this paper, we focus on findings about the use of formal versus informal interpreters because dialogues about these issues emerged as central to the identification of recommendations for best practice. This qualitative case study involved a Participatory Learning and Action (PLA) research methodology. The sample comprised 80 stakeholders: 51 from migrant communities; 15 general practitioners (GPs) and general practice staff; 7 established migrants as peer researchers; 5 formal, trained interpreters; and 2 service planners from the national health authority. Galway, Ireland. There was 100% consensus across stakeholder groups that while informal interpreters have uses for migrants and general practice staff, they are not considered acceptable as best practice. There was also 100% consensus that formal interpreters who are trained and working as per a professional code of practice are acceptable as best practice. Policymakers and service planners need to work in partnership with service providers and migrants to progress the implementation of professional, trained interpreters as a routine way of working in general practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Optimization of partial search
International Nuclear Information System (INIS)
Korepin, Vladimir E
2005-01-01
A quantum Grover search algorithm can find a target item in a database faster than any classical algorithm. One can trade accuracy for speed and find a part of the database (a block) containing the target item even faster; this is partial search. A partial search algorithm was recently suggested by Grover and Radhakrishnan. Here we optimize it. Efficiency of the search algorithm is measured by the number of queries to the oracle. The author suggests a new version of the Grover-Radhakrishnan algorithm which uses a minimal number of such queries. The algorithm can run on the same hardware that is used for the usual Grover algorithm. (letter to the editor)
Auxiliary partial liver transplantation
C.B. Reuvers (Cornelis Bastiaan)
1986-01-01
textabstractIn this thesis studies on auxiliary partial liver transplantation in the dog and the pig are reported. The motive to perform this study was the fact that patients with acute hepatic failure or end-stage chronic liver disease are often considered to form too great a risk for successful
DEFF Research Database (Denmark)
Andersen, Marie Louise Max; Hougaard, Philip; Pörksen, Sven
2014-01-01
OBJECTIVE: To validate the partial remission (PR) definition based on insulin dose-adjusted HbA1c (IDAA1c). SUBJECTS AND METHODS: The IDAA1c was developed using data in 251 children from the European Hvidoere cohort. For validation, 129 children from a Danish cohort were followed from the onset...
Fundamental partial compositeness
DEFF Research Database (Denmark)
Sannino, Francesco; Strumia, Alessandro; Tesi, Andrea
2016-01-01
We construct renormalizable Standard Model extensions, valid up to the Planck scale, that give a composite Higgs from a new fundamental strong force acting on fermions and scalars. Yukawa interactions of these particles with Standard Model fermions realize the partial compositeness scenario. Unde...
Fernandez, R.; Deveaux, V.
2010-01-01
We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).
Partially Hidden Markov Models
DEFF Research Database (Denmark)
Forchhammer, Søren Otto; Rissanen, Jorma
1996-01-01
Partially Hidden Markov Models (PHMM) are introduced. They differ from the ordinary HMM's in that both the transition probabilities of the hidden states and the output probabilities are conditioned on past observations. As an illustration they are applied to black and white image compression where...
W. van der Hoek (Wiebe); J.O.M. Jaspars; E. Thijsse
1995-01-01
textabstractWe propose an epistemic logic in which knowledge is fully introspective and implies truth, although truth need not imply epistemic possibility. The logic is presented in sequential format and is interpreted in a natural class of partial models, called balloon models. We examine the
Clustering stocks using partial correlation coefficients
Jung, Sean S.; Chang, Woojin
2016-11-01
A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.
Partial Actions, Paradoxicality and Topological full Groups
DEFF Research Database (Denmark)
Scarparo, Eduardo
uniform Roe algebra is finite. In Article C, we analyze the C*-algebra generated by the Koopman representation of a topological full group, showing, in particular, that it is not AF andhas real rank zero. We also prove that if G is a finitely generated, elementary amenable group, and C*(G) has real rank......We study how paradoxicality properties affect the way groups partially acton topological spaces and C*-algebras. We also investigate the real rank zero and AF properties for certain classes of group C*-algebras. Specifically, in article A, we characterize supramenable groups in terms of existence...... of invariant probability measures for partial actions on compact Hausdorff spaces and existence of tracial states on partial crossed products. These characterizations show that, in general, one cannot decompose a partial crossed product of a C*-algebra by a semidirect product of groups as two iterated...
Dianovsky, Michael T.; Wink, Donald J.
2012-01-01
This paper describes research on the use of journals in a general education chemistry course for elementary education majors. In the journals, students describe their understanding of a topic, the development of that understanding, and how the topic connects to their lives. In the process, they are able to engage in reflection about several…
Reid, J. C.; Seibert, Warren F.
The analysis of previously obtained data concerning short-term visual memory and cognition by a method suggested by Tucker is proposed. Although interesting individual differences undoubtedly exist in people's ability and capacity to process short-term visual information, studies have not generally examined these differences. In fact, conventional…
Jamison, Joseph A.
2013-01-01
This quantitative study sought to determine whether there were significant statistical differences between the performance scores of special education and general education students' scores when in team or solo-teaching environments as may occur in inclusively taught classrooms. The investigated problem occurs because despite education's stated…
Algebraic partial Boolean algebras
International Nuclear Information System (INIS)
Smith, Derek
2003-01-01
Partial Boolean algebras, first studied by Kochen and Specker in the 1960s, provide the structure for Bell-Kochen-Specker theorems which deny the existence of non-contextual hidden variable theories. In this paper, we study partial Boolean algebras which are 'algebraic' in the sense that their elements have coordinates in an algebraic number field. Several of these algebras have been discussed recently in a debate on the validity of Bell-Kochen-Specker theorems in the context of finite precision measurements. The main result of this paper is that every algebraic finitely-generated partial Boolean algebra B(T) is finite when the underlying space H is three-dimensional, answering a question of Kochen and showing that Conway and Kochen's infinite algebraic partial Boolean algebra has minimum dimension. This result contrasts the existence of an infinite (non-algebraic) B(T) generated by eight elements in an abstract orthomodular lattice of height 3. We then initiate a study of higher-dimensional algebraic partial Boolean algebras. First, we describe a restriction on the determinants of the elements of B(T) that are generated by a given set T. We then show that when the generating set T consists of the rays spanning the minimal vectors in a real irreducible root lattice, B(T) is infinite just if that root lattice has an A 5 sublattice. Finally, we characterize the rays of B(T) when T consists of the rays spanning the minimal vectors of the root lattice E 8
Directory of Open Access Journals (Sweden)
Cheryl Brunelle
2015-05-01
Full Text Available There has been an increasing call to prospectively screen patients with breast cancer for the development of breast cancer-related lymphedema (BCRL following their breast cancer treatment. While the components of a prospective screening program have been published, some centers struggle with how to initiate, establish, and sustain a screening program of their own. The intent of this manuscript is to share our experience and struggles in establishing a prospective surveillance program within the infrastructure of our institution. It is our hope that by sharing our history other centers can learn from our mistakes and successes to better design their own prospective screening program to best serve their patient population.
Torija, Antonio J; Ruiz, Diego P
2015-02-01
The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.
Learning Networks for Lifelong Learning
Sloep, Peter
2009-01-01
Presentation in a seminar organized by Christopher Hoadley at Penn State University, October 2004.Contains general introduction into the Learning Network Programme and a demonstration of the Netlogo Simulation of a Learning Network.
Leila Roshangar; Fariba Salek Ranjbarzadeh; Reza Piri; Mahdi Karimi Shoar; Leila Rasi Marzabadi
2014-01-01
Introduction: The basic medical sciences section requires 2.5 years in the medical education curriculum. Practical courses complement theoretical knowledge in this period to improve their appreciation. Despite spending lots of disbursement and time, this period’s efficacy is not clearly known. Methods: One hundred thirty-three General Practitioner (GP) students have been included in this descriptive cross-sectional study and were asked by questionnaire about the positive impact of practical c...
Schiller, Stefan
2013-01-01
The purpose of this paper is to further the development of initial accounting for internally generated intangible assets, relevant to both academics and practitioners, examining what happens when accountants are given principles-based discretion. This paper draws on existing insights into heuristics or experience-based techniques for making accounting judgments. Knowledge about judgment under uncertainty, and the general framework offered by the heuristics and biases program in particular, fo...
Ong, Natalie; Llewellyn, Cathy; Brown, Nicola; Woolfenden, Susan; Reti, Thomas; Magiros, Marisa; Todd, Katherine; Booth, Karen; Eastwood, Anne; Eastwood, John
2018-01-01
Introduction: Community-based integrated care initiatives for children and families had been developed in Sydney Australia over five years. One of those is the Healthy Homses and Neighbourhoods Integrated Care (HHAN) Initiative. The HHAN design includes several sector workforce capacity building initiatives. A partnership was formed with: primary health networks (PHN), child and family nurses, practice nurses, a general practice training organisation, Sydney Children's Hospita Network and t...
Howard, Robert W
2014-09-01
The power law of practice holds that a power function best interrelates skill performance and amount of practice. However, the law's validity and generality are moot. Some researchers argue that it is an artifact of averaging individual exponential curves while others question whether the law generalizes to complex skills and to performance measures other than response time. The present study tested the power law's generality to development over many years of a very complex cognitive skill, chess playing, with 387 skilled participants, most of whom were grandmasters. A power or logarithmic function best fit grouped data but individuals showed much variability. An exponential function usually was the worst fit to individual data. Groups differing in chess talent were compared and a power function best fit the group curve for the more talented players while a quadratic function best fit that for the less talented. After extreme amounts of practice, a logarithmic function best fit grouped data but a quadratic function best fit most individual curves. Individual variability is great and the power law or an exponential law are not the best descriptions of individual chess skill development. Copyright © 2014 Elsevier B.V. All rights reserved.
Partially composite Higgs models
DEFF Research Database (Denmark)
Alanne, Tommi; Buarque Franzosi, Diogo; Frandsen, Mads T.
2018-01-01
We study the phenomenology of partially composite-Higgs models where electroweak symmetry breaking is dynamically induced, and the Higgs is a mixture of a composite and an elementary state. The models considered have explicit realizations in terms of gauge-Yukawa theories with new strongly...... interacting fermions coupled to elementary scalars and allow for a very SM-like Higgs state. We study constraints on their parameter spaces from vacuum stability and perturbativity as well as from LHC results and find that requiring vacuum stability up to the compositeness scale already imposes relevant...... constraints. A small part of parameter space around the classically conformal limit is stable up to the Planck scale. This is however already strongly disfavored by LHC results. in different limits, the models realize both (partially) composite-Higgs and (bosonic) technicolor models and a dynamical extension...
Arthroscopic partial medial meniscectomy
Directory of Open Access Journals (Sweden)
Dašić Žarko
2011-01-01
Full Text Available Background/Aim. Meniscal injuries are common in professional or recreational sports as well as in daily activities. If meniscal lesions lead to physical impairment they usually require surgical treatment. Arthroscopic treatment of meniscal injuries is one of the most often performed orthopedic operative procedures. Methods. The study analyzed the results of arthroscopic partial medial meniscectomy in 213 patients in a 24-month period, from 2006, to 2008. Results. In our series of arthroscopically treated medial meniscus tears we noted 78 (36.62% vertical complete bucket handle lesions, 19 (8.92% vertical incomplete lesions, 18 (8.45% longitudinal tears, 35 (16.43% oblique tears, 18 (8.45% complex degenerative lesions, 17 (7.98% radial lesions and 28 (13.14% horisontal lesions. Mean preoperative International Knee Documentation Committee (IKDC score was 49.81%, 1 month after the arthroscopic partial medial meniscectomy the mean IKDC score was 84.08%, and 6 months after mean IKDC score was 90.36%. Six months after the procedure 197 (92.49% of patients had good or excellent subjective postoperative clinical outcomes, while 14 (6.57% patients subjectively did not notice a significant improvement after the intervention, and 2 (0.93% patients had no subjective improvement after the partial medial meniscectomy at all. Conclusion. Arthroscopic partial medial meniscetomy is minimally invasive diagnostic and therapeutic procedure and in well selected cases is a method of choice for treatment of medial meniscus injuries when repair techniques are not a viable option. It has small rate of complications, low morbidity and fast rehabilitation.
Hierarchical partial order ranking
International Nuclear Information System (INIS)
Carlsen, Lars
2008-01-01
Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters
Permissive Subsorted Partial Logic in CASL
DEFF Research Database (Denmark)
Cerioli, Maura; Haxthausen, Anne Elisabeth; Krieg-Brückner, Bernd
1997-01-01
This paper presents a permissive subsorted partial logic used in the CoFI Algebraic Specification Language. In contrast to other order-sorted logics, subsorting is not modeled by set inclusions, but by injective embeddings allowing for more general models in which subtypes can have different data...
Crichton ambiguities with infinitely many partial waves
International Nuclear Information System (INIS)
Atkinson, D.; Kok, L.P.; de Roo, M.
1978-01-01
We construct families of spinless two-particle unitary cross sections that possess a nontrivial discrete phase-shift ambiguity, with in general an infinite number of nonvanishing partial waves. A numerical investigation reveals that some of the previously known finite Crichton ambiguities are merely special cases of the newly constructed examples
Partial axillary dissection in early breast cancer
African Journals Online (AJOL)
Tarek Abdel Halim El-Fayoumi
ORIGINAL ARTICLE. Partial axillary dissection in early breast cancer. Tarek Abdel Halim El-Fayoumi *. Department of General Surgery, Faculty of Medicine, Alexandria University, Egypt. Received 16 October 2012; accepted 7 January 2013. Available online 7 March 2013. KEYWORDS. Breast cancer;. Axillary lymph nodes.
Crichton ambiguities with infinitely many partial waves
Atkinson, D.; Kok, L.P.; de Roo, M.
We construct families of spin less two-particle unitary cross sections that possess a nontrivial discrete phase-shift ambiguity, with in general an infinite number of nonvanishing partial waves. A numerical investigation reveals that some of the previously known finite Crichton ambiguities are
Ohno, K; Endo, K
2015-07-01
The Fukushima Daiichi nuclear power plant (FNP-1) accident, while as tragic as the tsunami, was a man-made disaster created by the ignorance of the effects of radiation and radioactive materials. Therefore, it is important that all specialists in radiation protection in medicine sympathize with the anxiety of the general public regarding the harmful effects of radiation and advise people accordingly. All questions and answers were collected related to inquiries from the general public that were posted to reliable websites, including those of the government and radiation-related organizations, from March 2011 to November 2012. The questions were summarized and classified by similarity of content. (1) The total number of questions is 372. The content was broadly classified into three categories: inquiries for radiation-related knowledge and about health effects and foods. The questions asked to obtain radiation-related knowledge were the most common, accounting for 38 %. Thirty-six percentage of the questions were related to health effects, and 26 % involved foods, whereas 18 % of the questions were related to children and pregnancy. (2) The change over time was investigated in 290 questions for which the time of inquiry was known. Directly after the earthquake, the questions were primarily from people seeking radiation-related knowledge. Later, questions related to health effects increased. The anxiety experienced by residents following the nuclear accident was caused primarily by insufficient knowledge related to radiation, concerns about health effects and uncertainties about food and water safety. The development of educational materials focusing on such content will be important for risk communication with the general public in countries with nuclear power plants. Physicians and medical physicist should possess the ability to respond to questions such as these and should continue with medical examinations and treatments in a safe and appropriate manner. © The
International Nuclear Information System (INIS)
Ohno, K.; Endo, K.
2015-01-01
The Fukushima Daiichi nuclear power plant (FNP-1) accident, while as tragic as the tsunami, was a man-made disaster created by the ignorance of the effects of radiation and radioactive materials. Therefore, it is important that all specialists in radiation protection in medicine sympathize with the anxiety of the general public regarding the harmful effects of radiation and advise people accordingly. All questions and answers were collected related to inquiries from the general public that were posted to reliable web sites, including those of the government and radiation-related organizations, from March 2011 to November 2012. The questions were summarized and classified by similarity of content. (1) The total number of questions is 372. The content was broadly classified into three categories: inquiries for radiation-related knowledge and about health effects and foods. The questions asked to obtain radiation-related knowledge were the most common, accounting for 38 %. Thirty-six percentage of the questions were related to health effects, and 26 % involved foods, whereas 18 % of the questions were related to children and pregnancy. (2) The change over time was investigated in 290 questions for which the time of inquiry was known. Directly after the earthquake, the questions were primarily from people seeking radiation-related knowledge. Later, questions related to health effects increased. The anxiety experienced by residents following the nuclear accident was caused primarily by insufficient knowledge related to radiation, concerns about health effects and uncertainties about food and water safety. The development of educational materials focusing on such content will be important for risk communication with the general public in countries with nuclear power plants. Physicians and medical physicist should possess the ability to respond to questions such as these and should continue with medical examinations and treatments in a safe and appropriate manner
Directory of Open Access Journals (Sweden)
Jie Wang
2017-03-01
Full Text Available Deep convolutional neural networks (CNNs have been widely used to obtain high-level representation in various computer vision tasks. However, in the field of remote sensing, there are not sufficient images to train a useful deep CNN. Instead, we tend to transfer successful pre-trained deep CNNs to remote sensing tasks. In the transferring process, generalization power of features in pre-trained deep CNNs plays the key role. In this paper, we propose two promising architectures to extract general features from pre-trained deep CNNs for remote scene classification. These two architectures suggest two directions for improvement. First, before the pre-trained deep CNNs, we design a linear PCA network (LPCANet to synthesize spatial information of remote sensing images in each spectral channel. This design shortens the spatial “distance” of target and source datasets for pre-trained deep CNNs. Second, we introduce quaternion algebra to LPCANet, which further shortens the spectral “distance” between remote sensing images and images used to pre-train deep CNNs. With five well-known pre-trained deep CNNs, experimental results on three independent remote sensing datasets demonstrate that our proposed framework obtains state-of-the-art results without fine-tuning and feature fusing. This paper also provides baseline for transferring fresh pretrained deep CNNs to other remote sensing tasks.
Prather, Edward E.; Rudolph, A. L.; Brissenden, G.; Cormier, S.; Consiglio, D.; Collaboration of Astronomy Teaching Scholars CATS
2012-01-01
Researchers with the NSF-funded Collaboration of Astronomy Teaching Scholars (CATS) Program and the JPL NASA funded Center for Astronomy Education at the University of Arizona have engaged in a multi-year study on the learning that occurs in a general education introductory astronomy class with an enrollment of greater than 700 students. This new "Mega” course, was modeled after the University of Arizona's highly-effective Astro 101 instructional environment which evolved out of the development and testing from the Lecture-Tutorials and Ranking-Task curriculum projects (Prather, Rudolph, & Brissenden 2009). We have undertaken an ambitious research project to assess the effectiveness of this Mega course through the simultaneous implementation of the Light and Spectroscopy Concept Inventory (LSCI), the Stellar Properties Concept Inventory (SPCI), The Lawson Test for Scientific Reasoning, and the Thinking about Science Survey Instrument (TSSI). Results indicate that the content learning gains of the students in these courses are quite high, and that new models for instruction pioneered for this course are critical to crating a productive and collaborative learning environment in the Mega classroom. This material is based in part upon work supported by the National Science Foundation under Grant No. 0715517, a CCLI Phase III Grant for the Collaboration of Astronomy Teaching Scholars (CATS). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Prather, E. E., A. L. Rudolph, and G. Brissenden. 2009. "Teaching and Learning Astronomy in the 21st Century.” Physics Today 62(10), 41.
Allen, Gregory Harold
between the OOA2 and WBOA factors and smoke levels indicates that these factors can be used to identify the influence of biomass burning on ambient aerosols. The effectiveness of using the ChemWiki instead of a traditional textbook was investigated during the spring quarter of 2014. Student performance was measured using common midterms, a final, and a pre/post content exams. We also employed surveys, the Colorado Learning Attitudes about Science Survey (CLASS) for Chemistry, and a weekly time-on-task survey to quantify students' attitudes and study habits. The effectiveness of the ChemWiki compared to a traditional textbook was examined using multiple linear regression analysis with a standard non-inferiority testing framework. Results show that the performance of students in the section who were assigned readings from the ChemWiki was non-inferior to the performance of students in the section who were assigned readings from the traditional textbook, indicating that the ChemWiki does not substantially differ from the standard textbook in terms of student learning outcomes. The results from the surveys also suggest that the two classes were similar in their beliefs about chemistry and overall average time spent studying. These results indicate that the ChemWiki is a viable cost-saving alternative to traditional textbooks. The impact of using active learning techniques in a large lecture general chemistry class was investigated by assessing student performance and attitudes during the fall 2014 and winter 2015 quarters. One instructor applied active learning strategies while the remaining instructors employed more traditional lecture styles. Student performance, learning, learning environments, and attitudes were measured using a standardized pre/post exams, common final exams, classroom observations, and the CLASS chemistry instrument in large lecture general chemistry courses. Classroom observation data showed that the active learning class was the most student centered
Energy Technology Data Exchange (ETDEWEB)
Paech, Daniel [German Cancer Research Center, Department of Radiology, Heidelberg (Germany); Heidelberg University, Institute of Anatomy and Cell Biology, Heidelberg (Germany); Giesel, Frederik L. [University Hospital Heidelberg, Department of Nuclear Medicine, Heidelberg (Germany); Unterhinninghofen, Roland [Institute of Anthropomatics, Karlsruhe Institute of Technology, Karlsruhe (Germany); Schlemmer, Heinz-Peter [German Cancer Research Center, Department of Radiology, Heidelberg (Germany); Kuner, Thomas; Doll, Sara [Heidelberg University, Institute of Anatomy and Cell Biology, Heidelberg (Germany)
2017-05-15
The purpose of this study was to quantify the benefit of the incorporation of radiologic anatomy (RA), in terms of student training in RA seminars, cadaver CT scans and life-size virtual dissection tables on the learning success in general anatomy. Three groups of a total of 238 students were compared in a multiple choice general anatomy exam during first-year gross anatomy: (1) a group (year 2015, n{sub 1} = 50) that received training in radiologic image interpretation (RA seminar) and additional access to cadaver CT scans (CT + seminar group); (2) a group (2011, n{sub 2} = 90) that was trained in the RA seminar only (RA seminar group); (3) a group (2011, n{sub 3} = 98) without any radiologic image interpretation training (conventional anatomy group). Furthermore, the students' perception of the new curriculum was assessed qualitatively through a survey. The average test score of the CT + seminar group (21.8 ± 5.0) was significantly higher when compared to both the RA seminar group (18.3 ± 5.0) and the conventional anatomy group (17.1 ± 4.7) (p < 0.001). The incorporation of cadaver CT scans and life-size virtual dissection tables significantly improved the performance of medical students in general gross anatomy. Medical imaging and virtual dissection should therefore be considered to be part of the standard curriculum of gross anatomy. circle Students provided with cadaver CT scans achieved 27 % higher scores in anatomy. (orig.)
International Nuclear Information System (INIS)
Paech, Daniel; Giesel, Frederik L.; Unterhinninghofen, Roland; Schlemmer, Heinz-Peter; Kuner, Thomas; Doll, Sara
2017-01-01
The purpose of this study was to quantify the benefit of the incorporation of radiologic anatomy (RA), in terms of student training in RA seminars, cadaver CT scans and life-size virtual dissection tables on the learning success in general anatomy. Three groups of a total of 238 students were compared in a multiple choice general anatomy exam during first-year gross anatomy: (1) a group (year 2015, n_1 = 50) that received training in radiologic image interpretation (RA seminar) and additional access to cadaver CT scans (CT + seminar group); (2) a group (2011, n_2 = 90) that was trained in the RA seminar only (RA seminar group); (3) a group (2011, n_3 = 98) without any radiologic image interpretation training (conventional anatomy group). Furthermore, the students' perception of the new curriculum was assessed qualitatively through a survey. The average test score of the CT + seminar group (21.8 ± 5.0) was significantly higher when compared to both the RA seminar group (18.3 ± 5.0) and the conventional anatomy group (17.1 ± 4.7) (p < 0.001). The incorporation of cadaver CT scans and life-size virtual dissection tables significantly improved the performance of medical students in general gross anatomy. Medical imaging and virtual dissection should therefore be considered to be part of the standard curriculum of gross anatomy. circle Students provided with cadaver CT scans achieved 27 % higher scores in anatomy. (orig.)
Partially coherent isodiffracting pulsed beams
Koivurova, Matias; Ding, Chaoliang; Turunen, Jari; Pan, Liuzhan
2018-02-01
We investigate a class of isodiffracting pulsed beams, which are superpositions of transverse modes supported by spherical-mirror laser resonators. By employing modal weights that, for stationary light, produce a Gaussian Schell-model beam, we extend this standard model to pulsed beams. We first construct the two-frequency cross-spectral density function that characterizes the spatial coherence in the space-frequency domain. By assuming a power-exponential spectral profile, we then employ the generalized Wiener-Khintchine theorem for nonstationary light to derive the two-time mutual coherence function that describes the space-time coherence of the ensuing beams. The isodiffracting nature of the laser resonator modes permits all (paraxial-domain) calculations at any propagation distance to be performed analytically. Significant spatiotemporal coupling is revealed in subcycle, single-cycle, and few-cycle domains, where the partial spatial coherence also leads to reduced temporal coherence even though full spectral coherence is assumed.
Robot-assisted partial nephrectomy in contemporary practice
Directory of Open Access Journals (Sweden)
Youssef S. Tanagho
2013-01-01
Full Text Available Laparoscopic renal surgery is associated with reduced blood loss, shorter hospital stay, enhanced cosmesis, and more rapid convalescence relative to open renal surgery. Laparoscopic partial nephrectomy is a minimally invasive, nephron-sparing alternative to laparoscopic radical nephrectomy for the management of small renal masses. While offering similar oncological outcomes to laparoscopic radical nephrectomy, the technical challenges and prolonged learning curve associated with laparoscopic partial nephrectomy limit its wider dissemination. Robot-assisted partial nephrectomy, although still an evolving procedure with no long-term data, has emerged as a viable alternative to laparoscopic partial nephrectomy, with favorable preliminary outcomes. This article provides an overview of the role of robot-assisted partial nephrectomy in the management of renal cell carcinoma. The clinical indications and principles of surgical technique for this procedure are discussed. The oncological, renal functional, and perioperative outcomes of robot-assisted partial nephrectomy are also evaluated, as are complication rates.
González-Gómez, David; Jeong, Jin Su; Airado Rodríguez, Diego; Cañada-Cañada, Florentina
2016-06-01
"Flipped classroom" teaching methodology is a type of blended learning in which the traditional class setting is inverted. Lecture is shifted outside of class, while the classroom time is employed to solve problems or doing practical works through the discussion/peer collaboration of students and instructors. This relatively new instructional methodology claims that flipping your classroom engages more effectively students with the learning process, achieving better teaching results. Thus, this research aimed to evaluate the effects of the flipped classroom on the students' performance and perception of this new methodology. This study was conducted in a general science course, sophomore of the Primary Education bachelor degree in the Training Teaching School of the University of Extremadura (Spain) during the course 2014/2015. In order to assess the suitability of the proposed methodology, the class was divided in two groups. For the first group, a traditional methodology was followed, and it was used as control. On the other hand, the "flipped classroom" methodology was used in the second group, where the students were given diverse materials, such as video lessons and reading materials, before the class to be revised at home by them. Online questionnaires were as well provided to assess the progress of the students before the class. Finally, the results were compared in terms of students' achievements and a post-task survey was also conducted to know the students' perceptions. A statistically significant difference was found on all assessments with the flipped class students performing higher on average. In addition, most students had a favorable perception about the flipped classroom noting the ability to pause, rewind and review lectures, as well as increased individualized learning and increased teacher availability.
Vock, David M; Wolfson, Julian; Bandyopadhyay, Sunayan; Adomavicius, Gediminas; Johnson, Paul E; Vazquez-Benitez, Gabriela; O'Connor, Patrick J
2016-06-01
Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing patient care. Electronic health data (EHD) are appealing sources of training data because they provide access to large amounts of rich individual-level data from present-day patient populations. However, because EHD are derived by extracting information from administrative and clinical databases, some fraction of subjects will not be under observation for the entire time frame over which one wants to make predictions; this loss to follow-up is often due to disenrollment from the health system. For subjects without complete follow-up, whether or not they experienced the adverse event is unknown, and in statistical terms the event time is said to be right-censored. Most machine learning approaches to the problem have been relatively ad hoc; for example, common approaches for handling observations in which the event status is unknown include (1) discarding those observations, (2) treating them as non-events, (3) splitting those observations into two observations: one where the event occurs and one where the event does not. In this paper, we present a general-purpose approach to account for right-censored outcomes using inverse probability of censoring weighting (IPCW). We illustrate how IPCW can easily be incorporated into a number of existing machine learning algorithms used to mine big health care data including Bayesian networks, k-nearest neighbors, decision trees, and generalized additive models. We then show that our approach leads to better calibrated predictions than the three ad hoc approaches when applied to predicting the 5-year risk of experiencing a cardiovascular adverse event, using EHD from a large U.S. Midwestern healthcare system. Copyright © 2016 Elsevier Inc. All rights reserved.
Partially ordered algebraic systems
Fuchs, Laszlo
2011-01-01
Originally published in an important series of books on pure and applied mathematics, this monograph by a distinguished mathematician explores a high-level area in algebra. It constitutes the first systematic summary of research concerning partially ordered groups, semigroups, rings, and fields. The self-contained treatment features numerous problems, complete proofs, a detailed bibliography, and indexes. It presumes some knowledge of abstract algebra, providing necessary background and references where appropriate. This inexpensive edition of a hard-to-find systematic survey will fill a gap i
International Nuclear Information System (INIS)
Sprung, D.W.L.
1975-01-01
This paper is a brief review of those aspects of the effective interaction problem that can be grouped under the heading of infinite partial summations of the perturbation series. After a brief mention of the classic examples of infinite summations, the author turns to the effective interaction problem for two extra core particles. Their direct interaction is summed to produce the G matrix, while their indirect interaction through the core is summed in a variety of ways under the heading of core polarization. (orig./WL) [de
Chen, Herman Z. Q.; Kitaev, Sergey; Mütze, Torsten; Sun, Brian Y.
2016-01-01
A universal word for a finite alphabet $A$ and some integer $n\\geq 1$ is a word over $A$ such that every word in $A^n$ appears exactly once as a subword (cyclically or linearly). It is well-known and easy to prove that universal words exist for any $A$ and $n$. In this work we initiate the systematic study of universal partial words. These are words that in addition to the letters from $A$ may contain an arbitrary number of occurrences of a special `joker' symbol $\\Diamond\
Partial differential equations
Agranovich, M S
2002-01-01
Mark Vishik's Partial Differential Equations seminar held at Moscow State University was one of the world's leading seminars in PDEs for over 40 years. This book celebrates Vishik's eightieth birthday. It comprises new results and survey papers written by many renowned specialists who actively participated over the years in Vishik's seminars. Contributions include original developments and methods in PDEs and related fields, such as mathematical physics, tomography, and symplectic geometry. Papers discuss linear and nonlinear equations, particularly linear elliptic problems in angles and gener
Partial differential equations
Levine, Harold
1997-01-01
The subject matter, partial differential equations (PDEs), has a long history (dating from the 18th century) and an active contemporary phase. An early phase (with a separate focus on taut string vibrations and heat flow through solid bodies) stimulated developments of great importance for mathematical analysis, such as a wider concept of functions and integration and the existence of trigonometric or Fourier series representations. The direct relevance of PDEs to all manner of mathematical, physical and technical problems continues. This book presents a reasonably broad introductory account of the subject, with due regard for analytical detail, applications and historical matters.
Partial differential equations
Sloan, D; Süli, E
2001-01-01
/homepage/sac/cam/na2000/index.html7-Volume Set now available at special set price ! Over the second half of the 20th century the subject area loosely referred to as numerical analysis of partial differential equations (PDEs) has undergone unprecedented development. At its practical end, the vigorous growth and steady diversification of the field were stimulated by the demand for accurate and reliable tools for computational modelling in physical sciences and engineering, and by the rapid development of computer hardware and architecture. At the more theoretical end, the analytical insight in
Elliptic partial differential equations
Han, Qing
2011-01-01
Elliptic Partial Differential Equations by Qing Han and FangHua Lin is one of the best textbooks I know. It is the perfect introduction to PDE. In 150 pages or so it covers an amazing amount of wonderful and extraordinary useful material. I have used it as a textbook at both graduate and undergraduate levels which is possible since it only requires very little background material yet it covers an enormous amount of material. In my opinion it is a must read for all interested in analysis and geometry, and for all of my own PhD students it is indeed just that. I cannot say enough good things abo
Boughner, Robert L; Papini, Mauricio R
2008-05-01
Results from a variety of independently run experiments suggest that latent inhibition (LI) and the partial reinforcement extinction effect (PREE) share underlying mechanisms. Experiment 1 tested this LI=PREE hypothesis by training the same set of rats in situations involving both nonreinforced preexposure to the conditioned stimulus (LI stage) and partial reinforcement training (PREE stage). Control groups were also included to assess both LI and the PREE. The results demonstrated a significant, but negative correlation between the size of the LI effect and that of the PREE. Experiment 2 extended this analysis to the effects on LI and the PREE of the anxiolytic benzodiazepine chlordiazepoxide (5 mg/kg, i.p.). Whereas chlordiazepoxide had no effect on LI, it delayed the onset of the PREE. No evidence in support of the LI=PREE hypothesis was obtained when these two learning phenomena were compared within the same experiment and under the same general conditions of training.
Directory of Open Access Journals (Sweden)
Quan-Hoang Vuong
2017-03-01
Full Text Available Background: General health examinations (GHEs help Vietnamese detect early signs of illness and serve to be an important part of preventive medicine. Having GHEs can help reduce risks of poverty due to prolonged medical treatments in Vietnam, as 70% patients without health insurance face financial burdens caused by expensive treatments. Aims & Objectives: Does owning a medicine cabinet or having practical first-aid knowledge and skills have effects on people’s attitude towards GHEs? Materials & Methods: Analysis is performed on a 2,068-observation dataset, collected from a survey towards GHEs propensity collected in Hanoi and its vicinities. The methods of baseline-categorical logit model and ordinary least square are used to estimate the probabilities. Results: (1 There exist differences in the tendency of attending GHEs between those with and without a family medicine cabinet, and knowledge of using basic medical equipment; (2 The factors of age, gender, job and marital status are also proven related to body mass index (BMI. Conclusion: People who have common medical tools in the family and medical skills are likely to have GHEs more often. The likelihood of being over-weight is higher when people become older, especially among women.
Directory of Open Access Journals (Sweden)
Quan-Hoang Vuong
2017-03-01
Full Text Available Background: General health examinations (GHEs help Vietnamese detect early signs of illness and serve to be an important part of preventive medicine. Having GHEs can help reduce risks of poverty due to prolonged medical treatments in Vietnam, as 70% patients without health insurance face financial burdens caused by expensive treatments. Aims & Objectives: Does owning a medicine cabinet or having practical first-aid knowledge and skills have effects on people’s attitude towards GHEs? Materials & Methods: Analysis is performed on a 2,068-observation dataset, collected from a survey towards GHEs propensity collected in Hanoi and its vicinities. The methods of baseline-categorical logit model and ordinary least square are used to estimate the probabilities. Results: (1 There exist differences in the tendency of attending GHEs between those with and without a family medicine cabinet, and knowledge of using basic medical equipment; (2 The factors of age, gender, job and marital status are also proven related to body mass index (BMI. Conclusion: People who have common medical tools in the family and medical skills are likely to have GHEs more often. The likelihood of being over-weight is higher when people become older, especially among women.
Simcock, Gabrielle; Dooley, Megan
2007-11-01
Researchers know little about whether very young children can recognize objects originally introduced to them in a picture book when they encounter similar looking objects in various real-world contexts. The present studies used an imitation procedure to explore young children's ability to generalize a novel action sequence from a picture book to novel test conditions. The authors found that 18-month-olds imitated the action sequence from a book only when the conditions at testing matched those at encoding; altering the test stimuli or context disrupted imitation (Experiment 1A). In contrast, the 24-month-olds imitated the action sequence with changes to both the test context and stimuli (Experiment 1B). Moreover, although the 24-month-olds exhibited deferred imitation with no changes to the test conditions, they did not defer imitation with changes to the context and stimuli (Experiment 2). Two factors may account for the pattern of results: age-related changes in children's ability to utilize novel retrieval cues as well as their emerging ability to understand the representational nature of pictures. (c) 2007 APA.
D'Isanto, A.; Polsterer, K. L.
2018-01-01
Context. The need to analyze the available large synoptic multi-band surveys drives the development of new data-analysis methods. Photometric redshift estimation is one field of application where such new methods improved the results, substantially. Up to now, the vast majority of applied redshift estimation methods have utilized photometric features. Aims: We aim to develop a method to derive probabilistic photometric redshift directly from multi-band imaging data, rendering pre-classification of objects and feature extraction obsolete. Methods: A modified version of a deep convolutional network was combined with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) were applied as performance criteria. We have adopted a feature based random forest and a plain mixture density network to compare performances on experiments with data from SDSS (DR9). Results: We show that the proposed method is able to predict redshift PDFs independently from the type of source, for example galaxies, quasars or stars. Thereby the prediction performance is better than both presented reference methods and is comparable to results from the literature. Conclusions: The presented method is extremely general and allows us to solve of any kind of probabilistic regression problems based on imaging data, for example estimating metallicity or star formation rate of galaxies. This kind of methodology is tremendously important for the next generation of surveys.
Unilateral removable partial dentures.
Goodall, W A; Greer, A C; Martin, N
2017-01-27
Removable partial dentures (RPDs) are widely used to replace missing teeth in order to restore both function and aesthetics for the partially dentate patient. Conventional RPD design is frequently bilateral and consists of a major connector that bridges both sides of the arch. Some patients cannot and will not tolerate such an extensive appliance. For these patients, bridgework may not be a predictable option and it is not always possible to provide implant-retained restorations. This article presents unilateral RPDs as a potential treatment modality for such patients and explores indications and contraindications for their use, including factors relating to patient history, clinical presentation and patient wishes. Through case examples, design, material and fabrication considerations will be discussed. While their use is not widespread, there are a number of patients who benefit from the provision of unilateral RPDs. They are a useful treatment to have in the clinician's armamentarium, but a highly-skilled dental team and a specific patient presentation is required in order for them to be a reasonable and predictable prosthetic option.
Universal Partial Words over Non-Binary Alphabets
Goeckner, Bennet; Groothuis, Corbin; Hettle, Cyrus; Kell, Brian; Kirkpatrick, Pamela; Kirsch, Rachel; Solava, Ryan
2016-01-01
Chen, Kitaev, M\\"{u}tze, and Sun recently introduced the notion of universal partial words, a generalization of universal words and de Bruijn sequences. Universal partial words allow for a wild-card character $\\diamond$, which is a placeholder for any letter in the alphabet. We settle and strengthen conjectures posed in the same paper where this notion was introduced. For non-binary alphabets, we show that universal partial words have periodic $\\diamond$ structure and are cyclic, and we give ...
Image Reconstruction For Bioluminescence Tomography From Partial Measurement
Jiang, M.; Zhou, T.; Cheng, J. T.; Cong, W. X.; Wang, Ge
2007-01-01
The bioluminescence tomography is a novel molecular imaging technology for small animal studies. Known reconstruction methods require the completely measured data on the external surface, although only partially measured data is available in practice. In this work, we formulate a mathematical model for BLT from partial data and generalize our previous results on the solution uniqueness to the partial data case. Then we extend two of our reconstruction methods for BLT to this case. The first m...
Tutorial on Online Partial Evaluation
Directory of Open Access Journals (Sweden)
William R. Cook
2011-09-01
Full Text Available This paper is a short tutorial introduction to online partial evaluation. We show how to write a simple online partial evaluator for a simple, pure, first-order, functional programming language. In particular, we show that the partial evaluator can be derived as a variation on a compositionally defined interpreter. We demonstrate the use of the resulting partial evaluator for program optimization in the context of model-driven development.
Type-Directed Partial Evaluation
DEFF Research Database (Denmark)
Danvy, Olivier
1998-01-01
Type-directed partial evaluation uses a normalization function to achieve partial evaluation. These lecture notes review its background, foundations, practice, and applications. Of specific interest is the modular technique of offline and online type-directed partial evaluation in Standard ML...
Type-Directed Partial Evaluation
DEFF Research Database (Denmark)
Danvy, Olivier
1998-01-01
Type-directed partial evaluation uses a normalization function to achieve partial evaluation. These lecture notes review its background, foundations, practice, and applications. Of specific interest is the modular technique of offline and online type-directed partial evaluation in Standard ML of ...
Directory of Open Access Journals (Sweden)
Rui Celso Martins Mamede
2008-02-01
Full Text Available Tireoidectomia sob efeito de bloqueio do plexo cervical superficial (BPCS tem sofrido resistência. OBJETIVO: Comparar variáveis cirúrgicas e anestésicas, custos do tratamento e grau de satisfação de pacientes submetidos à hemitireoidectomia sob efeito de anestesia geral e BPCS. CASUÍSTICA E MÉTODOS: Foram 21 pacientes submetidos à anestesia geral (AG e outro tanto ao BPCS. Após sedação, no grupo com BPCS, usou-se marcaína com vasoconstritor, e quando necessário, lidocaína a 2% com vasoconstritor. Sedação intra-operatória com diazepam endovenoso e metoprolol para controle da PA e FC eram administradas quando necessário. Usou-se anestesia geral (AG segundo padronização do serviço. RESULTADOS: Foram significantes (pThyroidectomy under the effect of superficial cervical plexus block (SCPB has met resistance. AIM: to compare variables in patients submitted to hemithyroidectomy under the effect of general anesthesia (GA and SCPB. CASE REPORT AND METHODS: GA was used in 21 patients, and SCPB was used in another 21 patients. Following sedation, marcaine 0.5% with vasoconstrictor was used in the SCPB group. Intraoperative sedation with diazepam and metoprolol to control arterial pressure and cardiac frequency was given as needed. GA followed the standard method in the unit. RESULTS: We found significant results (p<0.05, Student’s t-test for surgery time (GA - 111.4 min; SCPB - 125.5 min, anesthesia time (GA - 154.1 min; SCPB - 488.6 min, time in the surgery room (GA - 15 min; SCPB - 1 min, treatment costs (GA - R$203.2; SCPB - R$87.4, presence of bradycardia (GA - 0; SCPB - 23.8% and laryngotracheal injury (GA - 51; SCPB - 0 %. We also found the following non-significant results: hospitalization time (GA - 17.3; SCPB - 15.1 hours; bleeding volume (GA - 41,9 g; SCPB - 47.6 g, size of the operative specimen (GA - 52.1 cm3; SCPB - 93.69 cm3 and patient satisfaction level (GA - 3.8; SCPB - 3.9. CONCLUSION: Although the incidence of
Almanasreh, Hasan
2017-01-01
This study concerns the use of e-learning in the educational system shedding the light on its advantages and disadvantages, and analyzing its applicability either partially or totally. From mathematical perspectives, theories are developed to test the courses tendency to online transformation. This leads to a new trend of learning, the offline-online-offline learning (fnf-learning), it merges e-learning mode with the traditional orientation of education. The derivation of the new trend is bas...
Applied partial differential equations
Logan, J David
2004-01-01
This primer on elementary partial differential equations presents the standard material usually covered in a one-semester, undergraduate course on boundary value problems and PDEs. What makes this book unique is that it is a brief treatment, yet it covers all the major ideas: the wave equation, the diffusion equation, the Laplace equation, and the advection equation on bounded and unbounded domains. Methods include eigenfunction expansions, integral transforms, and characteristics. Mathematical ideas are motivated from physical problems, and the exposition is presented in a concise style accessible to science and engineering students; emphasis is on motivation, concepts, methods, and interpretation, rather than formal theory. This second edition contains new and additional exercises, and it includes a new chapter on the applications of PDEs to biology: age structured models, pattern formation; epidemic wave fronts, and advection-diffusion processes. The student who reads through this book and solves many of t...
Paul, Clayton R
2010-01-01
"Inductance is an unprecedented text, thoroughly discussing "loop" inductance as well as the increasingly important "partial" inductance. These concepts and their proper calculation are crucial in designing modern high-speed digital systems. World-renowned leader in electromagnetics Clayton Paul provides the knowledge and tools necessary to understand and calculate inductance." "With the present and increasing emphasis on high-speed digital systems and high-frequency analog systems, it is imperative that system designers develop an intimate understanding of the concepts and methods in this book. Inductance is a much-needed textbook designed for senior and graduate-level engineering students, as well as a hands-on guide for working engineers and professionals engaged in the design of high-speed digital and high-frequency analog systems."--Jacket.
Fundamental partial compositeness
Sannino, Francesco
2016-11-07
We construct renormalizable Standard Model extensions, valid up to the Planck scale, that give a composite Higgs from a new fundamental strong force acting on fermions and scalars. Yukawa interactions of these particles with Standard Model fermions realize the partial compositeness scenario. Successful models exist because gauge quantum numbers of Standard Model fermions admit a minimal enough 'square root'. Furthermore, right-handed SM fermions have an SU(2)$_R$-like structure, yielding a custodially-protected composite Higgs. Baryon and lepton numbers arise accidentally. Standard Model fermions acquire mass at tree level, while the Higgs potential and flavor violations are generated by quantum corrections. We further discuss accidental symmetries and other dynamical features stemming from the new strongly interacting scalars. If the same phenomenology can be obtained from models without our elementary scalars, they would reappear as composite states.
Fundamental partial compositeness
International Nuclear Information System (INIS)
Sannino, Francesco; Strumia, Alessandro; Tesi, Andrea; Vigiani, Elena
2016-01-01
We construct renormalizable Standard Model extensions, valid up to the Planck scale, that give a composite Higgs from a new fundamental strong force acting on fermions and scalars. Yukawa interactions of these particles with Standard Model fermions realize the partial compositeness scenario. Under certain assumptions on the dynamics of the scalars, successful models exist because gauge quantum numbers of Standard Model fermions admit a minimal enough ‘square root’. Furthermore, right-handed SM fermions have an SU(2)_R-like structure, yielding a custodially-protected composite Higgs. Baryon and lepton numbers arise accidentally. Standard Model fermions acquire mass at tree level, while the Higgs potential and flavor violations are generated by quantum corrections. We further discuss accidental symmetries and other dynamical features stemming from the new strongly interacting scalars. If the same phenomenology can be obtained from models without our elementary scalars, they would reappear as composite states.
Partial differential equations & boundary value problems with Maple
Articolo, George A
2009-01-01
Partial Differential Equations and Boundary Value Problems with Maple presents all of the material normally covered in a standard course on partial differential equations, while focusing on the natural union between this material and the powerful computational software, Maple. The Maple commands are so intuitive and easy to learn, students can learn what they need to know about the software in a matter of hours- an investment that provides substantial returns. Maple''s animation capabilities allow students and practitioners to see real-time displays of the solutions of partial differential equations. Maple files can be found on the books website. Ancillary list: Maple files- http://www.elsevierdirect.com/companion.jsp?ISBN=9780123747327 Provides a quick overview of the software w/simple commands needed to get startedIncludes review material on linear algebra and Ordinary Differential equations, and their contribution in solving partial differential equationsIncorporates an early introduction to Sturm-L...
International Nuclear Information System (INIS)
Najjar, M.S.
1987-01-01
A process is described for the production of gaseous mixtures comprising H/sub 2/+CO by the partial oxidation of a fuel feedstock comprising a heavy liquid hydrocarbonaceous fuel having a nickel, iron, and vanadium-containing ash or petroleum coke having a nickel, iron, and vanadium-containing ash, or mixtures thereof. The feedstock includes a minimum of 0.5 wt. % of sulfur and the ash includes a minimum of 5.0 wt. % vanadium, a minimum of 0.5 ppm nickel, and a minimum of 0.5 ppm iron. The process comprises: (1) mixing together a copper-containing additive with the fuel feedstock; wherein the weight ratio of copper-containing additive to ash in the fuel feedstock is in the range of about 1.0-10.0, and there is at least 10 parts by weight of copper for each part by weight of vanadium; (2) reacting the mixture from (1) at a temperature in the range of 2200 0 F to 2900 0 F and a pressure in the range of about 5 to 250 atmospheres in a free-flow refactory lined partial oxidation reaction zone with a free-oxygen containing gas in the presence of a temperature moderator and in a reducing atmosphere to produce a hot raw effluent gas stream comprising H/sub 2/+CO and entrained molten slag; and where in the reaction zone and the copper-containing additive combines with at least a portion of the nickel and iron constituents and sulfur found in the feedstock to produce a liquid phase washing agent that collects and transports at least a portion of the vanadium-containing oxide laths and spinels and other ash components and refractory out of the reaction zone; and (3) separating nongaseous materials from the hot raw effluent gas stream
48 CFR 49.109-5 - Partial settlements.
2010-10-01
... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Partial settlements. 49... MANAGEMENT TERMINATION OF CONTRACTS General Principles 49.109-5 Partial settlements. The TCO should attempt... settlements covering particular items of the prime contractor's settlement proposal. However, when a TCO...
A note on the Lie symmetries of complex partial differential
Indian Academy of Sciences (India)
Folklore suggests that the split Lie-like operators of a complex partial differential equation are symmetries of the split system of real partial differential equations. However, this is not the case generally. We illustrate this by using the complex heat equation, wave equation with dissipation, the nonlinear Burgers equation and ...
28 CFR 73.4 - Partial compliance not deemed compliance.
2010-07-01
... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Partial compliance not deemed compliance. 73.4 Section 73.4 Judicial Administration DEPARTMENT OF JUSTICE (CONTINUED) NOTIFICATIONS TO THE ATTORNEY GENERAL BY AGENTS OF FOREIGN GOVERNMENTS § 73.4 Partial compliance not deemed compliance. The fact...
Paech, Daniel; Giesel, Frederik L; Unterhinninghofen, Roland; Schlemmer, Heinz-Peter; Kuner, Thomas; Doll, Sara
2017-05-01
The purpose of this study was to quantify the benefit of the incorporation of radiologic anatomy (RA), in terms of student training in RA seminars, cadaver CT scans and life-size virtual dissection tables on the learning success in general anatomy. Three groups of a total of 238 students were compared in a multiple choice general anatomy exam during first-year gross anatomy: (1) a group (year 2015, n 1 = 50) that received training in radiologic image interpretation (RA seminar) and additional access to cadaver CT scans (CT + seminar group); (2) a group (2011, n 2 = 90) that was trained in the RA seminar only (RA seminar group); (3) a group (2011, n 3 = 98) without any radiologic image interpretation training (conventional anatomy group). Furthermore, the students' perception of the new curriculum was assessed qualitatively through a survey. The average test score of the CT + seminar group (21.8 ± 5.0) was significantly higher when compared to both the RA seminar group (18.3 ± 5.0) and the conventional anatomy group (17.1 ± 4.7) (p cadaver CT scans and life-size virtual dissection tables significantly improved the performance of medical students in general gross anatomy. Medical imaging and virtual dissection should therefore be considered to be part of the standard curriculum of gross anatomy. • Students provided with cadaver CT scans achieved 27 % higher scores in anatomy. • Radiological education integrated into gross anatomy is highly appreciated by medical students. • Simultaneous physical and virtual dissection provide unique conditions to study anatomy.
Hamiltonian partial differential equations and applications
Nicholls, David; Sulem, Catherine
2015-01-01
This book is a unique selection of work by world-class experts exploring the latest developments in Hamiltonian partial differential equations and their applications. Topics covered within are representative of the field’s wide scope, including KAM and normal form theories, perturbation and variational methods, integrable systems, stability of nonlinear solutions as well as applications to cosmology, fluid mechanics and water waves. The volume contains both surveys and original research papers and gives a concise overview of the above topics, with results ranging from mathematical modeling to rigorous analysis and numerical simulation. It will be of particular interest to graduate students as well as researchers in mathematics and physics, who wish to learn more about the powerful and elegant analytical techniques for Hamiltonian partial differential equations.
Accidental transection of flexometallic endotracheal tube during partial maxillectomy
Directory of Open Access Journals (Sweden)
Sushma D Ladi
2011-01-01
Full Text Available We report a rare case of an 18-year-old female patient in whom accidental sectioning of flexometallic endotracheal tube occurred during partial maxillectomy for mass lesion under general anaesthesia. She was managed successfully by tracheostomy.
Exact solutions of some nonlinear partial differential equations using ...
Indian Academy of Sciences (India)
Nonlinear partial differential equations (NPDEs) are encountered in various ... such as physics, mechanics, chemistry, biology, mathematics and engineering. ... In §3, this method is applied to the generalized forms of Klein–Gordon equation,.
DEFF Research Database (Denmark)
Hasse, Cathrine
This book shall explore the concept of learning from the new perspective of the posthuman. The vast majority of cognitive, behavioral and part of the constructionist learning theories operate with an autonomous individual who learn in a world of separate objects. Technology is (if mentioned at all......) understood as separate from the individual learner and perceived as tools. Learning theory has in general not been acknowledging materiality in their theorizing about what learning is. A new posthuman learning theory is needed to keep up with the transformations of human learning resulting from new...... technological experiences. One definition of learning is that it is a relatively permanent change in behavior as the result of experience. During the first half of the twentieth century, two theoretical approaches dominated the domain of learning theory: the schools of thought commonly known as behaviorism...
Experts' understanding of partial derivatives using the Partial Derivative Machine
Roundy, David; Dorko, Allison; Dray, Tevian; Manogue, Corinne A.; Weber, Eric
2014-01-01
Partial derivatives are used in a variety of different ways within physics. Most notably, thermodynamics uses partial derivatives in ways that students often find confusing. As part of a collaboration with mathematics faculty, we are at the beginning of a study of the teaching of partial derivatives, a goal of better aligning the teaching of multivariable calculus with the needs of students in STEM disciplines. As a part of this project, we have performed a pilot study of expert understanding...
Deterministic dense coding with partially entangled states
Mozes, Shay; Oppenheim, Jonathan; Reznik, Benni
2005-01-01
The utilization of a d -level partially entangled state, shared by two parties wishing to communicate classical information without errors over a noiseless quantum channel, is discussed. We analytically construct deterministic dense coding schemes for certain classes of nonmaximally entangled states, and numerically obtain schemes in the general case. We study the dependency of the maximal alphabet size of such schemes on the partially entangled state shared by the two parties. Surprisingly, for d>2 it is possible to have deterministic dense coding with less than one ebit. In this case the number of alphabet letters that can be communicated by a single particle is between d and 2d . In general, we numerically find that the maximal alphabet size is any integer in the range [d,d2] with the possible exception of d2-1 . We also find that states with less entanglement can have a greater deterministic communication capacity than other more entangled states.
Directory of Open Access Journals (Sweden)
Morayma Zulueta Yate
2012-03-01
of Iribarren municipality in Lara State, Venezuela. Methods: a retrospective, cross-sectional and descriptive study was conducted from December, 2006 to June, 2007. Study universe included 46 physicians working in consulting rooms of this municipality. To data collection a survey was applied previous informed consent. Absolute numbers and percentages were used as a measure by each variable used. Results: there was predominance of 28 physicians with a 6 and 10 years working experience for a 60.9 %. Total of physicians recognized as drugs the marihuana, heroin and cocaine. All declared that only the ill patient must to receive priority; also, the was predominance of the criterion that the treatment must to be applied when the patient is hospitalized for a 56.6 %. The was an scanty experience on the management of these patients for a 91.3 % and the 100 % of polled persons declared its total knowledge of the existence of the Drug Addiction National Program. Conclusions: there is a scanty knowledge regarding the management of drug addiction in the primary health care; the needs of learning by Venezuelan integral general physicians were identified.
Five Generalizations About Cognitive Development.
Siegler, Robert S.
1983-01-01
Proposes five generalizations on existing knowledge, learning, and their interaction, and discusses evidence for these from recent research on children's learning, memory, conceptual understanding, and problem solving. (Author/AOS)
On the relation between elementary partial difference equations and partial differential equations
van den Berg, I.P.
1998-01-01
The nonstandard stroboscopy method links discrete-time ordinary difference equations of first-order and continuous-time, ordinary differential equations of first order. We extend this method to the second order, and also to an elementary, yet general class of partial difference/differential
Ambit processes and stochastic partial differential equations
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Benth, Fred Espen; Veraart, Almut
Ambit processes are general stochastic processes based on stochastic integrals with respect to Lévy bases. Due to their flexible structure, they have great potential for providing realistic models for various applications such as in turbulence and finance. This papers studies the connection betwe...... ambit processes and solutions to stochastic partial differential equations. We investigate this relationship from two angles: from the Walsh theory of martingale measures and from the viewpoint of the Lévy noise analysis....
Generalized Superconductivity. Generalized Levitation
International Nuclear Information System (INIS)
Ciobanu, B.; Agop, M.
2004-01-01
In the recent papers, the gravitational superconductivity is described. We introduce the concept of generalized superconductivity observing that any nongeodesic motion and, in particular, the motion in an electromagnetic field, can be transformed in a geodesic motion by a suitable choice of the connection. In the present paper, the gravitoelectromagnetic London equations have been obtained from the generalized Helmholtz vortex theorem using the generalized local equivalence principle. In this context, the gravitoelectromagnetic Meissner effect and, implicitly, the gravitoelectromagnetic levitation are given. (authors)
Directory of Open Access Journals (Sweden)
Susan I. Gibson
2015-10-01
Full Text Available A rising need for workers in science, technology, engineering and mathematics (STEM fields has fueled interest in improving teaching within STEM disciplines. Numerous studies have demonstrated the benefits of active learning approaches on student learning outcomes. However, many of these studies have been conducted in experimental, rather than real-life class, settings. In addition, most of these studies have focused on in-class active learning exercises. This study tested the effects of answering questions outside of class on exam performance for General Biology students at the University of Minnesota. An online database of 1,020 multiple-choice questions covering material from the first half of the course was generated. Students in seven course sections (with an average of ∼265 students per section were given unlimited access to the online study questions. These students made extensive use of the online questions, with students answering an average of 1,323 questions covering material from the half of the semester for which the questions were available. After students answered a set of questions, they were shown the correct answers for those questions. More specific feedback describing how to arrive at the correct answer was provided for the 73% of the questions for which the correct answers were not deemed to be self-explanatory. The extent to which access to the online study questions improved student learning outcomes was assessed by comparing the performance on exam questions of students in the seven course sections with access to the online study questions with the performance of students in course sections without access to the online study questions. Student performance was analyzed for a total of 89 different exams questions that were not included in the study questions, but that covered the same material covered by the study questions. Each of these 89 questions was used on one to five exams given to students in course sections that
Gibson, Susan I
2015-01-01
A rising need for workers in science, technology, engineering and mathematics (STEM) fields has fueled interest in improving teaching within STEM disciplines. Numerous studies have demonstrated the benefits of active learning approaches on student learning outcomes. However, many of these studies have been conducted in experimental, rather than real-life class, settings. In addition, most of these studies have focused on in-class active learning exercises. This study tested the effects of answering questions outside of class on exam performance for General Biology students at the University of Minnesota. An online database of 1,020 multiple-choice questions covering material from the first half of the course was generated. Students in seven course sections (with an average of ∼265 students per section) were given unlimited access to the online study questions. These students made extensive use of the online questions, with students answering an average of 1,323 questions covering material from the half of the semester for which the questions were available. After students answered a set of questions, they were shown the correct answers for those questions. More specific feedback describing how to arrive at the correct answer was provided for the 73% of the questions for which the correct answers were not deemed to be self-explanatory. The extent to which access to the online study questions improved student learning outcomes was assessed by comparing the performance on exam questions of students in the seven course sections with access to the online study questions with the performance of students in course sections without access to the online study questions. Student performance was analyzed for a total of 89 different exams questions that were not included in the study questions, but that covered the same material covered by the study questions. Each of these 89 questions was used on one to five exams given to students in course sections that had access to the
Extinction of Conditioned Fear is Better Learned and Recalled in the Morning than in the Evening
Pace-Schott, Edward F.; Spencer, Rebecca M.C.; Vijayakumar, Shilpa; Ahmed, Nafis; Verga, Patrick W.; Orr, Scott P.; Pitman, Roger K.; Milad, Mohammed R.
2013-01-01
Sleep helps emotional memories consolidate and may promote generalization of fear extinction memory. We examined whether extinction learning and memory might differ in the morning and evening due, potentially, to circadian and/or sleep-homeostatic factors. Healthy men (N=109) in 6 groups completed a 2-session protocol. In Session 1, fear conditioning was followed by extinction learning. Partial reinforcement with mild electric shock produced conditioned skin conductance responses (SCR) to 2 d...
Partial Actions and Power Sets
Directory of Open Access Journals (Sweden)
Jesús Ávila
2013-01-01
Full Text Available We consider a partial action (X,α with enveloping action (T,β. In this work we extend α to a partial action on the ring (P(X,Δ,∩ and find its enveloping action (E,β. Finally, we introduce the concept of partial action of finite type to investigate the relationship between (E,β and (P(T,β.
Algorithms over partially ordered sets
DEFF Research Database (Denmark)
Baer, Robert M.; Østerby, Ole
1969-01-01
in partially ordered sets, answer the combinatorial question of how many maximal chains might exist in a partially ordered set withn elements, and we give an algorithm for enumerating all maximal chains. We give (in § 3) algorithms which decide whether a partially ordered set is a (lower or upper) semi......-lattice, and whether a lattice has distributive, modular, and Boolean properties. Finally (in § 4) we give Algol realizations of the various algorithms....
Monotherapy for partial epilepsy: focus on levetiracetam
Directory of Open Access Journals (Sweden)
Antonio Gambardella
2008-03-01
Full Text Available Antonio Gambardella1,2, Angelo Labate1,2, Eleonora Colosimo1, Roberta Ambrosio1, Aldo Quattrone1,21Institute of Neurology, University Magna Græcia, Catanzaro, Italy; 2Institute of Neurological Sciences, National Research Council, Piano Lago di Mangone, Cosenza, ItalyAbstract: Levetiracetam (LEV, the S-enantiomer of alpha-ethyl-2-oxo-1-pyrollidine acetamide, is a recently licensed antiepileptic drug (AED for adjunctive therapy of partial seizures. Its mechanism of action is uncertain but it exhibits a unique profile of anticonvulsant activity in models of chronic epilepsy. Five randomized, double-blind, placebo-controlled trials enrolling adult or pediatric patients with refractory partial epilepsy have demonstrated the efficacy of LEV as adjunctive therapy, with a responder rate (≥50% reduction in seizure frequency of 28%–45%. Long-term efficacy studies suggest retention rates of 60% after one year, with 13% of patients seizure-free for 6 months of the study and 8% seizure-free for 1 year. More recent studies illustrated successful conversion to monotherapy in patients with refractory epilepsy, and its effectiveness as a single agent in partial epilepsy. LEV has also efficacy in generalized epilepsies. Adverse effects of LEV, including somnolence, lethargy, and dizziness, are generally mild and their occurrence rate seems to be not significantly different from that observed in placebo groups. LEV also has no clinically significant pharmacokinetic interactions with other AEDs, or with commonly prescribed medications. The combination of effective antiepileptic properties with a relatively mild adverse effect profile makes LEV an attractive therapy for partial seizures.Keywords: levetiracetam, partial epilepsy, antiepileptic drugs
Algorithms for Reinforcement Learning
Szepesvari, Csaba
2010-01-01
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms'
López, Gabriel A.; Sáenz, Jon; Leonardo, Aritz; Gurtubay, Idoia G.
2016-01-01
The "Moodle" platform has been used to put into practice an ongoing evaluation of the students' Physics learning process. The evaluation has been done on the frame of the course General Physics, which is lectured during the first year of the Physics, Mathematics and Electronic Engineering Programmes at the Faculty of Science and…
Anatomic partial nephrectomy: technique evolution.
Azhar, Raed A; Metcalfe, Charles; Gill, Inderbir S
2015-03-01
Partial nephrectomy provides equivalent long-term oncologic and superior functional outcomes as radical nephrectomy for T1a renal masses. Herein, we review the various vascular clamping techniques employed during minimally invasive partial nephrectomy, describe the evolution of our partial nephrectomy technique and provide an update on contemporary thinking about the impact of ischemia on renal function. Recently, partial nephrectomy surgical technique has shifted away from main artery clamping and towards minimizing/eliminating global renal ischemia during partial nephrectomy. Supported by high-fidelity three-dimensional imaging, novel anatomic-based partial nephrectomy techniques have recently been developed, wherein partial nephrectomy can now be performed with segmental, minimal or zero global ischemia to the renal remnant. Sequential innovations have included early unclamping, segmental clamping, super-selective clamping and now culminating in anatomic zero-ischemia surgery. By eliminating 'under-the-gun' time pressure of ischemia for the surgeon, these techniques allow an unhurried, tightly contoured tumour excision with point-specific sutured haemostasis. Recent data indicate that zero-ischemia partial nephrectomy may provide better functional outcomes by minimizing/eliminating global ischemia and preserving greater vascularized kidney volume. Contemporary partial nephrectomy includes a spectrum of surgical techniques ranging from conventional-clamped to novel zero-ischemia approaches. Technique selection should be tailored to each individual case on the basis of tumour characteristics, surgical feasibility, surgeon experience, patient demographics and baseline renal function.
Partial order infinitary term rewriting
DEFF Research Database (Denmark)
Bahr, Patrick
2014-01-01
We study an alternative model of infinitary term rewriting. Instead of a metric on terms, a partial order on partial terms is employed to formalise convergence of reductions. We consider both a weak and a strong notion of convergence and show that the metric model of convergence coincides with th...... to the metric setting -- orthogonal systems are both infinitarily confluent and infinitarily normalising in the partial order setting. The unique infinitary normal forms that the partial order model admits are Böhm trees....
Partial differential equations in several complex variables
Chen, So-Chin
2001-01-01
This book is intended both as an introductory text and as a reference book for those interested in studying several complex variables in the context of partial differential equations. In the last few decades, significant progress has been made in the fields of Cauchy-Riemann and tangential Cauchy-Riemann operators. This book gives an up-to-date account of the theories for these equations and their applications. The background material in several complex variables is developed in the first three chapters, leading to the Levi problem. The next three chapters are devoted to the solvability and regularity of the Cauchy-Riemann equations using Hilbert space techniques. The authors provide a systematic study of the Cauchy-Riemann equations and the \\bar\\partial-Neumann problem, including L^2 existence theorems on pseudoconvex domains, \\frac 12-subelliptic estimates for the \\bar\\partial-Neumann problems on strongly pseudoconvex domains, global regularity of \\bar\\partial on more general pseudoconvex domains, boundary ...
On Degenerate Partial Differential Equations
Chen, Gui-Qiang G.
2010-01-01
Some of recent developments, including recent results, ideas, techniques, and approaches, in the study of degenerate partial differential equations are surveyed and analyzed. Several examples of nonlinear degenerate, even mixed, partial differential equations, are presented, which arise naturally in some longstanding, fundamental problems in fluid mechanics and differential geometry. The solution to these fundamental problems greatly requires a deep understanding of nonlinear degenerate parti...
[Acrylic resin removable partial dentures
Baat, C. de; Witter, D.J.; Creugers, N.H.J.
2011-01-01
An acrylic resin removable partial denture is distinguished from other types of removable partial dentures by an all-acrylic resin base which is, in principle, solely supported by the edentulous regions of the tooth arch and in the maxilla also by the hard palate. When compared to the other types of
Partial Epilepsy with Auditory Features
Directory of Open Access Journals (Sweden)
J Gordon Millichap
2004-07-01
Full Text Available The clinical characteristics of 53 sporadic (S cases of idiopathic partial epilepsy with auditory features (IPEAF were analyzed and compared to previously reported familial (F cases of autosomal dominant partial epilepsy with auditory features (ADPEAF in a study at the University of Bologna, Italy.
Togelius, Julian; Yannakakis, Georgios N.; 2016 IEEE Conference on Computational Intelligence and Games (CIG)
2016-01-01
Arguably the grand goal of artificial intelligence research is to produce machines with general intelligence: the capacity to solve multiple problems, not just one. Artificial intelligence (AI) has investigated the general intelligence capacity of machines within the domain of games more than any other domain given the ideal properties of games for that purpose: controlled yet interesting and computationally hard problems. This line of research, however, has so far focuse...
Partially massless higher-spin theory
Energy Technology Data Exchange (ETDEWEB)
Brust, Christopher [Perimeter Institute for Theoretical Physics,31 Caroline St. N, Waterloo, Ontario N2L 2Y5 (Canada); Hinterbichler, Kurt [CERCA, Department of Physics, Case Western Reserve University,10900 Euclid Ave, Cleveland, OH 44106 (United States)
2017-02-16
We study a generalization of the D-dimensional Vasiliev theory to include a tower of partially massless fields. This theory is obtained by replacing the usual higher-spin algebra of Killing tensors on (A)dS with a generalization that includes “third-order” Killing tensors. Gauging this algebra with the Vasiliev formalism leads to a fully non-linear theory which is expected to be UV complete, includes gravity, and can live on dS as well as AdS. The linearized spectrum includes three massive particles and an infinite tower of partially massless particles, in addition to the usual spectrum of particles present in the Vasiliev theory, in agreement with predictions from a putative dual CFT with the same symmetry algebra. We compute the masses of the particles which are not fixed by the massless or partially massless gauge symmetry, finding precise agreement with the CFT predictions. This involves computing several dozen of the lowest-lying terms in the expansion of the trilinear form of the enlarged higher-spin algebra. We also discuss nuances in the theory that occur in specific dimensions; in particular, the theory dramatically truncates in bulk dimensions D=3,5 and has non-diagonalizable mixings which occur in D=4,7.
Partially massless higher-spin theory
International Nuclear Information System (INIS)
Brust, Christopher; Hinterbichler, Kurt
2017-01-01
We study a generalization of the D-dimensional Vasiliev theory to include a tower of partially massless fields. This theory is obtained by replacing the usual higher-spin algebra of Killing tensors on (A)dS with a generalization that includes “third-order” Killing tensors. Gauging this algebra with the Vasiliev formalism leads to a fully non-linear theory which is expected to be UV complete, includes gravity, and can live on dS as well as AdS. The linearized spectrum includes three massive particles and an infinite tower of partially massless particles, in addition to the usual spectrum of particles present in the Vasiliev theory, in agreement with predictions from a putative dual CFT with the same symmetry algebra. We compute the masses of the particles which are not fixed by the massless or partially massless gauge symmetry, finding precise agreement with the CFT predictions. This involves computing several dozen of the lowest-lying terms in the expansion of the trilinear form of the enlarged higher-spin algebra. We also discuss nuances in the theory that occur in specific dimensions; in particular, the theory dramatically truncates in bulk dimensions D=3,5 and has non-diagonalizable mixings which occur in D=4,7.
Vilar, Lara; Gómez, Israel; Martínez-Vega, Javier; Echavarría, Pilar; Riaño, David; Martín, M Pilar
2016-01-01
The socio-economic factors are of key importance during all phases of wildfire management that include prevention, suppression and restoration. However, modeling these factors, at the proper spatial and temporal scale to understand fire regimes is still challenging. This study analyses socio-economic drivers of wildfire occurrence in central Spain. This site represents a good example of how human activities play a key role over wildfires in the European Mediterranean basin. Generalized Linear Models (GLM) and machine learning Maximum Entropy models (Maxent) predicted wildfire occurrence in the 1980s and also in the 2000s to identify changes between each period in the socio-economic drivers affecting wildfire occurrence. GLM base their estimation on wildfire presence-absence observations whereas Maxent on wildfire presence-only. According to indicators like sensitivity or commission error Maxent outperformed GLM in both periods. It achieved a sensitivity of 38.9% and a commission error of 43.9% for the 1980s, and 67.3% and 17.9% for the 2000s. Instead, GLM obtained 23.33, 64.97, 9.41 and 18.34%, respectively. However GLM performed steadier than Maxent in terms of the overall fit. Both models explained wildfires from predictors such as population density and Wildland Urban Interface (WUI), but differed in their relative contribution. As a result of the urban sprawl and an abandonment of rural areas, predictors like WUI and distance to roads increased their contribution to both models in the 2000s, whereas Forest-Grassland Interface (FGI) influence decreased. This study demonstrates that human component can be modelled with a spatio-temporal dimension to integrate it into wildfire risk assessment.
Directory of Open Access Journals (Sweden)
Pramita Suwal
2017-03-01
Full Text Available Aim: To compare the effects of cast partial denture with conventional all acrylic denture in respect to retention, stability, masticatory efficiency, comfort and periodontal health of abutments. Methods: 50 adult partially edentulous patient seeking for replacement of missing teeth having Kennedy class I and II arches with or without modification areas were selected for the study. Group-A was treated with cast partial denture and Group-B with acrylic partial denture. Data collected during follow-up visit of 3 months, 6 months, and 1 year by evaluating retention, stability, masticatory efficiency, comfort, periodontal health of abutment. Results: Chi-square test was applied to find out differences between the groups at 95% confidence interval where p = 0.05. One year comparison shows that cast partial denture maintained retention and stability better than acrylic partial denture (p< 0.05. The masticatory efficiency was significantly compromising from 3rd month to 1 year in all acrylic partial denture groups (p< 0.05. The comfort of patient with cast partial denture was maintained better during the observation period (p< 0.05. Periodontal health of abutment was gradually deteriorated in all acrylic denture group (p
Mosse, E. K.; Jarrold, C.
2010-01-01
Background: The Hebb effect is a form of repetition-driven long-term learning that is thought to provide an analogue for the processes involved in new word learning. Other evidence suggests that verbal short-term memory also constrains now vocabulary acquisition, but if the Hebb effect is independent of short-term memory, then it may be possible…
Ratnayaka, Harish H.
2017-01-01
Outdoor, hands-on and experiential learning, as opposed to instruction-based learning in classroom, increases student satisfaction and motivation leading to a deeper understanding of the subject. However, the use of outdoor exercises in undergraduate biology courses is declining due to a variety of constraints. Thus, the goal of this paper is to…
Steffensky, Mirjam; Gold, Bernadette; Holdynski, Manfred; Möller, Kornelia
2015-01-01
The present study investigates the internal structure of professional vision of in-service teachers and student teachers with respect to classroom management and learning support in primary science lessons. Classroom management (including monitoring, managing momentum, and rules and routines) and learning support (including cognitive activation…
Stochastic partial differential equations
Lototsky, Sergey V
2017-01-01
Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very active research discipline, this textbook provides all the necessary background from functional analysis and the theory of PDEs. It covers the main types of equations (elliptic, hyperbolic and parabolic) and discusses different types of random forcing. The objective is to give the reader the necessary tools to understand the proofs of existing theorems about SPDEs (from other sources) and perhaps even to formulate and prove a few new ones. Most of the material could be covered in about 40 hours of lectures, as long as not too much time is spent on the general discussion of stochastic analysis in infinite dimensions. As the subject of SPDEs is currently making the transition from the research level to that of a graduate or even undergraduate course, the book attempts to present enough exercise material to fill potential exams and homework assignments. Exercises appear throughout and are usually directly connected ...
Local cerebral metabolism during partial seizures
International Nuclear Information System (INIS)
Engel, J. Jr.; Kuhl, D.E.; Phelps, M.E.; Rausch, R.; Nuwer, M.
1983-01-01
Interictal and ictal fluorodeoxyglucose scans were obtained with positron CT from four patients with spontaneous recurrent partial seizures, one with epilepsia partialis continua, and one with a single partial seizure induced by electrical stimulation of the hippocampus. Ictal metabolic patterns were different for each patient studied. Focal and generalized increased and decreased metabolism were observed. Ictal hypermetabolism may exceed six times the interictal rate and could represent activation of excitatory or inhibitory synapses in the epileptogenic region and its projection fields. Hypometabolism seen on ictal scans most likely reflects postictal depression and may indicate projection fields of inhibited neurons. No quantitative relationship between alterations in metabolism and EEG or behavioral measurements of ictal events could be demonstrated
Local cerebral metabolism during partial seizures
Energy Technology Data Exchange (ETDEWEB)
Engel, J. Jr.; Kuhl, D.E.; Phelps, M.E.; Rausch, R.; Nuwer, M.
1983-04-01
Interictal and ictal fluorodeoxyglucose scans were obtained with positron CT from four patients with spontaneous recurrent partial seizures, one with epilepsia partialis continua, and one with a single partial seizure induced by electrical stimulation of the hippocampus. Ictal metabolic patterns were different for each patient studied. Focal and generalized increased and decreased metabolism were observed. Ictal hypermetabolism may exceed six times the interictal rate and could represent activation of excitatory or inhibitory synapses in the epileptogenic region and its projection fields. Hypometabolism seen on ictal scans most likely reflects postictal depression and may indicate projection fields of inhibited neurons. No quantitative relationship between alterations in metabolism and EEG or behavioral measurements of ictal events could be demonstrated.
Bactericidal activity of partially oxidized nanodiamonds.
Wehling, Julia; Dringen, Ralf; Zare, Richard N; Maas, Michael; Rezwan, Kurosch
2014-06-24
Nanodiamonds are a class of carbon-based nanoparticles that are rapidly gaining attention, particularly for biomedical applications, i.e., as drug carriers, for bioimaging, or as implant coatings. Nanodiamonds have generally been considered biocompatible with a broad variety of eukaryotic cells. We show that, depending on their surface composition, nanodiamonds kill Gram-positive and -negative bacteria rapidly and efficiently. We investigated six different types of nanodiamonds exhibiting diverse oxygen-containing surface groups that were created using standard pretreatment methods for forming nanodiamond dispersions. Our experiments suggest that the antibacterial activity of nanodiamond is linked to the presence of partially oxidized and negatively charged surfaces, specifically those containing acid anhydride groups. Furthermore, proteins were found to control the bactericidal properties of nanodiamonds by covering these surface groups, which explains the previously reported biocompatibility of nanodiamonds. Our findings describe the discovery of an exciting property of partially oxidized nanodiamonds as a potent antibacterial agent.
Stochastic partial differential equations an introduction
Liu, Wei
2015-01-01
This book provides an introduction to the theory of stochastic partial differential equations (SPDEs) of evolutionary type. SPDEs are one of the main research directions in probability theory with several wide ranging applications. Many types of dynamics with stochastic influence in nature or man-made complex systems can be modelled by such equations. The theory of SPDEs is based both on the theory of deterministic partial differential equations, as well as on modern stochastic analysis. Whilst this volume mainly follows the ‘variational approach’, it also contains a short account on the ‘semigroup (or mild solution) approach’. In particular, the volume contains a complete presentation of the main existence and uniqueness results in the case of locally monotone coefficients. Various types of generalized coercivity conditions are shown to guarantee non-explosion, but also a systematic approach to treat SPDEs with explosion in finite time is developed. It is, so far, the only book where the latter and t...
ONLINE SCIENCE LEARNING:Best Practices and Technologies
Directory of Open Access Journals (Sweden)
TOJDE
2009-04-01
Full Text Available This essential publication is for all research and academic libraries, especially those institutions with online and distance education courses available in their science education programs. This book will also benefit audiences within the science education community of practice and others interested in STEM education, virtual schools, e-learning, m-learning, natural sciences, physical sciences, biological sciences, geosciences, online learning models, virtual laboratories, virtual field trips, cyberinfrastructure, neurological learning and the neuro-cognitive model. The continued growth in general studies and liberal arts and science programs online has led to a rise in the number of students whose science learning experiences are partially or exclusively online. character and quality of online science instruction.
The Cousin problems in the viewpoint of partial differential equations
International Nuclear Information System (INIS)
Le Hung Son.
1990-01-01
In this paper we consider the Cousin problems for overdetermined systems of partial differential equations, which are generalizations of the Cauchy-Riemann system. The general methods for solving these problems are given. Applying the given methods we can solve the Cousin problems for many important systems in theoretical physics. (author). 19 refs
Partial Linearization of Mechanical Systems with Application to Observer Design
Sarras, Ioannis; Venkatraman, Aneesh; Ortega, Romeo; Schaft, Arjan van der
2008-01-01
We consider general mechanical systems and establish a necessary and sufficient condition for the existence of a suitable change in the generalized momentum coordinates such that the new dynamics become linear in the transformed momenta. The class of systems which can be (partially) linearized by
26 CFR 48.4041-20 - Partially exempt methanol and ethanol fuel.
2010-04-01
... 26 Internal Revenue 16 2010-04-01 2010-04-01 true Partially exempt methanol and ethanol fuel. 48... Partially exempt methanol and ethanol fuel. (a) In general. Under section 4041(m), the sale or use of partially exempt methanol or ethanol fuel is taxed at the rate of 41/2 cents per gallon of fuel sold or used...
New approach to breast cancer CAD using partial least squares and kernel-partial least squares
Land, Walker H., Jr.; Heine, John; Embrechts, Mark; Smith, Tom; Choma, Robert; Wong, Lut
2005-04-01
Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of breast cancer, its positive predictive value (PPV) is low, resulting in biopsies that are only 15-34% likely to reveal malignancy. This paper explores the use of two novel approaches called Partial Least Squares (PLS) and Kernel-PLS (K-PLS) to the diagnosis of breast cancer. The approach is based on optimization for the partial least squares (PLS) algorithm for linear regression and the K-PLS algorithm for non-linear regression. Preliminary results show that both the PLS and K-PLS paradigms achieved comparable results with three separate support vector learning machines (SVLMs), where these SVLMs were known to have been trained to a global minimum. That is, the average performance of the three separate SVLMs were Az = 0.9167927, with an average partial Az (Az90) = 0.5684283. These results compare favorably with the K-PLS paradigm, which obtained an Az = 0.907 and partial Az = 0.6123. The PLS paradigm provided comparable results. Secondly, both the K-PLS and PLS paradigms out performed the ANN in that the Az index improved by about 14% (Az ~ 0.907 compared to the ANN Az of ~ 0.8). The "Press R squared" value for the PLS and K-PLS machine learning algorithms were 0.89 and 0.9, respectively, which is in good agreement with the other MOP values.
Physics of partially ionized plasmas
Krishan, Vinod
2016-01-01
Plasma is one of the four fundamental states of matter; the other three being solid, liquid and gas. Several components, such as molecular clouds, diffuse interstellar gas, the solar atmosphere, the Earth's ionosphere and laboratory plasmas, including fusion plasmas, constitute the partially ionized plasmas. This book discusses different aspects of partially ionized plasmas including multi-fluid description, equilibrium and types of waves. The discussion goes on to cover the reionization phase of the universe, along with a brief description of high discharge plasmas, tokomak plasmas and laser plasmas. Various elastic and inelastic collisions amongst the three particle species are also presented. In addition, the author demonstrates the novelty of partially ionized plasmas using many examples; for instance, in partially ionized plasma the magnetic induction is subjected to the ambipolar diffusion and the Hall effect, as well as the usual resistive dissipation. Also included is an observation of kinematic dynam...
Partially massless fields during inflation
Baumann, Daniel; Goon, Garrett; Lee, Hayden; Pimentel, Guilherme L.
2018-04-01
The representation theory of de Sitter space allows for a category of partially massless particles which have no flat space analog, but could have existed during inflation. We study the couplings of these exotic particles to inflationary perturbations and determine the resulting signatures in cosmological correlators. When inflationary perturbations interact through the exchange of these fields, their correlation functions inherit scalings that cannot be mimicked by extra massive fields. We discuss in detail the squeezed limit of the tensor-scalar-scalar bispectrum, and show that certain partially massless fields can violate the tensor consistency relation of single-field inflation. We also consider the collapsed limit of the scalar trispectrum, and find that the exchange of partially massless fields enhances its magnitude, while giving no contribution to the scalar bispectrum. These characteristic signatures provide clean detection channels for partially massless fields during inflation.
Introduction to partial differential equations
Greenspan, Donald
2000-01-01
Designed for use in a one-semester course by seniors and beginning graduate students, this rigorous presentation explores practical methods of solving differential equations, plus the unifying theory underlying the mathematical superstructure. Topics include basic concepts, Fourier series, second-order partial differential equations, wave equation, potential equation, heat equation, approximate solution of partial differential equations, and more. Exercises appear at the ends of most chapters. 1961 edition.
[Acrylic resin removable partial dentures].
de Baat, C; Witter, D J; Creugers, N H J
2011-01-01
An acrylic resin removable partial denture is distinguished from other types of removable partial dentures by an all-acrylic resin base which is, in principle, solely supported by the edentulous regions of the tooth arch and in the maxilla also by the hard palate. When compared to the other types of removable partial dentures, the acrylic resin removable partial denture has 3 favourable aspects: the economic aspect, its aesthetic quality and the ease with which it can be extended and adjusted. Disadvantages are an increased risk of caries developing, gingivitis, periodontal disease, denture stomatitis, alveolar bone reduction, tooth migration, triggering of the gag reflex and damage to the acrylic resin base. Present-day indications are ofa temporary or palliative nature or are motivated by economic factors. Special varieties of the acrylic resin removable partial denture are the spoon denture, the flexible denture fabricated of non-rigid acrylic resin, and the two-piece sectional denture. Furthermore, acrylic resin removable partial dentures can be supplied with clasps or reinforced by fibers or metal wires.
Teacher learning as workplace learning
Imants, J.; Van Veen, K.
2010-01-01
Against the background of increasing attention in teacher professional development programs for situating teacher learning in the workplace, an overview is given of what is known in general and in educational workplace learning literature on the characteristics and conditions of the workplace.
Overlaps of partial Néel states and Bethe states
International Nuclear Information System (INIS)
Foda, O; Zarembo, K
2016-01-01
Partial Néel states are generalizations of the ordinary Néel (classical anti-ferromagnet) state that can have arbitrary integer spin. We study overlaps of these states with Bethe states. We first identify this overlap with a partial version of reflecting-boundary domain-wall partition function, and then derive various determinant representations for off-shell and on-shell Bethe states. (paper: quantum statistical physics, condensed matter, integrable systems)
Numerical Analysis for Stochastic Partial Differential Delay Equations with Jumps
Li, Yan; Hu, Junhao
2013-01-01
We investigate the convergence rate of Euler-Maruyama method for a class of stochastic partial differential delay equations driven by both Brownian motion and Poisson point processes. We discretize in space by a Galerkin method and in time by using a stochastic exponential integrator. We generalize some results of Bao et al. (2011) and Jacob et al. (2009) in finite dimensions to a class of stochastic partial differential delay equations with jumps in infinite dimensions.
Toprak, Fatih; Çelikler, Dilek
2013-01-01
The study aimed to investigate the emerging changes in prospective science teachers" attitudes and perceptions towards science, chemistry and laboratory resulting from the implementation of 3E. 5E learning cycles and traditional instruction in laboratory environment in which learning is achieved by doing and experiencing. The study included 74 first grade prospective science teachers from Ondokuz Mayıs University at the Department of Science Education. In the study, quasi-experimental pre-tes...
Toprak, Fatih; Çelikler, Dilek
2013-01-01
The study aimed to investigate the emerging changes in prospective science teachers" attitudes and perceptions towards science, chemistry and laboratory resulting from the implementation of 3E. 5E learning cycles and traditional instruction in laboratory environment in which learning is achieved by doing and experiencing. The study included 74 first grade prospective science teachers from Ondokuz Mayıs University at the Department of Science Education. In the study, quasi-experimental pr...
Nonlinear partial differential equations of second order
Dong, Guangchang
1991-01-01
This book addresses a class of equations central to many areas of mathematics and its applications. Although there is no routine way of solving nonlinear partial differential equations, effective approaches that apply to a wide variety of problems are available. This book addresses a general approach that consists of the following: Choose an appropriate function space, define a family of mappings, prove this family has a fixed point, and study various properties of the solution. The author emphasizes the derivation of various estimates, including a priori estimates. By focusing on a particular approach that has proven useful in solving a broad range of equations, this book makes a useful contribution to the literature.
ERC Workshop on Geometric Partial Differential Equations
Novaga, Matteo; Valdinoci, Enrico
2013-01-01
This book is the outcome of a conference held at the Centro De Giorgi of the Scuola Normale of Pisa in September 2012. The aim of the conference was to discuss recent results on nonlinear partial differential equations, and more specifically geometric evolutions and reaction-diffusion equations. Particular attention was paid to self-similar solutions, such as solitons and travelling waves, asymptotic behaviour, formation of singularities and qualitative properties of solutions. These problems arise in many models from Physics, Biology, Image Processing and Applied Mathematics in general, and have attracted a lot of attention in recent years.
ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.
Kim, Seongho
2015-11-01
Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.
Categorization = Decision Making + Generalization
Seger, Carol A; Peterson, Erik J.
2013-01-01
We rarely, if ever, repeatedly encounter exactly the same situation. This makes generalization crucial for real world decision making. We argue that categorization, the study of generalizable representations, is a type of decision making, and that categorization learning research would benefit from approaches developed to study the neuroscience of decision making. Similarly, methods developed to examine generalization and learning within the field of categorization may enhance decision making research. We first discuss perceptual information processing and integration, with an emphasis on accumulator models. We then examine learning the value of different decision making choices via experience, emphasizing reinforcement learning modeling approaches. Next we discuss how value is combined with other factors in decision making, emphasizing the effects of uncertainty. Finally, we describe how a final decision is selected via thresholding processes implemented by the basal ganglia and related regions. We also consider how memory related functions in the hippocampus may be integrated with decision making mechanisms and contribute to categorization. PMID:23548891
Directory of Open Access Journals (Sweden)
Sabina Jelenc Krašovec
2000-12-01
Full Text Available A vast array of economical, social, political, cultural and other factors influences the transformed role of learning and education in the society, as well as the functioning of local community and its social and communication patterns. The influences which are manifested as global problems can only be successfully solved on the level of local community. Analogously with the society in general, there is a great need of transforming a local community into a learning, flexible and interconnected environment which takes into account different interests, wishes and needs regarding learning and being active. The fundamental answer to changes is the strategy of lifelong learning and education which requires reorganisation of all walks of life (work, free time, family, mass media, culture, sport, education and transforming of organisations into learning organisations. With learning society based on networks of knowledge individuals are turning into learning individuals, and organisations into learning organisations; people who learn take the responsibility of their progress, learning denotes partnership among learning people, teachers, parents, employers and local community, so that they work together to achieve better results.
Directory of Open Access Journals (Sweden)
Noé Chávez Hernández
2012-12-01
Full Text Available This article provides an overview of the important aspects to be considered within learning organizations focused on continuous learning at the individual, group and organizational level, in order to develop the necessary competences and face their environment in a competitive way. This article aims to present several topics covered, from its introduction and identification of knowledge attributes and learning, until what is an intelligent organization, the structural design to be adopted as well as the skills of management to be implemented. The intention of this paper is to contribute to the stock of current theoretical information that serves as a reference for the practical research of the academics.Este artículo es un estudio de los aspectos que deben ser considerados dentro de las organizaciones inteligentes cuyo enfoque se centra en el aprendizaje constante (tanto individual como organizacional como una estrategia para desarrollar las competencias que les permitan enfrentar el entorno de una manera competitiva. Al exponer dichas temáticas, desde la presentación e identificación de las características del conocimiento y el aprendizaje dentro de una organización inteligente, hasta el diseño estructural a adoptar y las habilidades de gestión gerencial a ejecutar, nuestra intención es contribuir a la aplicación del conocimiento dentro del ámbito de la gestión empresarial.
1999-01-01
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 ...