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Sample records for learning generalized partially

  1. Generalizing the order and the parameters of macro-operators by explanation-based learning - Extension of Explanation-Based Learning on Partial Order

    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

  2. Partially Observed Mixtures of IRT Models: An Extension of the Generalized Partial-Credit Model

    Science.gov (United States)

    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…

  3. 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)

  4. 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)

  5. Generalized Partial Volume

    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....

  6. Testing the generalized partial credit model

    NARCIS (Netherlands)

    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

  7. Generalized solutions of nonlinear partial differential equations

    CERN Document Server

    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

  8. Testing the generalized partial credit model

    OpenAIRE

    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...

  9. Partial fingerprint identification algorithm based on the modified generalized Hough transform on mobile device

    Science.gov (United States)

    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.

  10. 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...

  11. 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.

  12. Hidden physics models: Machine learning of nonlinear partial differential equations

    Science.gov (United States)

    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.

  13. A Generalized Partial Credit Model: Application of an EM Algorithm.

    Science.gov (United States)

    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)

  14. Context generalization in Drosophila visual learning requires the mushroom bodies

    Science.gov (United States)

    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.

  15. Constructing general partial differential equations using polynomial and neural networks.

    Science.gov (United States)

    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.

  16. 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....

  17. 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.)

  18. 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.)

  19. Topographic generalization of tactile perceptual learning.

    Science.gov (United States)

    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.

  20. Optimal Designs for the Generalized Partial Credit Model

    OpenAIRE

    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...

  1. 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.

  2. Domain general constraints on statistical learning.

    Science.gov (United States)

    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.

  3. Generalized SMO algorithm for SVM-based multitask learning.

    Science.gov (United States)

    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.

  4. Recent progresses of neural network unsupervised learning: I. Independent component analyses generalizing PCA

    Science.gov (United States)

    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

  5. Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

    Science.gov (United States)

    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.

  6. General formalism for partial spatial coherence in reflection Mueller matrix polarimetry.

    Science.gov (United States)

    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.

  7. Path integral solution of linear second order partial differential equations I: the general construction

    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

  8. Shared learning in general practice--facilitators and barriers.

    Science.gov (United States)

    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.

  9. Implementing E-Learning Designed Courses in General Education

    Science.gov (United States)

    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…

  10. Learning styles of medical students, general surgery residents, and general surgeons: implications for surgical education.

    Science.gov (United States)

    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.

  11. 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...

  12. Learning styles of medical students, general surgery residents, and general surgeons: implications for surgical education

    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.

  13. Doubly robust estimation of generalized partial linear models for longitudinal data with dropouts.

    Science.gov (United States)

    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.

  14. Learning environment, approaches to learning and learning preferences: medical students versus general education students.

    Science.gov (United States)

    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.

  15. Learning partial differential equations via data discovery and sparse optimization.

    Science.gov (United States)

    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.

  16. The Relationship between Feelings-of-Knowing and Partial Knowledge for General Knowledge Questions.

    Science.gov (United States)

    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.

  17. 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".

  18. Informal and Formal Learning of General Practitioners

    Science.gov (United States)

    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…

  19. General Video Game AI: Learning from Screen Capture

    OpenAIRE

    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...

  20. Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data

    KAUST Repository

    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

  1. The generalized tanh method to obtain exact solutions of nonlinear partial differential equation

    OpenAIRE

    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.

  2. BOOK REVIEW: Partial Differential Equations in General Relativity

    Science.gov (United States)

    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

  3. Informal and formal learning of general practitioners

    NARCIS (Netherlands)

    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

  4. Gradient descent learning algorithm overview: a general dynamical systems perspective.

    Science.gov (United States)

    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.

  5. Logarithmic learning for generalized classifier neural network.

    Science.gov (United States)

    Ozyildirim, Buse Melis; Avci, Mutlu

    2014-12-01

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

  6. Domain-specific and domain-general constraints on word and sequence learning.

    Science.gov (United States)

    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.

  7. Stochastic abstract policies: generalizing knowledge to improve reinforcement learning.

    Science.gov (United States)

    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.

  8. Learning general phonological rules from distributional information: a computational model.

    Science.gov (United States)

    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.

  9. Partial relay selection based on shadowing side information over generalized composite fading channels

    KAUST Repository

    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.

  10. Evaluation of Team-Based Learning and Traditional Instruction in Teaching Removable Partial Denture Concepts.

    Science.gov (United States)

    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.

  11. 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)

  12. Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

    Science.gov (United States)

    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.

  13. 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

  14. Explaining Compound Generalization in Associative and Causal Learning Through Rational Principles of Dimensional Generalization

    Science.gov (United States)

    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

  15. A Comparison of Item Exposure Control Procedures with the Generalized Partial Credit Model

    Science.gov (United States)

    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…

  16. Learning Spaces

    CERN Document Server

    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

  17. Relationship between motivational goal orientations, perceptions of general education classroom learning environment, and deep approaches to learning

    OpenAIRE

    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...

  18. New Generalized Hyperbolic Functions to Find New Exact Solutions of the Nonlinear Partial Differential Equations

    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.

  19. Sleep restores loss of generalized but not rote learning of synthetic speech.

    Science.gov (United States)

    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.

  20. Generalization of perceptual and motor learning: a causal link with memory encoding and consolidation?

    Science.gov (United States)

    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.

  1. Estimation and variable selection for generalized additive partial linear models

    KAUST Repository

    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.

  2. Generalized concentration addition: a method for examining mixtures containing partial agonists.

    Science.gov (United States)

    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.

  3. An appraisal of the learning curve in robotic general surgery.

    Science.gov (United States)

    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.

  4. 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.

  5. Applying a Weighted Maximum Likelihood Latent Trait Estimator to the Generalized Partial Credit Model

    Science.gov (United States)

    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…

  6. Design and validation of general biology learning program based on scientific inquiry skills

    Science.gov (United States)

    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.

  7. Contingency learning deficits and generalization in chronic unilateral hand pain patients.

    Science.gov (United States)

    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

  8. An Investigative, Cooperative Learning Approach to the General Microbiology Laboratory

    Science.gov (United States)

    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…

  9. Development and Assessment of Service Learning Projects in General Biology

    Science.gov (United States)

    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…

  10. Personality characteristics and their connection with learning efficiency of deaf and partially deaf pupils in mainstream primary and secondary school

    OpenAIRE

    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 ...

  11. Learning Theory Estimates with Observations from General Stationary Stochastic Processes.

    Science.gov (United States)

    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.

  12. Exploring Alternative Characteristic Curve Approaches to Linking Parameter Estimates from the Generalized Partial Credit Model.

    Science.gov (United States)

    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…

  13. Experimentally Induced Learned Helplessness: How Far Does it Generalize?

    Science.gov (United States)

    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)

  14. 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.

  15. Learning and generalization from reward and punishment in opioid addiction.

    Science.gov (United States)

    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.

  16. Generalized query-based active learning to identify differentially methylated regions in DNA.

    Science.gov (United States)

    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.

  17. Strategies for Controlling Item Exposure in Computerized Adaptive Testing with the Generalized Partial Credit Model

    Science.gov (United States)

    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…

  18. Generalized multiple kernel learning with data-dependent priors.

    Science.gov (United States)

    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.

  19. Generalized least squares and empirical Bayes estimation in regional partial duration series index-flood modeling

    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...

  20. Special Education in General Education Classrooms: Cooperative Teaching Using Supportive Learning Activities.

    Science.gov (United States)

    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.…

  1. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    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.

  2. Discriminative Transfer Learning for General Image Restoration

    KAUST Repository

    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.

  3. 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)

  4. Learning and generalization errors for the 2D binary perceptron

    NARCIS (Netherlands)

    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

  5. 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

  6. Parent Ratings of ADHD Symptoms: Generalized Partial Credit Model Analysis of Differential Item Functioning across Gender

    Science.gov (United States)

    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…

  7. The Learning Preferences of Applicants Who Interview for General Surgery Residency: A Multiinstitutional Study.

    Science.gov (United States)

    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

  8. Learning with partially labeled and interdependent data

    CERN Document Server

    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

  9. Mirror neuron activation as a function of explicit learning: changes in mu-event-related power after learning novel responses to ideomotor compatible, partially compatible, and non-compatible stimuli.

    Science.gov (United States)

    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.

  10. Learning strategies and general cognitive ability as predictors of gender- specific academic achievement.

    Science.gov (United States)

    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.

  11. General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures

    OpenAIRE

    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...

  12. 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.

  13. Relationship between Motivation for Learning EFL and Intrinsic Motivation for Learning in General among Japanese Elementary School Students

    Science.gov (United States)

    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…

  14. A Multidimensional Partial Credit Model with Associated Item and Test Statistics: An Application to Mixed-Format Tests

    Science.gov (United States)

    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…

  15. A Study of Reverse-Worded Matched Item Pairs Using the Generalized Partial Credit and Nominal Response Models

    Science.gov (United States)

    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…

  16. Learning in neural networks based on a generalized fluctuation theorem

    Science.gov (United States)

    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.

  17. General Information about Learning Disabilities (Fact Sheet Number 7) = Informacion General sobre Impedimentos en el Aprendizaje (Fact Sheet Number 19).

    Science.gov (United States)

    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…

  18. Problem-Based Learning in a General Psychology Course.

    Science.gov (United States)

    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.)…

  19. Recurrent Partial Words

    Directory of Open Access Journals (Sweden)

    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.

  20. Computer use changes generalization of movement learning.

    Science.gov (United States)

    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.

  1. Vertical Integration in Teaching And Learning (VITAL): an approach to medical education in general practice.

    Science.gov (United States)

    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.

  2. Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data

    KAUST Repository

    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.

  3. Generalization bounds of ERM-based learning processes for continuous-time Markov chains.

    Science.gov (United States)

    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.

  4. Application of Generalized Hukuhara derivative approach in an economic production quantity model with partial trade credit policy under fuzzy environment

    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.

  5. Regional estimation of rainfall intensity-duration-frequency curves using generalized least squares regression of partial duration series statistics

    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...

  6. Diffusion of an e-learning programme among Danish General Practitioners: A nation-wide prospective survey

    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.

  7. Biodynamic feedback training to assure learning partial load bearing on forearm crutches.

    Science.gov (United States)

    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.

  8. 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.

  9. 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

  10. 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.

  11. How do general practice residents use social networking sites in asynchronous distance learning?

    Science.gov (United States)

    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.

  12. A Learning Trajectory in 6-Year-Olds' Thinking about Generalizing Functional Relationships

    Science.gov (United States)

    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…

  13. Partial differential equations & boundary value problems with Maple

    CERN Document Server

    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...

  14. 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.

  15. Partial Deconvolution with Inaccurate Blur Kernel.

    Science.gov (United States)

    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

  16. Workplace learning from a socio-cultural perspective: creating developmental space during the general practice clerkship.

    Science.gov (United States)

    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.

  17. A Comparison of Item Selection Techniques and Exposure Control Mechanisms in CATs Using the Generalized Partial Credit Model.

    Science.gov (United States)

    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…

  18. The use of an active learning approach in a SCALE-UP learning space improves academic performance in undergraduate General Biology.

    Science.gov (United States)

    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.

  19. [E-Learning--an important contribution to general medical training and continuing education?].

    Science.gov (United States)

    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.

  20. Impact of eLearning Perception and eLearning Advantages on eLearning for Stress Management (Mediating Role of eLearning for Corporate Training

    Directory of Open Access Journals (Sweden)

    Aamir Sarwar

    2015-08-01

    Full Text Available The objective of the study was to develop a model with and without the mediator comparing direct and indirect Impacts using Bootstrap (Two tailed significance results to be used, options for manufacturing, services sectors and overall and finding out the significance of the relationship. Study tried to find out the Impact of eLearning Perception and eLearning Advantages on eLearning for Stress Management with eLearning for Corporate Training as a mediator. This is a cross sectional study conducted in Pakistan. Detailed questionnaire was used to collect the data. Total sample size of 686 includes 331 from manufacturing sector and 355 from services sector. Study revealed that overall eLearning for corporate training partially mediates relationship between eLearning Perception and elearning for stress management. However, in subgroup of manufacturing sector full mediation is observed. eLearning for corporate training partially mediates relationship between eLearning Advantages and Stress management training. Similar partial mediation is observed for subgroups of manufacturing and services sector. However in subgroup of manufacturing sector no mediation was observed.

  1. Out-of-Sample Generalizations for Supervised Manifold Learning for Classification.

    Science.gov (United States)

    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.

  2. The relationship between learning mathematics and general cognitive ability in primary school.

    Science.gov (United States)

    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.

  3. Extreme learning machine for ranking: generalization analysis and applications.

    Science.gov (United States)

    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.

  4. The impact of category structure and training methodology on learning and generalizing within-category representations.

    Science.gov (United States)

    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.

  5. Team-Based Learning Reduces Attrition in a First-Semester General Chemistry Course

    Science.gov (United States)

    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…

  6. Benefits and harms of general health checks- lifelong learning in general practice: how to read and use scientific literature

    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...

  7. Strategic trade between two regions with partial local consumer protection - General setup and nash equilibria

    Science.gov (United States)

    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.

  8. General practitioners learning qualitative research: A case study of postgraduate education.

    Science.gov (United States)

    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.

  9. Stress before extinction learning enhances and generalizes extinction memory in a predictive learning task.

    Science.gov (United States)

    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.

  10. Robotic partial nephrectomy - Evaluation of the impact of case mix on the procedural learning curve.

    Science.gov (United States)

    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.

  11. On A Nonlinear Generalization of Sparse Coding and Dictionary Learning.

    Science.gov (United States)

    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.

  12. 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

  13. The partial-reinforcement extinction effect and the contingent-sampling hypothesis.

    Science.gov (United States)

    Hochman, Guy; Erev, Ido

    2013-12-01

    The partial-reinforcement extinction effect (PREE) implies that learning under partial reinforcements is more robust than learning under full reinforcements. While the advantages of partial reinforcements have been well-documented in laboratory studies, field research has failed to support this prediction. In the present study, we aimed to clarify this pattern. Experiment 1 showed that partial reinforcements increase the tendency to select the promoted option during extinction; however, this effect is much smaller than the negative effect of partial reinforcements on the tendency to select the promoted option during the training phase. Experiment 2 demonstrated that the overall effect of partial reinforcements varies inversely with the attractiveness of the alternative to the promoted behavior: The overall effect is negative when the alternative is relatively attractive, and positive when the alternative is relatively unattractive. These results can be captured with a contingent-sampling model assuming that people select options that provided the best payoff in similar past experiences. The best fit was obtained under the assumption that similarity is defined by the sequence of the last four outcomes.

  14. Partial differential equations for scientists and engineers

    CERN Document Server

    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

  15. A Vowel Is a Vowel: Generalizing Newly Learned Phonotactic Constraints to New Contexts

    Science.gov (United States)

    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…

  16. Distributed Systems of Generalizing as the Basis of Workplace Learning

    Science.gov (United States)

    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.…

  17. Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants.

    Science.gov (United States)

    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

  18. Effect of Formative Quizzes on Teacher Candidates’ Learning in General Chemistry

    OpenAIRE

    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...

  19. A General Semi-Analytical Solution for Three Types of Well Tests in Confined Aquifers with a Partially Penetrating Well

    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.

  20. 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.

  1. 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

  2. Clinical Evaluation of Periodontal Tissue Status in Prosthodontic Treatment of Patients with Partial Tooth Loss and Generalized Periodontitis

    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

  3. Distributing learning over time: the spacing effect in children's acquisition and generalization of science concepts.

    Science.gov (United States)

    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.

  4. In-Course Instructor-Guided Service Learning in a Community College General Psychology Class

    Science.gov (United States)

    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,…

  5. New approach to breast cancer CAD using partial least squares and kernel-partial least squares

    Science.gov (United States)

    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.

  6. An investigative, cooperative learning approach to the general microbiology laboratory.

    Science.gov (United States)

    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.

  7. An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel

    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.

  8. Non-linear partial differential equations an algebraic view of generalized solutions

    CERN Document Server

    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

  9. 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.

  10. When You've Seen One, Have You Seen Them All? Children's Memory for General and Specific Learning Episodes

    Science.gov (United States)

    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…

  11. Evolution of arbitrary moments of radiant intensity distribution for partially coherent general beams in atmospheric turbulence

    Science.gov (United States)

    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.

  12. General relativity in upper secondary school: Design and evaluation of an online learning environment using the model of educational reconstruction

    Science.gov (United States)

    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.

  13. Partial rectangular metric spaces and fixed point theorems.

    Science.gov (United States)

    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.

  14. Effects of conventional and problem-based learning on clinical and general competencies and career development

    NARCIS (Netherlands)

    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.

  15. Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption

    OpenAIRE

    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...

  16. Generalized Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions

    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...

  17. Photogenic partial seizures.

    Science.gov (United States)

    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.

  18. A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

    Science.gov (United States)

    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.

  19. Examining the Effectiveness of a Semi-Self-Paced Flipped Learning Format in a College General Chemistry Sequence

    Science.gov (United States)

    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…

  20. Suggestions for Modifications in the Teaching of General Chemistry to Accommodate Learning Disabled Students: Alternative Techniques for Teaching General Chemistry to Learning Disabled Students in the University.

    Science.gov (United States)

    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…

  1. 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.

  2. ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients.

    Science.gov (United States)

    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.

  3. Job-demand for learning and job-related learning: the mediating effect of job performance improvement initiatives

    OpenAIRE

    Loon, M; Bartram, T

    2007-01-01

    This study examined whether job-performance-improvementinitiatives mediate the relationship between individuals’ job-demand for learning and job-related learning. Data were obtained from 115 full-time\\ud employees in a diverse range of occupations. A partial least squares analysis revealed that job-performance-improvement-initiatives mediate partially the effects of job-demand for learning on job-related learning. Several implications\\ud for future research and policy are drawn from the findi...

  4. 48 CFR 49.109-5 - Partial settlements.

    Science.gov (United States)

    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...

  5. Child first language and adult second language are both tied to general-purpose learning systems.

    Science.gov (United States)

    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.

  6. On the relation between elementary partial difference equations and partial differential equations

    NARCIS (Netherlands)

    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

  7. Compiling a register of patients with moderate or severe learning disabilities: experience at one United Kingdom general practice

    Science.gov (United States)

    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

  8. Compiling a register of patients with moderate or severe learning disabilities: experience at one United Kingdom general practice.

    Science.gov (United States)

    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.

  9. The influence of experiential learning on medical equipment adoption in general practices.

    Science.gov (United States)

    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.

  10. 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...

  11. How do general practice registrars learn from their clinical experience? A critical incident study.

    Science.gov (United States)

    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.

  12. Factors Affecting the Integration of Information Literacy in the Teaching and Learning Processes of General Education Courses

    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.

  13. Universal Partial Words over Non-Binary Alphabets

    OpenAIRE

    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 ...

  14. Superior Generalization Capability of Hardware-Learing Algorithm Developed for Self-Learning Neuron-MOS Neural Networks

    Science.gov (United States)

    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.

  15. Variance Function Partially Linear Single-Index Models1.

    Science.gov (United States)

    Lian, Heng; Liang, Hua; Carroll, Raymond J

    2015-01-01

    We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

  16. Generalized polygons

    CERN Document Server

    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...

  17. Partial gigantism

    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.

  18. Infants' Learning, Memory, and Generalization of Learning for Bimodal Events.

    Science.gov (United States)

    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…

  19. Selective Attention is a Primary Determinant of the Relationship between Working Memory and General Learning Ability in Outbred Mice

    Science.gov (United States)

    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…

  20. Soliton solution for nonlinear partial differential equations by cosine-function method

    International Nuclear Information System (INIS)

    Ali, A.H.A.; Soliman, A.A.; Raslan, K.R.

    2007-01-01

    In this Letter, we established a traveling wave solution by using Cosine-function algorithm for nonlinear partial differential equations. The method is used to obtain the exact solutions for five different types of nonlinear partial differential equations such as, general equal width wave equation (GEWE), general regularized long wave equation (GRLW), general Korteweg-de Vries equation (GKdV), general improved Korteweg-de Vries equation (GIKdV), and Coupled equal width wave equations (CEWE), which are the important soliton equations

  1. Elements of partial differential equations

    CERN Document Server

    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

  2. Extinction of Conditioned Fear is Better Learned and Recalled in the Morning than in the Evening

    OpenAIRE

    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...

  3. Working memory training mostly engages general-purpose large-scale networks for learning.

    Science.gov (United States)

    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.

  4. Generalization of Auditory Sensory and Cognitive Learning in Typically Developing Children.

    Directory of Open Access Journals (Sweden)

    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.

  5. Generalization of Auditory Sensory and Cognitive Learning in Typically Developing Children.

    Science.gov (United States)

    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.

  6. Two cases of partial trisomy 4p and partial trisomy 14q.

    Science.gov (United States)

    Kim, Yeo-Hyang; Kim, Heung-Sik; Ryoo, Nam-Hee; Ha, Jung-Sook

    2013-01-01

    We present clinical and cytogenetic data on 2 cases of partial trisomy 4p and partial trisomy 14q. Both patients had an extra der(14)t(4;14)(p15.31;q12) chromosome due to a 3:1 segregation from a balanced translocation carrier mother. Array analyses indicated that their chromosomal breakpoints were similar, but there was no relationship between the 2 families. Both patients showed prominent growth retardation and psychomotor developmental delay. Other phenotypic manifestations were generally mild and variable; for example, patient 1 had a short palpebral fissure and low-set ears whereas patient 2 had a round face, asymmetric eyes, small ears, a short neck, finger/toe abnormalities, and behavioral problems.

  7. 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

  8. An approach of partial control design for system control and synchronization

    International Nuclear Information System (INIS)

    Hu Wuhua; Wang Jiang; Li Xiumin

    2009-01-01

    In this paper, a general approach of partial control design for system control and synchronization is proposed. It turns control problems into simpler ones by reducing their control variables. This is realized by utilizing the dynamical relations between variables, which are described by the dynamical relation matrix and the dependence-influence matrix. By adopting partial control theory, the presented approach provides a simple and general way to stabilize systems to their partial or whole equilibriums, or to synchronize systems with their partial or whole states. Further, based on this approach, the controllers can be simplified. Two examples of synchronizing chaotic systems are given to illustrate its effectiveness.

  9. MRSA model of learning and adaptation: a qualitative study among the general public

    Science.gov (United States)

    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

  10. MRSA model of learning and adaptation: a qualitative study among the general public

    Directory of Open Access Journals (Sweden)

    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

  11. Making reasonable and achievable adjustments: the contributions of learning disability liaison nurses in 'Getting it right' for people with learning disabilities receiving general hospitals care.

    Science.gov (United States)

    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.

  12. Hamiltonian partial differential equations and applications

    CERN Document Server

    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.

  13. Image Reconstruction For Bioluminescence Tomography From Partial Measurement

    OpenAIRE

    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...

  14. Making ATLAS Data from CERN Accessible to the General Public: The Development and Evaluation of a Learning Resource in Experimental Particle Physics

    CERN Document Server

    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 ...

  15. Communication and mental health in general practice: physicians' self-perceived learning needs and self-efficacy

    OpenAIRE

    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.

  16. An application of programmatic assessment for learning (PAL) system for general practice training.

    Science.gov (United States)

    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.

  17. 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.

  18. 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.

  19. e-Learning Mathematics

    OpenAIRE

    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...

  20. The Development of Learning Activities in Srijanwittaya General Buddhist Scripture School: A Participatory Action Research

    Directory of Open Access Journals (Sweden)

    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”.

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

    Science.gov (United States)

    Cho, Sun-Joo; Goodwin, Amanda P

    2016-04-01

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

  2. 28 CFR 73.4 - Partial compliance not deemed compliance.

    Science.gov (United States)

    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...

  3. Preliminary effects of pagoclone, a partial GABAA agonist, on neuropsychological performance

    Directory of Open Access Journals (Sweden)

    Angela F Caveney

    2008-03-01

    Full Text Available Angela F Caveney1, Bruno Giordani1, George M Haig21Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA; 2Neurosciences Development, Abbott Laboratories, Abbott Park, IL, USAAbstract: Pagoclone is a novel cyclopyrrolone that acts as a partial GABAA receptor agonist. Preclinical studies suggest that pagoclone may have clinical utility as an anxiolytic agent, as well as a reduced incidence of side-effects. The present study was conducted to determine whether pagoclone would affect healthy individuals’ performances on neuropsychological measures as a function of dose within the projected therapeutic range. Twelve healthy adult subjects were randomly assigned to dosage groups in a 3-way crossover study. Participants were administered neuropsychological measures six hours following dosing on Day 1 and Day 6 of administration of the drug. Dose effects were noted on measures of alertness, learning, and memory and movement time. Significant effects were also noted on measures of alertness, learning and memory, information processing and psychomotor speed. Overall, the results of this small, preliminary study do not support a finding of behavioral toxicity for these doses of pagoclone. Rather, a pattern was found of transient and mild negative effects on learning and memory scores at the highest dose administered, though these changes were small and no longer evident by the sixth day of use.Keywords: pagoclone, cyclopyrrolone, neuropsychological, memory, generalized anxiety disorder

  4. A learning collaborative of CMHCs and CHCs to support integration of behavioral health and general medical care.

    Science.gov (United States)

    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.

  5. Assessing the relationship between latent inhibition and the partial reinforcement extinction effect in autoshaping with rats.

    Science.gov (United States)

    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.

  6. Promoting Active Learning in Calculus and General Physics through Interactive and Media-Enhanced Lectures

    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."

  7. Towards Robust and Accurate Multi-View and Partially-Occluded Face Alignment.

    Science.gov (United States)

    Xing, Junliang; Niu, Zhiheng; Huang, Junshi; Hu, Weiming; Zhou, Xi; Yan, Shuicheng

    2018-04-01

    Face alignment acts as an important task in computer vision. Regression-based methods currently dominate the approach to solving this problem, which generally employ a series of mapping functions from the face appearance to iteratively update the face shape hypothesis. One keypoint here is thus how to perform the regression procedure. In this work, we formulate this regression procedure as a sparse coding problem. We learn two relational dictionaries, one for the face appearance and the other one for the face shape, with coupled reconstruction coefficient to capture their underlying relationships. To deploy this model for face alignment, we derive the relational dictionaries in a stage-wised manner to perform close-loop refinement of themselves, i.e., the face appearance dictionary is first learned from the face shape dictionary and then used to update the face shape hypothesis, and the updated face shape dictionary from the shape hypothesis is in return used to refine the face appearance dictionary. To improve the model accuracy, we extend this model hierarchically from the whole face shape to face part shapes, thus both the global and local view variations of a face are captured. To locate facial landmarks under occlusions, we further introduce an occlusion dictionary into the face appearance dictionary to recover face shape from partially occluded face appearance. The occlusion dictionary is learned in a data driven manner from background images to represent a set of elemental occlusion patterns, a sparse combination of which models various practical partial face occlusions. By integrating all these technical innovations, we obtain a robust and accurate approach to locate facial landmarks under different face views and possibly severe occlusions for face images in the wild. Extensive experimental analyses and evaluations on different benchmark datasets, as well as two new datasets built by ourselves, have demonstrated the robustness and accuracy of our proposed

  8. 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.

  9. 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

  10. Clustering stocks using partial correlation coefficients

    Science.gov (United States)

    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.

  11. Reward-Modulated Hebbian Plasticity as Leverage for Partially Embodied Control in Compliant Robotics

    Science.gov (United States)

    Burms, Jeroen; Caluwaerts, Ken; Dambre, Joni

    2015-01-01

    In embodied computation (or morphological computation), part of the complexity of motor control is offloaded to the body dynamics. We demonstrate that a simple Hebbian-like learning rule can be used to train systems with (partial) embodiment, and can be extended outside of the scope of traditional neural networks. To this end, we apply the learning rule to optimize the connection weights of recurrent neural networks with different topologies and for various tasks. We then apply this learning rule to a simulated compliant tensegrity robot by optimizing static feedback controllers that directly exploit the dynamics of the robot body. This leads to partially embodied controllers, i.e., hybrid controllers that naturally integrate the computations that are performed by the robot body into a neural network architecture. Our results demonstrate the universal applicability of reward-modulated Hebbian learning. Furthermore, they demonstrate the robustness of systems trained with the learning rule. This study strengthens our belief that compliant robots should or can be seen as computational units, instead of dumb hardware that needs a complex controller. This link between compliant robotics and neural networks is also the main reason for our search for simple universal learning rules for both neural networks and robotics. PMID:26347645

  12. Precision attachment-retained removable partial dentures. Part 3. General practitioner results up to 2 years.

    Science.gov (United States)

    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.

  13. Triangular relationship between sleep spindle activity, general cognitive ability and the efficiency of declarative learning.

    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.

  14. Applying Universal Design for Learning and the Inclusion Spectrum for Students with Severe Disabilities in General Physical Education

    Science.gov (United States)

    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…

  15. Inquiry and Blended Learning Based Learning Material Development for Improving Student Achievement on General Physics I of Mathematics and Natural Science of State University of Medan

    Science.gov (United States)

    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…

  16. Expectation-maximization algorithms for learning a finite mixture of univariate survival time distributions from partially specified class values

    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.

  17. 26 CFR 48.4041-20 - Partially exempt methanol and ethanol fuel.

    Science.gov (United States)

    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...

  18. Individual and social learning processes involved in the acquisition and generalization of tool use in macaques

    Science.gov (United States)

    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

  19. 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

  20. Verbal memory functioning in recurrent depression during partial remission and remission-Brief report

    Directory of Open Access Journals (Sweden)

    Åsa eHammar

    2013-10-01

    Full Text Available The aim of the present study was to investigate verbal memory performance in a group of patients with remitted and partial remitted major depressive disorder. Thirty-one patients and 31 healthy matched controls were included in the study. Results from the California Verbal Learning Test show intact verbal memory performance in the patient group regarding learning, recall and recognition. However, patients had significantly poorer performance compared to healthy controls in immediate recall of the first trial in the verbal memory test. In conclusion, the patient group showed intact memory performance, when material is presented more than once. These findings indicate that memory performance in MDD patients with partial remission and remission benefit from repetition of material.

  1. Learning automaton newtork and its dynamics. Gakushu automaton network to sono dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Quan, F [Hiroshima-Denki Institute of Technology, Hiroshima (Jpaan); Unno, F; Hirata, H [Chiba Univ., Chiba (Japan)

    1991-10-20

    In order to construct a distributed processing system having learning automata as autonomous elements, a reinforcement learning network of the automaton is proposed and it{prime}s dynamics is investigated. In this paper, it is attempted to add another level of meaning to computational cooperativity by using a reinforcement learning network with generalized leaning automata. The collection of learning automata in the team situation acts as self-interested agents that work toward improving their performance with respect to their individual preference ordering. In the global state space of the network, the case of partially synchronous stochastic process is considered. In this case, the existence of mean field is shown and a reinforcement learning algorithm which can make the dynamics on the average reinforcement trajectory is presented. This algorithm is shown to have a high convergence speed as a result of a simple experiment. 14 refs., 9 figs.

  2. Utility of learning plans in general practice vocational training: a mixed-methods national study of registrar, supervisor, and educator perspectives.

    Science.gov (United States)

    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.

  3. Algorithms for Reinforcement Learning

    CERN Document Server

    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'

  4. Transferring and generalizing deep-learning-based neural encoding models across subjects.

    Science.gov (United States)

    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.

  5. The Evaluation of Students' Written Reflection on the Learning of General Chemistry Lab Experiment

    Science.gov (United States)

    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…

  6. Partial Information Community Detection in a Multilayer Network

    Science.gov (United States)

    2016-06-01

    26 3 Methodology 33 3.1 Topology of the Noordin Top Terrorist Network . . . . . . . . . . . . 33 3.2 Partial Information... Topology of Synthetic Network. . . . . . . . . . . . . . . . . . . 69 4.4 Four Discovery Algorithms Discovering Red Vertices in a Synthetic Network 72 4.5...without their expertise and analysis. I have been lucky enough to have learned from the wonderful faculty of Applied Mathe - matics Department at the Naval

  7. Directly assessing interpersonal RSA influences in the frequency domain: An illustration with generalized partial directed coherence.

    Science.gov (United States)

    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.

  8. Implicit sequence learning in deaf children with cochlear implants.

    Science.gov (United States)

    Conway, Christopher M; Pisoni, David B; Anaya, Esperanza M; Karpicke, Jennifer; Henning, Shirley C

    2011-01-01

    Deaf children with cochlear implants (CIs) represent an intriguing opportunity to study neurocognitive plasticity and reorganization when sound is introduced following a period of auditory deprivation early in development. Although it is common to consider deafness as affecting hearing alone, it may be the case that auditory deprivation leads to more global changes in neurocognitive function. In this paper, we investigate implicit sequence learning abilities in deaf children with CIs using a novel task that measured learning through improvement to immediate serial recall for statistically consistent visual sequences. The results demonstrated two key findings. First, the deaf children with CIs showed disturbances in their visual sequence learning abilities relative to the typically developing normal-hearing children. Second, sequence learning was significantly correlated with a standardized measure of language outcome in the CI children. These findings suggest that a period of auditory deprivation has secondary effects related to general sequencing deficits, and that disturbances in sequence learning may at least partially explain why some deaf children still struggle with language following cochlear implantation. © 2010 Blackwell Publishing Ltd.

  9. HDAC I inhibition in the dorsal and ventral hippocampus differentially modulates predator-odor fear learning and generalization.

    Science.gov (United States)

    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.

  10. Observations Of General Learning Patterns In An Upper-Level Thermal Physics Course

    Science.gov (United States)

    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.

  11. ON PARTIAL DIFFERENTIAL AND DIFFERENCE EQUATIONS WITH SYMMETRIES DEPENDING ON ARBITRARY FUNCTIONS

    Directory of Open Access Journals (Sweden)

    Giorgio Gubbiotti

    2016-06-01

    Full Text Available In this note we present some ideas on when Lie symmetries, both point and generalized, can depend on arbitrary functions. We show a few examples, both in partial differential and partial difference equations where this happens. Moreover we show that the infinitesimal generators of generalized symmetries depending on arbitrary functions, both for continuous and discrete equations, effectively play the role of master symmetries.

  12. 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...

  13. Partial Interference and Its Performance Impact on Wireless Multiple Access Networks

    Directory of Open Access Journals (Sweden)

    Lau WingCheong

    2010-01-01

    Full Text Available To determine the capacity of wireless multiple access networks, the interference among the wireless links must be accurately modeled. In this paper, we formalize the notion of the partial interference phenomenon observed in many recent wireless measurement studies and establish analytical models with tractable solutions for various types of wireless multiple access networks. In particular, we characterize the stability region of IEEE 802.11 networks under partial interference with two potentially unsaturated links numerically. We also provide a closed-form solution for the stability region of slotted ALOHA networks under partial interference with two potentially unsaturated links and obtain a partial characterization of the boundary of the stability region for the general M-link case. Finally, we derive a closed-form approximated solution for the stability region for general M-link slotted ALOHA system under partial interference effects. Based on our results, we demonstrate that it is important to model the partial interference effects while analyzing wireless multiple access networks. This is because such considerations can result in not only significant quantitative differences in the predicted system capacity but also fundamental qualitative changes in the shape of the stability region of the systems.

  14. How partial reinforcement of food cues affects the extinction and reacquisition of appetitive responses. A new model for dieting success?

    Science.gov (United States)

    van den Akker, Karolien; Havermans, Remco C; Bouton, Mark E; Jansen, Anita

    2014-10-01

    Animals and humans can easily learn to associate an initially neutral cue with food intake through classical conditioning, but extinction of learned appetitive responses can be more difficult. Intermittent or partial reinforcement of food cues causes especially persistent behaviour in animals: after exposure to such learning schedules, the decline in responding that occurs during extinction is slow. After extinction, increases in responding with renewed reinforcement of food cues (reacquisition) might be less rapid after acquisition with partial reinforcement. In humans, it may be that the eating behaviour of some individuals resembles partial reinforcement schedules to a greater extent, possibly affecting dieting success by interacting with extinction and reacquisition. Furthermore, impulsivity has been associated with less successful dieting, and this association might be explained by impulsivity affecting the learning and extinction of appetitive responses. In the present two studies, the effects of different reinforcement schedules and impulsivity on the acquisition, extinction, and reacquisition of appetitive responses were investigated in a conditioning paradigm involving food rewards in healthy humans. Overall, the results indicate both partial reinforcement schedules and, possibly, impulsivity to be associated with worse extinction performance. A new model of dieting success is proposed: learning histories and, perhaps, certain personality traits (impulsivity) can interfere with the extinction and reacquisition of appetitive responses to food cues and they may be causally related to unsuccessful dieting. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Repeated Strains, Social Control, Social Learning, and Delinquency: Testing an Integrated Model of General Strain Theory in China

    Science.gov (United States)

    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…

  16. 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 ...

  17. Learning to spell from reading: general knowledge about spelling patterns influences memory for specific words.

    Science.gov (United States)

    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.

  18. Role of different colours of aposematic insects in learning, memory and generalization of naive bird predators

    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

  19. 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...

  20. Improving Neuromuscular Monitoring and Reducing Residual Neuromuscular Blockade With E-Learning

    DEFF Research Database (Denmark)

    Thomsen, Jakob Louis Demant; Mathiesen, Ole; Hägi-Pedersen, Daniel

    2017-01-01

    BACKGROUND: Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Residual neuromuscular blockade occurs when the patient is still partially paralyzed when awakened after surgery. The condition is associated with subjective discomfort and an......-learning module can increase anesthetists' use of neuromuscular monitoring. TRIAL REGISTRATION: Clinicaltrials.gov NCT02925143; https://clinicaltrials.gov/ct2/show/NCT02925143 (Archived by WebCite® at http://www.webcitation.org/6s50iTV2x)....

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

    Science.gov (United States)

    Wei, Qinglai; Li, Benkai; Song, Ruizhuo

    2018-04-01

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

  2. Improved probabilistic inference as a general learning mechanism with action video games.

    Science.gov (United States)

    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.

  3. Differentiating Instruction for Students with Learning Disabilities: Best Teaching Practices for General and Special Educators.

    Science.gov (United States)

    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…

  4. Partial differential equations in several complex variables

    CERN Document Server

    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 ...

  5. Generalised partial autocorrelations and the mutual information between past and future

    DEFF Research Database (Denmark)

    Proietti, Tommaso; Luati, Alessandra

    the generalized partial autocorrelations as the partial autocorrelation coefficients of an auxiliary process, we derive their properties and relate them to essential features of the original process. Based on a parameterisation suggested by Barndorff-Nielsen and Schou (1973) and on Whittle likelihood, we develop...

  6. Teach Astronomy: An Online Resource for General Education and Informal Learning

    Science.gov (United States)

    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.

  7. Separation of time-based and trial-based accounts of the partial reinforcement extinction effect.

    Science.gov (United States)

    Bouton, Mark E; Woods, Amanda M; Todd, Travis P

    2014-01-01

    Two appetitive conditioning experiments with rats examined time-based and trial-based accounts of the partial reinforcement extinction effect (PREE). In the PREE, the loss of responding that occurs in extinction is slower when the conditioned stimulus (CS) has been paired with a reinforcer on some of its presentations (partially reinforced) instead of every presentation (continuously reinforced). According to a time-based or "time-accumulation" view (e.g., Gallistel and Gibbon, 2000), the PREE occurs because the organism has learned in partial reinforcement to expect the reinforcer after a larger amount of time has accumulated in the CS over trials. In contrast, according to a trial-based view (e.g., Capaldi, 1967), the PREE occurs because the organism has learned in partial reinforcement to expect the reinforcer after a larger number of CS presentations. Experiment 1 used a procedure that equated partially and continuously reinforced groups on their expected times to reinforcement during conditioning. A PREE was still observed. Experiment 2 then used an extinction procedure that allowed time in the CS and the number of trials to accumulate differentially through extinction. The PREE was still evident when responding was examined as a function of expected time units to the reinforcer, but was eliminated when responding was examined as a function of expected trial units to the reinforcer. There was no evidence that the animal responded according to the ratio of time accumulated during the CS in extinction over the time in the CS expected before the reinforcer. The results thus favor a trial-based account over a time-based account of extinction and the PREE. This article is part of a Special Issue entitled: Associative and Temporal Learning. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. The learning curve of laparoscopic holecystectomy in general surgery resident training: old age of the patient may be a risk factor?

    Science.gov (United States)

    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

  9. General Education Oral Communication Assessment and Student Preferences for Learning: E-Textbook versus Paper Textbook

    Science.gov (United States)

    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…

  10. Robot-assisted partial nephrectomy in contemporary practice

    Energy Technology Data Exchange (ETDEWEB)

    Tanagho, Youssef S.; Bhayani, Sam B.; Figenshau, Robert S., E-mail: tanaghoy@wudosis.wustl.edu [Division of Urologic Surgery, Washington University School of Medicine, St. Louis, MO (United States)

    2013-01-11

    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 (LPN) is a minimally invasive, nephron-sparing alternative to laparoscopic radical nephrectomy (RN) for the management of small renal masses. While offering similar oncological outcomes to laparoscopic RN, the technical challenges and prolonged learning curve associated with LPN limit its wider dissemination. Robot-assisted partial nephrectomy (RAPN), although still an evolving procedure with no long-term data, has emerged as a viable alternative to LPN, with favorable preliminary outcomes. This article provides an overview of the role of RAPN 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 RAPN are also evaluated, as are complication rates.

  11. Robot-assisted partial nephrectomy in contemporary practice

    International Nuclear Information System (INIS)

    Tanagho, Youssef S.; Bhayani, Sam B.; Figenshau, Robert S.

    2013-01-01

    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 (LPN) is a minimally invasive, nephron-sparing alternative to laparoscopic radical nephrectomy (RN) for the management of small renal masses. While offering similar oncological outcomes to laparoscopic RN, the technical challenges and prolonged learning curve associated with LPN limit its wider dissemination. Robot-assisted partial nephrectomy (RAPN), although still an evolving procedure with no long-term data, has emerged as a viable alternative to LPN, with favorable preliminary outcomes. This article provides an overview of the role of RAPN 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 RAPN are also evaluated, as are complication rates.

  12. 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...

  13. Social Networks as Learning Environments for Higher Education

    Directory of Open Access Journals (Sweden)

    J.A.Cortés

    2014-09-01

    Full Text Available Learning is considered as a social activity, a student does not learn only of the teacher and the textbook or only in the classroom, learn also from many other agents related to the media, peers and society in general. And since the explosion of the Internet, the information is within the reach of everyone, is there where the main area of opportunity in new technologies applied to education, as well as taking advantage of recent socialization trends that can be leveraged to improve not only informing of their daily practices, but rather as a tool that explore different branches of education research. One can foresee the future of higher education as a social learning environment, open and collaborative, where people construct knowledge in interaction with others, in a comprehensive manner. The mobility and ubiquity that provide mobile devices enable the connection from anywhere and at any time. In modern educational environments can be expected to facilitate mobile devices in the classroom expansion in digital environments, so that students and teachers can build the teaching-learning process collectively, this partial derivative results in the development of draft research approved by the CONADI in “Universidad Cooperativa de Colombia”, "Social Networks: A teaching strategy in learning environments in higher education."

  14. Practice makes it better: A psychophysical study of visual perceptual learning and its transfer effects on aging.

    Science.gov (United States)

    Li, Xuan; Allen, Philip A; Lien, Mei-Ching; Yamamoto, Naohide

    2017-02-01

    Previous studies on perceptual learning, acquiring a new skill through practice, appear to stimulate brain plasticity and enhance performance (Fiorentini & Berardi, 1981). The present study aimed to determine (a) whether perceptual learning can be used to compensate for age-related declines in perceptual abilities, and (b) whether the effect of perceptual learning can be transferred to untrained stimuli and subsequently improve capacity of visual working memory (VWM). We tested both healthy younger and older adults in a 3-day training session using an orientation discrimination task. A matching-to-sample psychophysical method was used to measure improvements in orientation discrimination thresholds and reaction times (RTs). Results showed that both younger and older adults improved discrimination thresholds and RTs with similar learning rates and magnitudes. Furthermore, older adults exhibited a generalization of improvements to 3 untrained orientations that were close to the training orientation and benefited more compared with younger adults from the perceptual learning as they transferred learning effects to the VWM performance. We conclude that through perceptual learning, older adults can partially counteract age-related perceptual declines, generalize the learning effect to other stimulus conditions, and further overcome the limitation of using VWM capacity to perform a perceptual task. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  15. Trends in Research on Writing as a Learning Activity

    Directory of Open Access Journals (Sweden)

    Perry D. Klein

    2016-02-01

    Full Text Available This article discusses five trends in research on writing as a learning activity. Firstly, earlier decades were marked by conflicting views about the effects of writing on learning; in the past decade, the use of meta-analysis has shown that the effects of writing on learning are reliable, and that several variables mediate and moderate these effects. Secondly, in earlier decades, it was thought that text as a medium inherently elicited thinking and learning. Research during the past decade has indicated that writing to learn is a self-regulated activity, dependent on the goals and strategies of the writer. Thirdly, the Writing Across the Curriculum (WAC movement emphasized domain-general approaches to WTL. Much recent research is consistent with the Writing in the Disciplines (WID movement, incorporating genres that embody forms of reasoning specific to a given discipline. Fourthly, WTL as a classroom practice was always partially social, but the theoretical conceptualization of it was largely individual. During the past two decades, WTL has broadened to include theories and research that integrate social and psychological processes. Fifthly, WTL research has traditionally focused on epistemic learning in schools; more recently, it has been extended to include reflective learning in the professions and additional kinds of outcomes.

  16. Quality of communication and master impressions for the fabrication of cobalt chromium removable partial dentures in general dental practice in England, Ireland and Wales in 2009.

    Science.gov (United States)

    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.

  17. 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.

  18. Crichton ambiguities with infinitely many partial waves

    NARCIS (Netherlands)

    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

  19. 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)

  20. Beyond IQ: A Latent State-Trait Analysis of General Intelligence, Dynamic Decision Making, and Implicit Learning

    Science.gov (United States)

    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…

  1. Partial Linearization of Mechanical Systems with Application to Observer Design

    NARCIS (Netherlands)

    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

  2. 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

  3. 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.

  4. Do general practitioners' risk-taking propensities and learning styles influence their continuing medical education preferences?

    Science.gov (United States)

    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

  5. Partially converted stereoscopic images and the effects on visual attention and memory

    Science.gov (United States)

    Kim, Sanghyun; Morikawa, Hiroyuki; Mitsuya, Reiko; Kawai, Takashi; Watanabe, Katsumi

    2015-03-01

    This study contained two experimental examinations of the cognitive activities such as visual attention and memory in viewing stereoscopic (3D) images. For this study, partially converted 3D images were used with binocular parallax added to a specific region of the image. In Experiment 1, change blindness was used as a presented stimulus. The visual attention and impact on memory were investigated by measuring the response time to accomplish the given task. In the change blindness task, an 80 ms blank was intersected between the original and altered images, and the two images were presented alternatingly for 240 ms each. Subjects were asked to temporarily memorize the two switching images and to compare them, visually recognizing the difference between the two. The stimuli for four conditions (2D, 3D, Partially converted 3D, distracted partially converted 3D) were randomly displayed for 20 subjects. The results of Experiment 1 showed that partially converted 3D images tend to attract visual attention and are prone to remain in viewer's memory in the area where moderate negative parallax has been added. In order to examine the impact of a dynamic binocular disparity on partially converted 3D images, an evaluation experiment was conducted that applied learning, distraction, and recognition tasks for 33 subjects. The learning task involved memorizing the location of cells in a 5 × 5 matrix pattern using two different colors. Two cells were positioned with alternating colors, and one of the gray cells was moved up, down, left, or right by one cell width. Experimental conditions was set as a partially converted 3D condition in which a gray cell moved diagonally for a certain period of time with a dynamic binocular disparity added, a 3D condition in which binocular disparity was added to all gray cells, and a 2D condition. The correct response rates for recognition of each task after the distraction task were compared. The results of Experiment 2 showed that the correct

  6. Academic Self-Handicapping: Relationships with Learning Specific and General Self-Perceptions and Academic Performance over Time

    Science.gov (United States)

    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…

  7. Exploring students' perceptions on the use of significant event analysis, as part of a portfolio assessment process in general practice, as a tool for learning how to use reflection in learning.

    Science.gov (United States)

    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

  8. Deterministic dense coding with partially entangled states

    Science.gov (United 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.

  9. Sex Differences in Learned Helplessness: IV. An Experimental and Naturalistic Study of Failure Generalization and Its Mediators.

    Science.gov (United States)

    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)

  10. Teachers' Attitudes toward Assessment of Student Learning and Teacher Assessment Practices in General Educational Institutions: The Case of Georgia

    Science.gov (United States)

    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…

  11. Robust Monotonically Convergent Iterative Learning Control for Discrete-Time Systems via Generalized KYP Lemma

    Directory of Open Access Journals (Sweden)

    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.

  12. Effect of Emotional Intelligence on Student Learning Achievement

    Directory of Open Access Journals (Sweden)

    Hendra Hadiwijaya

    2017-08-01

    Full Text Available The Effect of Emotional Intelligence Against Student Achievement aims to determine the effect of emotional intelligence which consists of self awareness, self management, Motivation, social awareness, relationship management partially and simultaneously on learning achievement. Respondents are students of SMP Negeri 4 Lalan Bumi Agung  Vilage Musi Banyuasin Regency to be 135 people. Methods of data analysis using regression analysis techniques. Partial assay results (t-test showed emotional intelligence consists of Self awareness, self management, Motivation, social awareness, relationship management positive and significant effect on learning achievement. Simultaneous Test Results (Test-F emotional intelligence consists of Self awareness, self management, motivation, social awareness, relationship management and significant positive effect on learning achievement. Social awareness is more dominant influence on learning achievement.

  13. Cast Partial Denture versus Acrylic Partial Denture for Replacement of Missing Teeth in Partially Edentulous Patients

    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

  14. Using Computational Chemistry Activities to Promote Learning and Retention in a Secondary School General Chemistry Setting

    Science.gov (United States)

    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…

  15. The Contributions of Domain-General and Numerical Factors to Third-Grade Arithmetic Skills and Mathematical Learning Disability

    Science.gov (United States)

    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…

  16. 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,.

  17. ANALYTIC FITS FOR PARTIAL PHOTOIONIZATION CROSS-SECTIONS

    NARCIS (Netherlands)

    VERNER, DA; YAKOVLEV, DG

    We present a compact, uniform and complete set of analytic fits to the partial Hartree-Dirac-Slater photoionization cross sections for the ground state shells of all atoms and ions of elements from H to Zn (Z less-than-or-equal-to 30). Comparison with experiment and theory demonstrates generally

  18. 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

  19. 48 CFR 52.219-7 - Notice of Partial Small Business Set-Aside.

    Science.gov (United States)

    2010-10-01

    ... Clauses 52.219-7 Notice of Partial Small Business Set-Aside. As prescribed in 19.508(d), insert the following clause: Notice of Partial Small Business Set-Aside (JUN 2003) (a) Definitions. Small business..., and qualified as a small business under the size standards in this solicitation. (b) General. (1) A...

  20. Slower Reacquisition after Partial Extinction in Human Contingency Learning

    Science.gov (United States)

    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,…

  1. Systems control with generalized probabilistic fuzzy-reinforcement learning

    NARCIS (Netherlands)

    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

  2. Impression Procedures for Metal Frame Removable Partial Dentures as Applied by General Dental Practitioners.

    NARCIS (Netherlands)

    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

  3. The learning technique. Theoretical considerations for planning lessons wit h a strategic learning approach

    Directory of Open Access Journals (Sweden)

    Dania Regueira Martínez

    2014-03-01

    Full Text Available This article presents the learning task considered as the unit of smaller organization level in the teaching-learning process that conditions in its systemic structuring, the learning actions, for the students acquisition of the content, by means of the development of the reflection and the metacognitiv e regulation when they conscious ly or partially plan different types of learning strategies in the ir realization, with the objective to solv e the pedagogic professional problems that are p resented in the disciplines they receive and in its research task during the direction o f the teaching-learning process.

  4. Generalized EMV-Effect Algebras

    Science.gov (United States)

    Borzooei, R. A.; Dvurečenskij, A.; Sharafi, A. H.

    2018-04-01

    Recently in Dvurečenskij and Zahiri (2017), new algebraic structures, called EMV-algebras which generalize both MV-algebras and generalized Boolean algebras, were introduced. We present equivalent conditions for EMV-algebras. In addition, we define a partial algebraic structure, called a generalized EMV-effect algebra, which is close to generalized MV-effect algebras. Finally, we show that every generalized EMV-effect algebra is either an MV-effect algebra or can be embedded into an MV-effect algebra as a maximal ideal.

  5. Nonlinear analysis of shear deformable beam-columns partially ...

    African Journals Online (AJOL)

    In this paper, a boundary element method is developed for the nonlinear analysis of shear deformable beam-columns of arbitrary doubly symmetric simply or multiply connected constant cross section, partially supported on tensionless Winkler foundation, undergoing moderate large deflections under general boundary ...

  6. Students' Perceptions and Emotions Toward Learning in a Flipped General Science Classroom

    Science.gov (United States)

    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.

  7. 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

  8. Vocational trainees' views and experiences regarding the learning and teaching of communication skills in general practice.

    Science.gov (United States)

    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.

  9. Numerical Analysis for Stochastic Partial Differential Delay Equations with Jumps

    OpenAIRE

    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.

  10. An applied test of the social learning theory of deviance to college alcohol use.

    Science.gov (United States)

    DeMartino, Cynthia H; Rice, Ronald E; Saltz, Robert

    2015-04-01

    Several hypotheses about influences on college drinking derived from the social learning theory of deviance were tested and confirmed. The effect of ethnicity on alcohol use was completely mediated by differential association and differential reinforcement, whereas the effect of biological sex on alcohol use was partially mediated. Higher net positive reinforcements to costs for alcohol use predicted increased general use, more underage use, and more frequent binge drinking. Two unexpected finding were the negative relationship between negative expectations and negative experiences, and the substantive difference between nondrinkers and general drinkers compared with illegal or binge drinkers. The discussion considers implications for future campaigns based on Akers's deterrence theory.

  11. Generalization of stochastic visuomotor rotations.

    Directory of Open Access Journals (Sweden)

    Hugo L Fernandes

    Full Text Available Generalization studies examine the influence of perturbations imposed on one movement onto other movements. The strength of generalization is traditionally interpreted as a reflection of the similarity of the underlying neural representations. Uncertainty fundamentally affects both sensory integration and learning and is at the heart of many theories of neural representation. However, little is known about how uncertainty, resulting from variability in the environment, affects generalization curves. Here we extend standard movement generalization experiments to ask how uncertainty affects the generalization of visuomotor rotations. We find that although uncertainty affects how fast subjects learn, the perturbation generalizes independently of uncertainty.

  12. Evaluating the Generalization Value of Process-based Models in a Deep-in-time Machine Learning framework

    Science.gov (United States)

    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.

  13. E-learning for medical imaging specialists: introducing blended learning in a nuclear medicine specialist course.

    Science.gov (United States)

    Haslerud, Torjan; Tulipan, Andreas Julius; Gray, Robert M; Biermann, Martin

    2017-07-01

    While e-learning has become an important tool in teaching medical students, the training of specialists in medical imaging is still dominated by lecture-based courses. To assess the potential of e-learning in specialist education in medical imaging. An existing lecture-based five-day course in Clinical Nuclear Medicine (NM) was enhanced by e-learning resources and activities, including practical exercises. An anonymized survey was conducted after participants had completed and passed the multiple choice electronic course examination. Twelve out of 15 course participants (80%) responded. Overall satisfaction with the new course format was high, but 25% of the respondents wanted more interactive elements such as discussions and practical exercises. The importance of lecture handouts and supplementary online material such as selected original articles and professional guidelines was affirmed by all the respondents (92% fully, 8% partially), while 75% fully and 25% partially agreed that the lectures had been interesting and relevant. E-learning represents a hitherto unrealized potential in the education of medical specialists. It may expedite training of medical specialists while at the same time containing costs.

  14. Learning styles of medical students, general surgery residents, and general surgeons: implications for surgical education

    OpenAIRE

    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 ...

  15. Aspect-based Relevance Learning for Image Retrieval

    NARCIS (Netherlands)

    M.J. Huiskes (Mark)

    2005-01-01

    htmlabstractWe analyze the special structure of the relevance feedback learning problem, focusing particularly on the effects of image selection by partial relevance on the clustering behavior of feedback examples. We propose a scheme, aspect-based relevance learning, which guarantees that feedback

  16. General Dimensional Multiple-Output Support Vector Regressions and Their Multiple Kernel Learning.

    Science.gov (United States)

    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.

  17. Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex.

    Science.gov (United States)

    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.

  18. Analysis of ensemble learning using simple perceptrons based on online learning theory

    Science.gov (United States)

    Miyoshi, Seiji; Hara, Kazuyuki; Okada, Masato

    2005-03-01

    Ensemble learning of K nonlinear perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. One purpose of statistical learning theory is to theoretically obtain the generalization error. This paper shows that ensemble generalization error can be calculated by using two order parameters, that is, the similarity between a teacher and a student, and the similarity among students. The differential equations that describe the dynamical behaviors of these order parameters are derived in the case of general learning rules. The concrete forms of these differential equations are derived analytically in the cases of three well-known rules: Hebbian learning, perceptron learning, and AdaTron (adaptive perceptron) learning. Ensemble generalization errors of these three rules are calculated by using the results determined by solving their differential equations. As a result, these three rules show different characteristics in their affinity for ensemble learning, that is “maintaining variety among students.” Results show that AdaTron learning is superior to the other two rules with respect to that affinity.

  19. BLENDED LEARNING AS AN INNOVATIVE FORM OF TEACHING AND LEARNING AT SCHOOL

    Directory of Open Access Journals (Sweden)

    Olga Kuzmenko

    2017-09-01

    Full Text Available In the paper the theoretical background of blended learning is examined, traditional brick-and-mortar and blended learning are compared, the advantages of blended learning are outlined and it effectiveness in foreign language teaching is proven. The topicality of this research is determined by the prospect of implementing the blended learning models to achieve the goals set by the National Strategy for the Development of Education in Ukraine for 2012-2021, namely: improving the quality of education on an innovative basis, creating and providing opportunities for implementing various learning models, forms and means of getting education. In this context, a modern educational institution is required to set up a combination of traditional and innovative forms of learning, and constantly update its information and communication resources, which cause the need to introduce the blended learning approach. Blended learning is a relatively new approach in the field of education in Ukraine. The great prospect of blended learning consists in its potential to combine the best of traditional and online practices. This is a formal education program in which pupils learn partially through online learning with some element of self-control over time, place and pace; and partially in a traditional classroom setting. It provides more efficiency and flexibility in comparison with traditional learning as well as online or distance learning. Moreover, blended learning implies a mastery-based approach ensuring that pupils achieve the required level of mastery at the end of the course. It also prepares learners to collaborate in an online environment and meet the demands of the modern labour market. This is particularly important for schools, because modern pupils are tech-savvy and their motivation is determined by the need for autonomy, personalization, communicatively-oriented and mastery-based learning. For the teaching staff, blended learning can improve teaching

  20. Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning.

    Science.gov (United States)

    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.

  1. Analysis of generalized Schwarz alternating procedure for domain decomposition

    Energy Technology Data Exchange (ETDEWEB)

    Engquist, B.; Zhao, Hongkai [Univ. of California, Los Angeles, CA (United States)

    1996-12-31

    The Schwartz alternating method(SAM) is the theoretical basis for domain decomposition which itself is a powerful tool both for parallel computation and for computing in complicated domains. The convergence rate of the classical SAM is very sensitive to the overlapping size between each subdomain, which is not desirable for most applications. We propose a generalized SAM procedure which is an extension of the modified SAM proposed by P.-L. Lions. Instead of using only Dirichlet data at the artificial boundary between subdomains, we take a convex combination of u and {partial_derivative}u/{partial_derivative}n, i.e. {partial_derivative}u/{partial_derivative}n + {Lambda}u, where {Lambda} is some {open_quotes}positive{close_quotes} operator. Convergence of the modified SAM without overlapping in a quite general setting has been proven by P.-L.Lions using delicate energy estimates. The important questions remain for the generalized SAM. (1) What is the most essential mechanism for convergence without overlapping? (2) Given the partial differential equation, what is the best choice for the positive operator {Lambda}? (3) In the overlapping case, is the generalized SAM superior to the classical SAM? (4) What is the convergence rate and what does it depend on? (5) Numerically can we obtain an easy to implement operator {Lambda} such that the convergence is independent of the mesh size. To analyze the convergence of the generalized SAM we focus, for simplicity, on the Poisson equation for two typical geometry in two subdomain case.

  2. Students' Learning of a Generalized Theory of Sound Transmission from a Teaching-Learning Sequence about Sound, Hearing and Health

    Science.gov (United States)

    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.

  3. 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.

  4. Learning Networks for Lifelong Learning

    OpenAIRE

    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.

  5. 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...

  6. Matching games with partial information

    Science.gov (United States)

    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.

  7. Socio-cognitive profiles for visual learning in young and older adults

    Directory of Open Access Journals (Sweden)

    Julie eChristian

    2015-06-01

    Full Text Available It is common wisdom that practice makes perfect; but why do some adults learn better than others? Here, we investigate individuals’ cognitive and social profiles to test which variables account for variability in learning ability across the lifespan. In particular, we focused on visual learning using tasks that test the ability to inhibit distractors and select task-relevant features. We tested the ability of young and older adults to improve through training in the discrimination of visual global forms embedded in a cluttered background. Further, we used a battery of cognitive tasks and psycho-social measures to examine which of these variables predict training-induced improvement in perceptual tasks and may account for individual variability in learning ability. Using partial least squares regression modelling, we show that visual learning is influenced by cognitive (i.e. cognitive inhibition, attention and social (strategic and deep learning factors rather than an individual’s age alone. Further, our results show that independent of age, strong learners rely on cognitive factors such as attention, while weaker learners use more general cognitive strategies. Our findings suggest an important role for higher-cognitive circuits involving executive functions that contribute to our ability to improve in perceptual tasks after training across the lifespan.

  8. Using partially labeled data for normal mixture identification with application to class definition

    Science.gov (United States)

    Shahshahani, Behzad M.; Landgrebe, David A.

    1992-01-01

    The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

  9. General practitioners as supervisors in postgraduate clinical education

    DEFF Research Database (Denmark)

    Wearne, Susan; Dornan, Tim; Teunissen, Pim W.

    2012-01-01

    Context General practice supervisors are said to serve as the cornerstones of general practice postgraduate education and therefore it is important to clearly define their roles and what makes them effective. The commonly used definition of a supervisor is not primarily based on general practice...... with resident doctors that provided a foundation for learning. Residents needed a balance of challenge, usually provided by patients, and support, provided by supervisors. Supervisors established learning environments, assessed residents' learning needs, facilitated learning, monitored the content and process...... of learning and the well-being of residents, and summarised learning in ways that turned 'know that' into 'know how'. Conclusions General practice must be expert in ensuring patients are well cared for 'by proxy' and in giving residents just the right amount of support they need to face the challenges posed...

  10. Context-dependent Generalization

    Directory of Open Access Journals (Sweden)

    Jordan A Taylor

    2013-05-01

    Full Text Available The pattern of generalization following motor learning can provide a probe on the neural mechanisms underlying learning. For example, the breadth of generalization to untrained regions of space after visuomotor adaptation to targets in a restricted region of space has been attributed to the directional tuning properties of neurons in the motor system. Building on this idea, the effect of different types of perturbations on generalization (e.g., rotation versus visual translation have been attributed to the selection of differentially tuned populations. Overlooked in this discussion is consideration of how the context of the training environment may constrain generalization. Here, we explore the role of context by having participants learn a visuomotor rotation or a translational shift in two different contexts, one in which the array of targets were presented in a circular arrangement and the other in which they were presented in a rectilinear arrangement. The perturbation and environments were either consistent (e.g., rotation with circular arrangement or inconsistent (e.g., rotation with rectilinear arrangement. The pattern of generalization across the workspace was much more dependent on the context of the environment than on the perturbation, with broad generalization for the rectilinear arrangement for both types of perturbations. Moreover, the generalization pattern for this context was evident, even when the perturbation was introduced in a gradual manner, precluding the use of an explicit strategy. We describe how current models of generalization might be modified to incorporate these results, building on the idea that context provides a strong bias for how the motor system infers the nature of the visuomotor perturbation and, in turn, how this information influences the pattern of generalization.

  11. Learning during processing Word learning doesn’t wait for word recognition to finish

    Science.gov (United States)

    Apfelbaum, Keith S.; McMurray, Bob

    2017-01-01

    Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. PMID:27471082

  12. Active Learning Through Discussion in E-Learning

    OpenAIRE

    Daru Wahyuningsih

    2016-01-01

    Active learning is generally made by a lecturer in learning face to face. In the face to face learning, lecturer can implement a variety of teaching methods to make students actively involved in learning. This is different from learning that is actuating in e-learning. The main characteristic of e-learning is learning that can take place anytime and anywhere. Special strategies are needed so that lecturer can make students play an active role in the course of e-learning. Research in order to ...

  13. The Essences of Culinary Arts Students' Lived Experience of General Education Online Learning: An Interpretive Phenomenological Analysis

    Science.gov (United States)

    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…

  14. A Model Fit Statistic for Generalized Partial Credit Model

    Science.gov (United States)

    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…

  15. Partial logics with two kinds of negation as a foundation for knowledge-based reasoning

    NARCIS (Netherlands)

    H. Herre; J.O.M. Jaspars; G. Wagner

    1995-01-01

    textabstractWe show how to use model classes of partial logic to define semantics of general knowledge-based reasoning. Its essential benefit is that partial logics allow us to distinguish two sorts of negative information: the absence of information and the explicit rejection or falsification of

  16. Partial Reduction of Esters to Aldehydes Using a Novel Modified Red-Al Reducing Agent

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Won Kyu; Kang, Daehoon; An, Duk Keun [Kangwon National Univ., Chunchon (Korea, Republic of)

    2014-07-15

    We have developed a convenient alternative method for the synthesis of aldehydes from both aromatic and aliphatic esters in very good to excellent yields in the absence of any additives using a modified Red-Al that was easily prepared by reacting commercially available Red-Al with cis-2,6-dimethyl morpholine. The advantages of the present methodology are as follows: simple preparation procedure of the reducing agent, improved product yields, convenient reaction temperature, and short reaction times. Therefore, the new reagent has great potential to be a useful alternative partial reducing agent for the synthesis of aldehydes from esters in organic synthesis. Aldehydes are valuable building blocks and reactive intermediates in organic synthesis. The general and classical syntheses of aldehydes from esters involve reduction-oxidation and partial reduction using efficient partial reducing agents. Obviously, one-step partial reduction methods are more useful than two-step reduction-oxidation methods owing to their simplicity, and generality in organic synthesis.

  17. The generalized Airy diffusion equation

    Directory of Open Access Journals (Sweden)

    Frank M. Cholewinski

    2003-08-01

    Full Text Available Solutions of a generalized Airy diffusion equation and an associated nonlinear partial differential equation are obtained. Trigonometric type functions are derived for a third order generalized radial Euler type operator. An associated complex variable theory and generalized Cauchy-Euler equations are obtained. Further, it is shown that the Airy expansions can be mapped onto the Bessel Calculus of Bochner, Cholewinski and Haimo.

  18. Distance educational technologies as means of increase of student’s motivation in the learning of general physics course

    Science.gov (United States)

    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).

  19. Oxford Partial Knee Replacement as a Gateway to Outpatient Arthroplasty “Lessons Learned along the Journey”

    Directory of Open Access Journals (Sweden)

    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.

  20. On formation of a partially coherent beam in a stable-resonator laser

    International Nuclear Information System (INIS)

    Suvorov, A A

    2010-01-01

    A new method involving the expansion of the field coherence function in partially coherent modes - the eigensolutions of the problem for the second-order coherence function in a stable resonator - is proposed for the theoretical description of the process of multimode laser beam formation. The method for solving the problem for arbitrary partially coherent modes is formulated and the expressions for these modes are derived in the general form. The characteristics of the fundamental partially coherent mode, which coincides with the coherence function of a Gaussian partially coherent beam, are analysed in detail. The partially coherent modes are shown to possess two spatial scales - the effective radius and the coherence radius, which makes them a convenient tool for solving the problem of generation of a partially coherent beam. It is found that the unambiguous relation between the characteristics of partially coherent modes and the stable-resonator parameters is achieved by involving into consideration not only the process of the beam formation by the resonator mirrors but also the process of interaction of radiation with the active laser medium. (laser beams and resonators)

  1. Atmospheric weighting functions and surface partial derivatives for remote sensing of scattering planetary atmospheres in thermal spectral region: general adjoint approach

    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

  2. An Investigation of the Relationship between Autonomous Learning and Lifelong Learning

    Directory of Open Access Journals (Sweden)

    Cengiz Yurdakul

    2016-12-01

    Full Text Available The present study aims to investigate the relationship between autonomous learning and lifelong learning. The study group consists of 657 secondary school students enrolled in three public schools, aged 11 – 16 from Sakarya, Turkey. In this study, relationships between the variables of autonomous learning and lifelong learning and the sub-dimensions of autonomous learning were investigated. Pearson Product Moment Correlation, Partial Correlation methods were utilized in order to investigate these relationships. Autonomous Learning Scale (12 items which was developed by Macaskill and Taylor (2010, was adapted to Turkish by Arslan and Yurdakul (2015 was conducted to measure autonomous learning. Lifelong Learning Scale (14 items which was developed by Kirby, Knapper, Lamon and Egnatoff (2010, was adapted to Turkish by Arslan and Akcaalan (2015 was carried out to assess lifelong learning level. In the light of the research findings, it can be purported that autonomous learning and lifelong learning scores were correlating significantly. According to the existing results, it can be argued that autonomous learning which can be defined as the capacity to take charge of one’s own learning, has a positive interaction with lifelong learning which can be found voice in one’s ongoing, voluntary, and self-motivated learning.

  3. Generalized vector calculus on convex domain

    Science.gov (United States)

    Agrawal, Om P.; Xu, Yufeng

    2015-06-01

    In this paper, we apply recently proposed generalized integral and differential operators to develop generalized vector calculus and generalized variational calculus for problems defined over a convex domain. In particular, we present some generalization of Green's and Gauss divergence theorems involving some new operators, and apply these theorems to generalized variational calculus. For fractional power kernels, the formulation leads to fractional vector calculus and fractional variational calculus for problems defined over a convex domain. In special cases, when certain parameters take integer values, we obtain formulations for integer order problems. Two examples are presented to demonstrate applications of the generalized variational calculus which utilize the generalized vector calculus developed in the paper. The first example leads to a generalized partial differential equation and the second example leads to a generalized eigenvalue problem, both in two dimensional convex domains. We solve the generalized partial differential equation by using polynomial approximation. A special case of the second example is a generalized isoperimetric problem. We find an approximate solution to this problem. Many physical problems containing integer order integrals and derivatives are defined over arbitrary domains. We speculate that future problems containing fractional and generalized integrals and derivatives in fractional mechanics will be defined over arbitrary domains, and therefore, a general variational calculus incorporating a general vector calculus will be needed for these problems. This research is our first attempt in that direction.

  4. Partial volume and aliasing artefacts in helical cone-beam CT

    International Nuclear Information System (INIS)

    Zou Yu; Sidky, Emil Y; Pan, Xiaochuan

    2004-01-01

    A generalization of the quasi-exact algorithms of Kudo et al (2000 IEEE Trans. Med. Imaging 19 902-21) is developed that allows for data acquisition in a 'practical' frame for clinical diagnostic helical, cone-beam computed tomography (CT). The algorithm is investigated using data that model nonlinear partial volume averaging. This investigation leads to an understanding of aliasing artefacts in helical, cone-beam CT image reconstruction. An ad hoc scheme is proposed to mitigate artefacts due to the nonlinear partial volume and aliasing artefacts

  5. Partial liquid-penetration inside a deep trench by film flowing over it

    Science.gov (United States)

    Nguyen, Phuc-Khanh; Dimakopoulos, Yiannis; Tsamopoulos, John

    2014-11-01

    Liquid film flow along substrates featuring a deep trench may not wet the trench floor, but create a second gas-liquid interface inside the trench. The liquid penetration inside the trench depends on the location and shape of this inner interface. The penetration increases by decreasing the two three-phase contact lines between the inner interface and the two side-walls or the flow rate and depends on the liquid properties. This partial-penetration is studied by employing the Galerkin / finite element method to solve the two-dimensional steady-state Navier-Stokes equations in a physical domain that is adaptively remeshed. Multiple branches of steady solutions connected via turning points are revealed by pseudo arc-length continuation. Flow hysteresis may occur in a certain range of liquid penetration depth, when the interaction of the two interfaces changes qualitatively. This induces an abrupt jump of penetration distance and deformation amplitude of the outer interface. Work supported by the General Secretariat of Research & Technology of Greece through the program ``Excellence'' (Grant No. 1918) in the framework ``Education and Lifelong Learning'' co-funded by the ESF.

  6. Concurrent Learning of Control in Multi agent Sequential Decision Tasks

    Science.gov (United States)

    2018-04-17

    Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement... learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable... learning of policies in Dec-POMDPs, established performance bounds, evaluated these algorithms both theoretically and empirically, The views

  7. Equation of state of partially-ionized dense plasmas

    International Nuclear Information System (INIS)

    Rogers, F.J.

    1989-01-01

    This paper describes methods for calculating the equation of state of partially-ionized dense plasmas. The term dense plasma is used rather than strongly coupled plasma, since it is possible that at plasma conditions such that only a few levels can be observed spectroscopically the plasma coupling parameters are not large. Due mainly to their importance in theoretical astrophysics, the properties of partially ionized plasmas have been of interest for a long while. More recently, this interest has intensified due to the development of methods for producing partially ionized plasmas in the laboratory. This has opened up large programs of experimental investigation and of practical application. In this paper we consider detailed statistical mechanical methods that explicitly treat the distribution over ionic species and their energy level structure. These detailed approaches are generally characterized as being in the ''chemical picture'' when a free energy expression is minimized or in the ''physical picture'' when the starting point is the grand canonical ensemble. 52 refs., 2 tabs

  8. Semantics and correctness proofs for programs with partial functions

    International Nuclear Information System (INIS)

    Yakhnis, A.; Yakhnis, V.

    1996-01-01

    This paper presents a portion of the work on specification, design, and implementation of safety-critical systems such as reactor control systems. A natural approach to this problem, once all the requirements are captured, would be to state the requirements formally and then either to prove (preferably via automated tools) that the system conforms to spec (program verification), or to try to simultaneously generate the system and a mathematical proof that the requirements are being met (program derivation). An obstacle to this is frequent presence of partially defined operations within the software and its specifications. Indeed, the usual proofs via first order logic presuppose everywhere defined operations. Recognizing this problem, David Gries, in ''The Science of Programming,'' 1981, introduced the concept of partial functions into the mainstream of program correctness and gave hints how his treatment of partial functions could be formalized. Still, however, existing theorem provers and software verifiers have difficulties in checking software with partial functions, because of absence of uniform first order treatment of partial functions within classical 2-valued logic. Several rigorous mechanisms that took partiality into account were introduced [Wirsing 1990, Breu 1991, VDM 1986, 1990, etc.]. However, they either did not discuss correctness proofs or departed from first order logic. To fill this gap, the authors provide a semantics for software correctness proofs with partial functions within classical 2-valued 1st order logic. They formalize the Gries treatment of partial functions and also cover computations of functions whose argument lists may be only partially available. An example is nuclear reactor control relying on sensors which may fail to deliver sense data. This approach is sufficiently general to cover correctness proofs in various implementation languages

  9. Distributed wireless quantum communication networks with partially entangled pairs

    International Nuclear Information System (INIS)

    Yu Xu-Tao; Zhang Zai-Chen; Xu Jin

    2014-01-01

    Wireless quantum communication networks transfer quantum state by teleportation. Existing research focuses on maximal entangled pairs. In this paper, we analyse the distributed wireless quantum communication networks with partially entangled pairs. A quantum routing scheme with multi-hop teleportation is proposed. With the proposed scheme, is not necessary for the quantum path to be consistent with the classical path. The quantum path and its associated classical path are established in a distributed way. Direct multi-hop teleportation is conducted on the selected path to transfer a quantum state from the source to the destination. Based on the feature of multi-hop teleportation using partially entangled pairs, if the node number of the quantum path is even, the destination node will add another teleportation at itself. We simulated the performance of distributed wireless quantum communication networks with a partially entangled state. The probability of transferring the quantum state successfully is statistically analyzed. Our work shows that multi-hop teleportation on distributed wireless quantum networks with partially entangled pairs is feasible. (general)

  10. Approximate thermodynamic state relations in partially ionized gas mixtures

    International Nuclear Information System (INIS)

    Ramshaw, John D.

    2004-01-01

    Thermodynamic state relations for mixtures of partially ionized nonideal gases are often approximated by artificially partitioning the mixture into compartments or subvolumes occupied by the pure partially ionized constituent gases, and requiring these subvolumes to be in temperature and pressure equilibrium. This intuitively reasonable procedure is easily shown to reproduce the correct thermal and caloric state equations for a mixture of neutral (nonionized) ideal gases. The purpose of this paper is to point out that (a) this procedure leads to incorrect state equations for a mixture of partially ionized ideal gases, whereas (b) the alternative procedure of requiring that the subvolumes all have the same temperature and free electron density reproduces the correct thermal and caloric state equations for such a mixture. These results readily generalize to the case of partially degenerate and/or relativistic electrons, to a common approximation used to represent pressure ionization effects, and to two-temperature plasmas. This suggests that equating the subvolume electron number densities or chemical potentials instead of pressures is likely to provide a more accurate approximation in nonideal plasma mixtures

  11. Acquisition with partial and continuous reinforcement in pigeon autoshaping.

    Science.gov (United States)

    Gottlieb, Daniel A

    2004-08-01

    Contemporary time accumulation models make the unique prediction that acquisition of a conditioned response will be equally rapid with partial and continuous reinforcement, if the time between conditioned stimuli is held constant. To investigate this, acquisition of conditioned responding was examined in pigeon autoshaping under conditions of 100% and 25% reinforcement, holding intertrial interval constant. Contrary to what was predicted, evidence for slowed acquisition in partially reinforced animals was observed with several response measures. However, asymptotic performance was superior with 25% reinforcement. A switching of reinforcement contingencies after initial acquisition did not immediately affect responding. After further sessions, partial reinforcement augmented responding, whereas continuous reinforcement did not, irrespective of an animal's reinforcement history. Subsequent training with a novel stimulus maintained the response patterns. These acquisition results generally support associative, rather than time accumulation, accounts of conditioning.

  12. Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals.

    Science.gov (United States)

    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

  13. A regional and nonstationary model for partial duration series of extreme rainfall

    DEFF Research Database (Denmark)

    Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

    2017-01-01

    as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found...... of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts...... furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network...

  14. Homeostatic Agent for General Environment

    Science.gov (United States)

    Yoshida, Naoto

    2018-03-01

    One of the essential aspect in biological agents is dynamic stability. This aspect, called homeostasis, is widely discussed in ethology, neuroscience and during the early stages of artificial intelligence. Ashby's homeostats are general-purpose learning machines for stabilizing essential variables of the agent in the face of general environments. However, despite their generality, the original homeostats couldn't be scaled because they searched their parameters randomly. In this paper, first we re-define the objective of homeostats as the maximization of a multi-step survival probability from the view point of sequential decision theory and probabilistic theory. Then we show that this optimization problem can be treated by using reinforcement learning algorithms with special agent architectures and theoretically-derived intrinsic reward functions. Finally we empirically demonstrate that agents with our architecture automatically learn to survive in a given environment, including environments with visual stimuli. Our survival agents can learn to eat food, avoid poison and stabilize essential variables through theoretically-derived single intrinsic reward formulations.

  15. RECTC/RECTCF, 2. Order Elliptical Partial Differential Equation, Arbitrary Boundary Conditions

    International Nuclear Information System (INIS)

    Hackbusch, W.

    1983-01-01

    1 - Description of problem or function: A general linear elliptical second order partial differential equation on a rectangle with arbitrary boundary conditions is solved. 2 - Method of solution: Multi-grid iteration

  16. Effects of dose and of partial body ionizing radiation on taste aversion learning in rats with lesions of the area postrema

    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

  17. Exact solutions of some nonlinear partial differential equations using ...

    Indian Academy of Sciences (India)

    The functional variable method is a powerful solution method for obtaining exact solutions of some nonlinear partial differential equations. In this paper, the functional variable method is used to establish exact solutions of the generalized forms of Klein–Gordon equation, the (2 + 1)-dimensional Camassa–Holm ...

  18. Teacher learning as workplace learning

    NARCIS (Netherlands)

    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.

  19. The origin of the concept of partial epilepsy.

    Science.gov (United States)

    Eadie

    1999-03-01

    The International League Against Epilepsy has devised classifications which subdivide both epileptic seizures and the epilepsies and epileptic syndromes into two main types: generalized and partial. Epileptogenesis in the partial variety is believed to originate in a localized part of the cerebral cortex and results in clinical manifestations which appear to commence in only a restricted part of the sufferer's body. Use of the term 'partial' in relation to these entities has often been said to date back to James Cowles Prichard (1786-1849) who was the author of the second major work on epilepsy to be written in the UK. While Prichard certainly described 'partial epilepsy', he stated that he intended the words to refer to the fact that the disorder he described under that designation was only partly, and not fully, epileptic in nature. He did not refer to the fact that it affected only part of the body as his basis for using the term. In the absence of knowledge of localization of function in the cerebral cortex at Prichard's time of writing, he had no basis for deducing that the underlying epileptic process arose in only part of the brain. However, there is an earlier mention of the use of the word 'partial' in relation to epilepsy. This is to be found in the writings of the great Scottish physician William Cullen (1710-1790), and there is reason to believe that Prichard should have been aware of this. Cullen used 'partial' with an intention similar to the modern one, employing the word to refer to seizures which affected only part of the body. Credit for the origin of the idea of a 'partial' epilepsy should belong to Cullen; not only did he have priority over Prichard but his concept was closer to the modern one than was Prichard's. Copyright 1999 Harcourt Publishers Ltd.

  20. Five Generalizations About Cognitive Development.

    Science.gov (United States)

    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)

  1. LEARNING ABOUT LEARNING, A CONFERENCE REPORT.

    Science.gov (United States)

    BRUNER, JEROME

    TO EXPLORE THE NATURE OF THE LEARNING PROCESS, THREE IMPORTANT PROBLEM AREAS WERE STUDIED. STUDIES IN THE FIRST AREA, ATTITUDINAL AND AFFECTIVE SKILLS, ARE CONCERNED WITH INDUCING A CHILD TO LEARN AND SUSTAINING HIS ATTENTION. STUDIES IN THE SECOND AREA, COGNITIVE SKILLS, SOUGHT TO DISCOVER WHETHER GENERAL IDEAS AND SKILLS CAN BE LEARNED IN SUCH A…

  2. ALTEC Learning Games: Successful Integration of Learning and Gaming

    Science.gov (United States)

    Bacon, Melanie A.; Ault, Marilyn M.

    2009-01-01

    Of the 53 million K-12 students in the United States, 93%, or 51 million, of them play video games (Etuk, 2008). ALTEC Learning Games utilize the excitement of video games to engage students and provide teachers authentic online resources that reinforce skills in math and language arts. Our recent work was partially supported by a partnership with…

  3. Design and Assessment of a General Science STEM Course with a Blended Learning Approach

    Science.gov (United States)

    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.

  4. Generalization of socially transmitted and instructed avoidance

    Directory of Open Access Journals (Sweden)

    Gemma eCameron

    2015-06-01

    Full Text Available Excessive avoidance behavior, in which an instrumental action prevents an upcoming aversive event, is a defining feature of anxiety disorders. Left unchecked, both fear and avoidance of potentially threatening stimuli may generalize to perceptually related stimuli and situations. The behavioral consequences of generalization mean that aversive learning experiences with specific threats may lead people to infer that classes of related stimuli are threatening, potentially dangerous, and need to be avoided, despite differences in physical form. Little is known about avoidance generalization in humans and the learning pathways by which it may be transmitted. In the present study, we compared two pathways to avoidance, instructions and social observation, on subsequent generalization of avoidance behavior, fear expectancy and physiological arousal. Participants first learned that one cue was a danger cue (conditioned stimulus, CS+ and another was a safety cue (CS-. Groups then were either instructed that a simple avoidance response in the presence of the CS+ cancelled upcoming shock presentations (instructed-learning group or observed a short movie showing a demonstrator performing the avoidance response to prevent shock (observational-learning group. During generalization testing, danger and safety cues were presented along with generalization stimuli that parametrically varied in perceptual similarity to the CS+. Reinstatement of fear and avoidance was also tested. Findings demonstrate, for the first time, generalization of socially transmitted and instructed avoidance: both groups showed comparable generalization gradients in fear expectancy, avoidance behavior and arousal. Return of fear was evident, suggesting that generalized avoidance remains persistent following extinction testing. The utility of the present paradigm for research on avoidance generalization is discussed.

  5. Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

    KAUST Repository

    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.

  6. Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm

    KAUST Repository

    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.

  7. Projection specificity in heterogeneous locus coeruleus cell populations: implications for learning and memory

    Science.gov (United States)

    Uematsu, Akira; Tan, Bao Zhen

    2015-01-01

    Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory. This relatively small population of cells sends widespread projections throughout the brain including to a number of regions such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is important for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical, behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons respond during associative learning and when previously learned task contingencies change. Together, these studies suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection specificity. PMID:26330494

  8. Generalized Path Analysis and Generalized Simultaneous Equations Model for Recursive Systems with Responses of Mixed Types

    Science.gov (United States)

    Tsai, Tien-Lung; Shau, Wen-Yi; Hu, Fu-Chang

    2006-01-01

    This article generalizes linear path analysis (PA) and simultaneous equations models (SiEM) to deal with mixed responses of different types in a recursive or triangular system. An efficient instrumental variable (IV) method for estimating the structural coefficients of a 2-equation partially recursive generalized path analysis (GPA) model and…

  9. Partial tooth gear bearings

    Science.gov (United States)

    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.

  10. Higher iridescent-to-pigment optical effect in flowers facilitates learning, memory and generalization in foraging bumblebees.

    Science.gov (United States)

    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).

  11. Partial stabilization and control of distributed parameter systems with elastic elements

    CERN Document Server

    Zuyev, Alexander L

    2015-01-01

     This monograph provides a rigorous treatment of problems related to partial asymptotic stability and controllability for models of flexible structures described by coupled nonlinear ordinary and partial differential equations or equations in abstract spaces. The text is self-contained, beginning with some basic results from the theory of continuous semigroups of operators in Banach spaces. The problem of partial asymptotic stability with respect to a continuous functional is then considered for a class of abstract multivalued systems on a metric space. Next, the results of this study are applied to the study of a rotating body with elastic attachments. Professor Zuyev demonstrates that the equilibrium cannot be made strongly asymptotically stable in the general case, motivating consideration of the problem of partial stabilization with respect to the functional that represents “averaged” oscillations. The book’s focus moves on to spillover analysis for infinite-dimensional systems with finite-dimensio...

  12. Developing renal nurses' buttonhole cannulation skills using e-learning.

    Science.gov (United States)

    Blackman, Ian R; Mannix, Trudi; Sinclair, Peter M

    2014-03-01

    It has previously been shown that nurses can learn clinical nursing skills by e-learning (online), and that many variables will influence how well nurses adopt learned clinical skills using distance education. This study aimed to identify and measure the strength of those factors which would simultaneously influence registered nurses' (RNs') beliefs about their own learning about buttonhole cannulation, using e-learning. An online Likert style survey consisting of a list of statements related to knowledge and skill domains considered crucial in the area of buttonhole cannulation was distributed to 101 RNs before and after completing an e-learning programme. Participants were required to identify their current level of self-confidence in relationship to each of the statements. Measures of RNs' self-rated abilities to assess and implement buttonhole cannulation after completing a related e-learning program were tested using a Partial Least Squares Analysis (PLS-PATH) programme. The study's results strongly identify that the nurses' ability to meet both clinical and educational outcomes of the renal e-learning module can be predicted by six variables, none of which are directly related to the participants' demographic or clinical backgrounds. These findings support the use of e-learning to teach clinical skills to RNs, and demonstrate the value of Partial Least Squares Analysis in determining influential learning factors. © 2014 European Dialysis and Transplant Nurses Association/European Renal Care Association.

  13. Learning and coding in biological neural networks

    Science.gov (United States)

    Fiete, Ila Rani

    How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and

  14. Bactericidal activity of partially oxidized nanodiamonds.

    Science.gov (United States)

    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.

  15. Stochastic partial differential equations an introduction

    CERN Document Server

    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...

  16. Vocational trainees’ views and experiences regarding the learning and teaching of communication skills in general practice

    OpenAIRE

    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...

  17. Dynamic programming approach for partial decision rule optimization

    KAUST Repository

    Amin, Talha

    2012-10-04

    This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

  18. Dynamic programming approach for partial decision rule optimization

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2012-01-01

    This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

  19. A Fast Optimization Method for General Binary Code Learning.

    Science.gov (United States)

    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.

  20. Sexual learning among East African adolescents in the context of generalized HIV epidemics: A systematic qualitative meta-synthesis.

    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

  1. rFerns: An Implementation of the Random Ferns Method for General-Purpose Machine Learning

    Directory of Open Access Journals (Sweden)

    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.

  2. Effective Learning Environments in Relation to Different Learning Theories

    OpenAIRE

    Guney, Ali; Al, Selda

    2012-01-01

    There are diverse learning theories which explain learning processes which are discussed within this paper, through cognitive structure of learning process. Learning environments are usually described in terms of pedagogical philosophy, curriculum design and social climate. There have been only just a few studies about how physical environment is related to learning process. Many researchers generally consider teaching and learning issues as if independent from physical environment, whereas p...

  3. Darboux transformations and linear parabolic partial differential equations

    International Nuclear Information System (INIS)

    Arrigo, Daniel J.; Hickling, Fred

    2002-01-01

    Solutions for a class of linear parabolic partial differential equation are provided. These solutions are obtained by first solving a system of (n+1) nonlinear partial differential equations. This system arises as the coefficients of a Darboux transformation and is equivalent to a matrix Burgers' equation. This matrix equation is solved using a generalized Hopf-Cole transformation. The solutions for the original equation are given in terms of solutions of the heat equation. These results are applied to the (1+1)-dimensional Schroedinger equation where all bound state solutions are obtained for a 2n-parameter family of potentials. As a special case, the solutions for integral members of the regular and modified Poeschl-Teller potentials are recovered. (author). Letter-to-the-editor

  4. Learning Together; part 2: training costs and health gain - a cost analysis.

    Science.gov (United States)

    Cullen, Katherine; Riches, Wendy; Macaulay, Chloe; Spicer, John

    2017-01-01

    Learning Together is a complex educational intervention aimed at improving health outcomes for children and young people. There is an additional cost as two doctors are seeing patients together for a longer appointment than a standard general practice (GP) appointment. Our approach combines the impact of the training clinics on activity in South London in 2014-15 with health gain, using NICE guidance and standards to allow comparison of training options. Activity data was collected from Training Practices hosting Learning Together. A computer based model was developed to analyse the costs of the Learning Together intervention compared to usual training in a partial economic evaluation. The results of the model were used to value the health gain required to make the intervention cost effective. Data were returned for 363 patients booked into 61 clinics across 16 Training Practices. Learning Together clinics resulted in an increase in costs of £37 per clinic. Threshold analysis illustrated one child with a common illness like constipation needs to be well for two weeks, in one Practice hosting four training clinics for the clinics to be considered cost effective. Learning Together is of minimal training cost. Our threshold analysis produced a rubric that can be used locally to test cost effectiveness at a Practice or Programme level.

  5. Mechanisms for Creating a Psychologically Safe Learning Environment in an Educational Institution of General Education

    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

  6. Association between Exposure of Young Children to Procedures Requiring General Anesthesia and Learning and Behavioral Outcomes in a Population-based Birth Cohort.

    Science.gov (United States)

    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.

  7. Categorization = Decision Making + Generalization

    Science.gov (United States)

    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

  8. Relationship between Individual and Organizational Learning: Mediating Role of Team Learning

    Directory of Open Access Journals (Sweden)

    Monika Stelmaszczyk

    2016-12-01

    Full Text Available The aim of this paper is to recognize the relationships between individual and organizational learning while considering team learning as a mediator of these relationships. The research object is a large Polish enterprise specializing in the production of cast-iron items. In order to test assumed research hypotheses, statistical analyses were conducted using the IBM SPSS Statistics Suite, version 20. The suite helped conduct correlation analyses concatenation, line regression analyses and mediation analyses using the PROCESS macro by Hayes and Preacher. The research results show a statistically significant relationship between individual learning and each of the five dimensions of organizational learning [clarity of purpose and mission; leadership commitment and empowerment; knowledge transfer; experimentation and rewards; and teamwork and group problem solving]. What is more, they prove that team learning is a mediator of a relationship between individual and organizational learning. Interestingly, only one full mediation has been observed while researching the mediative effect of team learning in relation to each out of the five dimensions of organizational learning. It occurred in relation to experimentation and rewards. In the remaining cases these were partial mediations.

  9. A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning.

    Science.gov (United States)

    Windridge, David; Felsberg, Michael; Shaukat, Affan

    2013-02-01

    Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

  10. Stochastic collusion and the power law of learning: a general reinforcement learning model of cooperation

    NARCIS (Netherlands)

    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

  11. Computation of Partially Invariant Solutions for the Einstein Walker Manifolds' Identifying Equations

    OpenAIRE

    Nadjafikhah, Mehdi; Jafari, Mehdi

    2014-01-01

    In this paper, partially invariant solutions (PISs) method is applied in order to obtain new four-dimensional Einstein Walker manifolds. This method is based on subgroup classification for the symmetry group of partial differential equations (PDEs) and can be regarded as the generalization of the similarity reduction method. For this purpose, those cases of PISs which have the defect structure delta=1 and are resulted from two-dimensional subalgebras are considered in the present paper. Also ...

  12. Learning about light and optics in on-line general education classes using at-home experimentation

    Science.gov (United States)

    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.

  13. Transformative learning spaces

    DEFF Research Database (Denmark)

    Maslo, Elina

    Despite rapid development of learning theory in general and language learning theory in particular in the last years, we still cannot provide an unequivocal answer on the question “why do individuals who presumably possess similar cognitive capacities for second language learning achieve such var......, Leo (2010). The ecology of language learning: Practice to theory, theory to practice. Procedia – Social and Behavioral Sciences. Elsevier......., social, personal, cultural, and historical world they live in (van Lier, 2000). People can learn when they discover possibilities for learning, which appear in this complex world – so called affordances (Gibson, 1979). This happens in the interaction between people and their environment on the basis...... to the different ways of interaction of cognitive, affective and social factors by different individuals. Learning stories, where multilingual individuals are telling about their subjective experiences in language learning in particular and learning in general, are constructed by using a special developed...

  14. A general picture of the learning communities: characteristics, similarities and differences.

    NARCIS (Netherlands)

    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

  15. Evaluation of articulation of Turkish phonemes after removable partial denture application

    Directory of Open Access Journals (Sweden)

    Özbeki Murat

    2003-01-01

    Full Text Available In this study, the adaptation of patients to removable partial dentures was evaluated related to articulation of Turkish phonemes. Articulation of /t,d,n,l,r/, /g,k/, /b,p,m/ and /s,z,Õ,v,f,y,j,h,c/ phonemes were evaluated by three speech pathologists, on records taken from 15 patients before the insertion of a removable partial denture, just after insertion, and one week later. The test consisted of evaluation of phoneme articulation of independent syllables in terms of distortion, omission, substitution, mass effect, hypernasality and hyponasality. Data were evaluated with Cochrane Q, McNemar and Kruskal-Wallis tests. The results showed that for some phonemes, problems in articulation occurred after the insertion of a removable partial denture while for others a significant amelioration was observed after the insertion of a removable partial denture. In general, problems in articulation of evaluated phonemes were resolved after one week of use.

  16. 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.

  17. 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

  18. Deep Learning in Medical Imaging: General Overview

    Science.gov (United States)

    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

  19. Deep Learning in Medical Imaging: General Overview.

    Science.gov (United States)

    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.

  20. Organizational Learning Supported by Machine Learning Models Coupled with General Explanation Methods: A Case of B2B Sales Forecasting

    Directory of Open Access Journals (Sweden)

    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.

  1. Knowing, Applying, and Reasoning about Arithmetic: Roles of Domain-General and Numerical Skills in Multiple Domains of Arithmetic Learning

    Science.gov (United States)

    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…

  2. Effects of Group Awareness and Self-Regulation Level on Online Learning Behaviors

    Science.gov (United States)

    Lin, Jian-Wei; Szu, Yu-Chin; Lai, Ching-Neng

    2016-01-01

    Group awareness can affect student online learning while self-regulation also can substantially influence student online learning. Although some studies identify that these two variables may partially determine learning behavior, few empirical studies or thorough analyses elucidate the simultaneous impact of these two variables (group awareness…

  3. A noncommutative mean ergodic theorem for partial W*-dynamical semigroups

    International Nuclear Information System (INIS)

    Ekhaguere, G.O.S.

    1992-12-01

    A noncommutative mean ergodic theorem for dynamical semigroups of maps on partial W*-algebras of linear operators from a pre-Hilbert space into its completion is proved. This generalizes a similar result of Watanabe for dynamical semigroups of maps on W*-algebras of operators. (author). 14 refs

  4. A neurogenetic dissociation between punishment-, reward- and relief-learning in Drosophila

    Directory of Open Access Journals (Sweden)

    ayse Yarali

    2010-12-01

    Full Text Available What is particularly worth remembering about a traumatic experience is what brought it about, and what made it cease. For example, fruit flies avoid an odour which during training had preceded electric shock punishment; on the other hand, if the odour had followed shock during training, it is later on approached as a signal for the relieving end of shock. We provide a neurogenetic analysis of such relief learning. Blocking, using UAS-shibirets1, the output from a particular set of dopaminergic neurons defined by the TH-Gal4 driver partially impaired punishment learning, but left relief learning intact. Thus, with respect to these particular neurons, relief learning differs from punishment learning. Targeting another set of dopaminergic/ serotonergic neurons defined by the DDC-Gal4 driver on the other hand affected neither punishment nor relief learning. As for the octopaminergic system, the tbhM18 mutation, compromising octopamine biosynthesis, partially impaired sugar-reward learning, but not relief learning. Thus, with respect to this particular mutation, relief learning and reward learning are dissociated. Finally, blocking output from the set of octopaminergic/ tyraminergic neurons defined by the TDC2-Gal4 driver affected neither reward, nor relief learning. We conclude that regarding the used genetic tools, relief learning is neurogenetically dissociated from both punishment and reward learning.

  5. Experts' understanding of partial derivatives using the Partial Derivative Machine

    OpenAIRE

    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...

  6. Dictionary learning for data recovery in positron emission tomography

    International Nuclear Information System (INIS)

    Valiollahzadeh, SeyyedMajid; Clark, John W Jr; Mawlawi, Osama

    2015-01-01

    Compressed sensing (CS) aims to recover images from fewer measurements than that governed by the Nyquist sampling theorem. Most CS methods use analytical predefined sparsifying domains such as total variation, wavelets, curvelets, and finite transforms to perform this task. In this study, we evaluated the use of dictionary learning (DL) as a sparsifying domain to reconstruct PET images from partially sampled data, and compared the results to the partially and fully sampled image (baseline).A CS model based on learning an adaptive dictionary over image patches was developed to recover missing observations in PET data acquisition. The recovery was done iteratively in two steps: a dictionary learning step and an image reconstruction step. Two experiments were performed to evaluate the proposed CS recovery algorithm: an IEC phantom study and five patient studies. In each case, 11% of the detectors of a GE PET/CT system were removed and the acquired sinogram data were recovered using the proposed DL algorithm. The recovered images (DL) as well as the partially sampled images (with detector gaps) for both experiments were then compared to the baseline. Comparisons were done by calculating RMSE, contrast recovery and SNR in ROIs drawn in the background, and spheres of the phantom as well as patient lesions.For the phantom experiment, the RMSE for the DL recovered images were 5.8% when compared with the baseline images while it was 17.5% for the partially sampled images. In the patients’ studies, RMSE for the DL recovered images were 3.8%, while it was 11.3% for the partially sampled images. Our proposed CS with DL is a good approach to recover partially sampled PET data. This approach has implications toward reducing scanner cost while maintaining accurate PET image quantification. (paper)

  7. Increasing the capacity to learn in organizations

    International Nuclear Information System (INIS)

    Barker Scott, B.

    2007-01-01

    This presentation outlines the process of learning in organizations. The learning cycle involves acquiring, applying, reflecting and generalizing. There are three levels of learning: organizational learning, team learning and individual learning. Organizational learning is learning that is embedded into the way we do things through process, norms, systems, structures, strategy etc. It concludes by suggesting that organization must generate ideas with impact and generalize ideas with impact

  8. Fluid description of multi-component solar partially ionized plasma

    International Nuclear Information System (INIS)

    Khomenko, E.; Collados, M.; Vitas, N.; Díaz, A.

    2014-01-01

    We derive self-consistent formalism for the description of multi-component partially ionized solar plasma, by means of the coupled equations for the charged and neutral components for an arbitrary number of chemical species, and the radiation field. All approximations and assumptions are carefully considered. Generalized Ohm's law is derived for the single-fluid and two-fluid formalism. Our approach is analytical with some order-of-magnitude support calculations. After general equations are developed, we particularize to some frequently considered cases as for the interaction of matter and radiation

  9. Deep learning? What deep learning? | Fourie | South African ...

    African Journals Online (AJOL)

    In teaching generally over the past twenty years, there has been a move towards teaching methods that encourage deep, rather than surface approaches to learning. The reason for this being that students, who adopt a deep approach to learning are considered to have learning outcomes of a better quality and desirability ...

  10. Action Learning in Virtual Higher Education: Applying Leadership Theory

    Science.gov (United States)

    Curtin, Joseph

    2016-01-01

    This paper reports the historical foundation of Northeastern University's course, LDR 6100: Developing Your Leadership Capability, a partial literature review of action learning (AL) and virtual action learning (VAL), a course methodology of LDR 6100 requiring students to apply leadership perspectives using VAL as instructed by the author,…

  11. Introduction to special issue on machine learning approaches to shallow parsing

    NARCIS (Netherlands)

    Hammerton, J; Osborne, M; Armstrong, S; Daelemans, W

    2002-01-01

    This article introduces the problem of partial or shallow parsing (assigning partial syntactic structure to sentences) and explains why it is an important natural language processing (NLP) task. The complexity of the task makes Machine Learning an attractive option in comparison to the handcrafting

  12. Students' General Knowledge of the Learning Process: A Mixed Methods Study Illustrating Integrated Data Collection and Data Consolidation

    Science.gov (United States)

    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…

  13. Hyperbolic partial differential equations populations, reactors, tides and waves theory and applications

    CERN Document Server

    Witten, Matthew

    1983-01-01

    Hyperbolic Partial Differential Equations, Volume 1: Population, Reactors, Tides and Waves: Theory and Applications covers three general areas of hyperbolic partial differential equation applications. These areas include problems related to the McKendrick/Von Foerster population equations, other hyperbolic form equations, and the numerical solution.This text is composed of 15 chapters and begins with surveys of age specific population interactions, populations models of diffusion, nonlinear age dependent population growth with harvesting, local and global stability for the nonlinear renewal eq

  14. ‘His home is his castle. And mine is a cage’: a new partial defence for primary victims who kill

    OpenAIRE

    Wake, Nicola

    2015-01-01

    This article provides an in-depth analysis of the Crimes Amendment (Abolition of Defensive Homicide) Act 2014 which had the effect of repealing Victoria’s only generalpartial defence’ of defensive homicide, and replaced the existing statutory self-defence in murder/manslaughter provisions and general common law self- defence rules with a single test. The abolition of defensive homicide means there is now no generalpartial defence’ to accommodate cases falling short of self-defence. The ch...

  15. Active Learning in a Large General Physics Classroom.

    Science.gov (United States)

    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.

  16. The Reinforcement Learning Competition 2014

    OpenAIRE

    Dimitrakakis, Christos; Li, Guangliang; Tziortziotis, Nikoalos

    2014-01-01

    Reinforcement learning is one of the most general problems in artificial intelligence. It has been used to model problems in automated experiment design, control, economics, game playing, scheduling and telecommunications. The aim of the reinforcement learning competition is to encourage the development of very general learning agents for arbitrary reinforcement learning problems and to provide a test-bed for the unbiased evaluation of algorithms.

  17. 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....

  18. Teaching children generalized imitation skills: a case report.

    Science.gov (United States)

    Brown, Freddy Jackson; Peace, Natalie; Parsons, Rachel

    2009-03-01

    Generalized imitation plays an important role in the acquisition of new skills, in particular language and communication. In this case report a multiple exemplar training procedure, with an errorless learning phase, was used to teach Ben, a 13-year-old child with severe intellectual disabilities, to imitate behaviours modelled by an adult instructor. After exposure to seven multiple exemplars, Ben learned to imitate novel actions to criterion (i.e. generalized imitation). These skills were maintained at 90 percent at 6 week and 18 week follow-up. In line with earlier research, this article provides some further support for the finding that multiple exemplar training can facilitate the reliable emergence of generalized imitation skills. Topographically similar behaviours during the learning phase can be difficult to discriminate and hence can slow the learning process. Future research could explore how generalized imitation supports the development of basic communication and activity skills.

  19. Learning and Memory

    OpenAIRE

    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 ...

  20. Learning of grammar-like visual sequences by adults with and without language-learning disabilities.

    Science.gov (United States)

    Aguilar, Jessica M; Plante, Elena

    2014-08-01

    Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. In Study 1, adults with normal language (NL) or language-learning disability (LLD) were familiarized with the visual artificial grammar and then tested using items that conformed or deviated from the grammar. In Study 2, a 2nd sample of adults with NL and LLD were presented auditory word pairs with weak semantic associations (e.g., groom + clean) along with the visual learning task. Participants were instructed to attend to visual sequences and to ignore the auditory stimuli. Incidental encoding of these words would indicate reduced attention to the primary task. In Studies 1 and 2, both groups demonstrated learning and generalization of the artificial grammar. In Study 2, neither the NL nor the LLD group appeared to encode the words presented during the learning phase. The results argue against a general deficit in statistical learning for individuals with LLD and demonstrate that both NL and LLD learners can ignore extraneous auditory stimuli during visual learning.

  1. Difficulty in Learning Similar-Sounding Words: A Developmental Stage or a General Property of Learning?

    Science.gov (United States)

    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…

  2. An Experimental Investigation on the Ultimate Strength of Partially Infilled: Braced Steel Frames

    Science.gov (United States)

    Dubey, Shailendra Kumar Damodar; Kute, Sunil Y.

    2017-12-01

    Infilled walls are usually, considered as non-structural elements. However, these walls are effective in carrying lateral loads. In this regard, an experimental investigation was planned and conducted to study the effect of braced and partially infilled steel frames with cement mortar and concrete in comparison to the bare frames. All these frames were tested up to collapse and subjected only to horizontal loads to obtain an effective and possible solution for soft storey which are generally not infilled. In comparison to bare steel frames, partially infilled frames have an increase of lateral load capacity by 45-60%. Central bracing is more effective than that of the corner bracing. For the same load partially infilled frames have significantly less deflection than that of the bare frames. A reduced load factor is suggested for the design of soft storey columns with the partial infills. A mathematical model has been proposed to calculate the theoretical ultimate load for the braced, cement mortar and concrete partial infilled frames.

  3. Development of Learning to Learn Skills in Primary School

    Science.gov (United States)

    Vainikainen, Mari-Pauliina; Wüstenberg, Sascha; Kupiainen, Sirkku; Hotulainen, Risto; Hautamäki, Jarkko

    2015-01-01

    In Finland, schools' effectiveness in fostering the development of transversal skills is evaluated through large-scale learning to learn (LTL) assessments. This article presents how LTL skills--general cognitive competences and learning-related motivational beliefs--develop during primary school and how they predict pupils' CPS skills at the end…

  4. Generalization in adaptation to stable and unstable dynamics.

    Directory of Open Access Journals (Sweden)

    Abdelhamid Kadiallah

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

  5. Design of Online Report Writing Based on Constructive and Cooperative Learning for a Course on Traditional General Physics Experiments

    Science.gov (United States)

    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…

  6. What does it mean to be a General Practitioner?

    DEFF Research Database (Denmark)

    Olesen, Henning Salling

    2012-01-01

    Studying professional learning offers a particular contribution to learning research in general because professionals embody societal circumstances for learning in everyday life and work. This article refers to the medical profession. A general heuristic model is presented for organizing empirical...... studies in the experiences of everyday professional life, in which they are related to three dimensions: occupational framework, knowledge domain, and life history of the professional. Two examples of interpretation from general medical practice are presented, and the theoretical framework...

  7. Scikit-learn: Machine Learning in Python

    OpenAIRE

    Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu; Perrot, Matthieu

    2011-01-01

    International audience; Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic ...

  8. Scikit-learn: Machine Learning in Python

    OpenAIRE

    Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Louppe, Gilles; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu

    2012-01-01

    Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings....

  9. Extinction of laminar partially premixed flames

    Energy Technology Data Exchange (ETDEWEB)

    Aggarwal, Suresh K. [Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, 842 W. Taylor Street, Room 2039, MC-251, Chicago, IL 60607-7022 (United States)

    2009-12-15

    Flame extinction represents one of the classical phenomena in combustion science. It is important to a variety of combustion systems in transportation and power generation applications. Flame extinguishment studies are also motivated from the consideration of fire safety and suppression. Such studies have generally considered non-premixed and premixed flames, although fires can often originate in a partially premixed mode, i.e., fuel and oxidizer are partially premixed as they are transported to the reaction zone. Several recent investigations have considered this scenario and focused on the extinction of partially premixed flames (PPFs). Such flames have been described as hybrid flames possessing characteristics of both premixed and non-premixed flames. This paper provides a review of studies dealing with the extinction of PPFs, which represent a broad family of flames, including double, triple (tribrachial), and edge flames. Theoretical, numerical and experimental studies dealing with the extinction of such flames in coflow and counterflow configurations are discussed. Since these flames contain both premixed and non-premixed burning zones, a brief review of the dilution-induced extinction of premixed and non-premixed flames is also provided. For the coflow configuration, processes associated with flame liftoff and blowout are described. Since lifted non-premixed jet flames often contain a partially premixed or an edge-flame structure prior to blowout, the review also considers such flames. While the perspective of this review is broad focusing on the fundamental aspects of flame extinction and blowout, results mostly consider flame extinction caused by the addition of a flame suppressant, with relevance to fire suppression on earth and in space environment. With respect to the latter, the effect of gravity on the extinction of PPFs is discussed. Future research needs are identified. (author)

  10. Computational acceleration for MR image reconstruction in partially parallel imaging.

    Science.gov (United States)

    Ye, Xiaojing; Chen, Yunmei; Huang, Feng

    2011-05-01

    In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images.

  11. 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...

  12. 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 ...

  13. Conservation Laws for Partially Conservative Variable Mass Systems via d'Alembert's Principle

    Institute of Scientific and Technical Information of China (English)

    AFTAB Ahmed; NASEER Ahmed; QUDRAT Khan

    2008-01-01

    Conservation laws for partially conservative variable mass dynamical systems under symmetric infinitesimal transformations are determined. A generalization of Lagrange-d'Alembert's principle for a variable mass system in terms of asynchronous virtual variation is presented. The generalized Killing equations are obtained such that their solution yields the transformations and the associated conservation laws. An example illustrative of the theory is furnished at the end as well.

  14. LEARNING TECHNOLOGIES FOR STUDENTS IN THE CLOUD ORIENTED LEARNING ENVIRONMENT OF COMPREHENSIVE EDUCATIONAL INSTITUTIONS

    OpenAIRE

    Svitlana G. Lytvynova

    2015-01-01

    The paper analyzes the «flipped» learning and «Web Quest» technologies. The features of the «flipped» learning technology are generalized, as well as compared with traditional learning, clarified the benefits of the technology for teachers and students, described the features of the technology used by teacher and students, developed a teacher’s and student’s flow chart for preparation to the lesson, generalized control and motivation components for activating learning activities of students, ...

  15. Evaluation of deterioration of insulators in high-voltage motors by partial discharge

    International Nuclear Information System (INIS)

    Mikami, Masao

    2003-01-01

    For the purpose of early detection of deterioration of insulators in high-voltage motors which are widely utilized in nuclear power stations, a new type on-line partial discharge monitor developed at INSS was applied to test the deterioration of about 150 sets of high-voltage motors running in nuclear power stations practically. From the results, it is shown that (1) tendency of the deterioration can be obtained by this method in general, (2) the magnitude of the on-line partial discharge hardly correlates with that of off-line measurement, but depends on temperature and other environmental conditions, and (3) by observing phase characteristics of partial discharge, it is possible to make a diagnosis of phase-to-phase tracking in end-winding coils of a stator. (author)

  16. Customized Videos on a YouTube Channel: A beyond the Classroom Teaching and Learning Platform for General Chemistry Courses

    Science.gov (United States)

    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…

  17. Tailoring Earned Value Management. General Guidelines

    National Research Council Canada - National Science Library

    2002-01-01

    Partial Contents: General Principles, A Spectrum of Implementation, OMB Guidance, A Special Note about DOD, Risk Factors to Consider, How can EVMS be tailored, Tailor EVMS to Inherent Risk, Application Thresholds-DoD...

  18. Query construction, entropy, and generalization in neural-network models

    Science.gov (United States)

    Sollich, Peter

    1994-05-01

    We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

  19. Compatriot partiality and cosmopolitan justice: Can we justify compatriot partiality within the cosmopolitan framework?

    Directory of Open Access Journals (Sweden)

    Rachelle Bascara

    2016-10-01

    Full Text Available This paper shows an alternative way in which compatriot partiality could be justified within the framework of global distributive justice. Philosophers who argue that compatriot partiality is similar to racial partiality capture something correct about compatriot partiality. However, the analogy should not lead us to comprehensively reject compatriot partiality. We can justify compatriot partiality on the same grounds that liberation movements and affirmative action have been justified. Hence, given cosmopolitan demands of justice, special consideration for the economic well-being of your nation as a whole is justified if and only if the country it identifies is an oppressed developing nation in an unjust global order.This justification is incomplete. We also need to say why Person A, qua national of Country A, is justified in helping her compatriots in Country A over similarly or slightly more oppressed non-compatriots in Country B. I argue that Person A’s partiality towards her compatriots admits further vindication because it is part of an oppressed group’s project of self-emancipation, which is preferable to paternalistic emancipation.Finally, I identify three benefits in my justification for compatriot partiality. First, I do not offer a blanket justification for all forms of compatriot partiality. Partiality between members of oppressed groups is only a temporary effective measure designed to level an unlevel playing field. Second, because history attests that sovereign republics could arise as a collective response to colonial oppression, justifying compatriot partiality on the grounds that I have identified is conducive to the development of sovereignty and even democracy in poor countries, thereby avoiding problems of infringement that many humanitarian poverty alleviation efforts encounter. Finally, my justification for compatriot partiality complies with the implicit cosmopolitan commitment to the realizability of global justice

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

    Science.gov (United States)

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

    2017-04-01

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

  1. Extinction of conditioned fear is better learned and recalled in the morning than in the evening.

    Science.gov (United States)

    Pace-Schott, Edward F; Spencer, Rebecca M C; Vijayakumar, Shilpa; Ahmed, Nafis A K; Verga, Patrick W; Orr, Scott P; Pitman, Roger K; Milad, Mohammed R

    2013-11-01

    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 (SCRs) to 2 differently colored lamps (CS+), but not a third color (CS-), within the computer image of a room (conditioning context). One CS+ (CS + E) but not the other (CS + U) was immediately extinguished by un-reinforced presentations in a different room (extinction context). Delay durations of 3 h (within AM or PM), 12 h (morning-to-evening or evening-to-morning) or 24 h (morning-to-morning or evening-to-evening) followed. In Session 2, extinction recall and contextual fear renewal were tested. We observed no significant effects of the delay interval on extinction memory but did observe an effect of time-of-day. Fear extinction was significantly better if learned in the morning (p = .002). Collapsing across CS + type, there was smaller morning differential SCR at both extinction recall (p = .003) and fear renewal (p = .005). Morning extinction recall showed better generalization from the CS + E to CS + U with the response to the CS + U significantly larger than to the CS + E only in the evening (p = .028). Thus, extinction is learned faster and its memory is better generalized in the morning. Cortisol and testosterone showed the expected greater salivary levels in the morning when higher testosterone/cortisol ratio also predicted better extinction learning. Circadian factors may promote morning extinction. Alternatively, evening homeostatic sleep pressure may impede extinction and favor recall of conditioned fear. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Organizational Learning Strategies and Verbal Memory Deficits in Bipolar Disorder.

    Science.gov (United States)

    Nitzburg, George C; Cuesta-Diaz, Armando; Ospina, Luz H; Russo, Manuela; Shanahan, Megan; Perez-Rodriguez, Mercedes; Larsen, Emmett; Mulaimovic, Sandra; Burdick, Katherine E

    2017-04-01

    Verbal memory (VM) impairment is prominent in bipolar disorder (BD) and is linked to functional outcomes. However, the intricacies of VM impairment have not yet been studied in a large sample of BD patients. Moreover, some have proposed VM deficits that may be mediated by organizational strategies, such as semantic or serial clustering. Thus, the exact nature of VM break-down in BD patients is not well understood, limiting remediation efforts. We investigated the intricacies of VM deficits in BD patients versus healthy controls (HCs) and examined whether verbal learning differences were mediated by use of clustering strategies. The California Verbal Learning Test (CVLT) was administered to 113 affectively stable BD patients and 106 HCs. We compared diagnostic groups on all CVLT indices and investigated whether group differences in verbal learning were mediated by clustering strategies. Although BD patients showed significantly poorer attention, learning, and memory, these indices were only mildly impaired. However, BD patients evidenced poorer use of effective learning strategies and lower recall consistency, with these indices falling in the moderately impaired range. Moreover, relative reliance on semantic clustering fully mediated the relationship between diagnostic category and verbal learning, while reliance on serial clustering partially mediated this relationship. VM deficits in affectively stable bipolar patients were widespread but were generally mildly impaired. However, patients displayed inadequate use of organizational strategies with clear separation from HCs on semantic and serial clustering. Remediation efforts may benefit from education about mnemonic devices or "chunking" techniques to attenuate VM deficits in BD. (JINS, 2017, 23, 358-366).

  3. Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching

    International Nuclear Information System (INIS)

    Kouvaritakis, N.; Soria, A.; Isoard, S.

    2000-01-01

    This paper presents a module endogenising technical change which is capable of being attached to large scale energy models that follow an adaptive-expectations. The formulation includes, apart from the more classical learning by doing effects, quantitative relationships between technology performance and R and D expenditure. It even attempts to go further by partially endogenising the latter by incorporating an optimisation module describing private equipment manufacturers' R and D budget allocation in a context of risk and expectation. Having presented this module in abstract, the paper proceeds to describe how an operational version of it has been constructed and implemented inside a large-scale partial equilibrium world energy model (the POLES model). Concerning learning functions problems associated with the data are alluded to, the hybrid econometric methods used to estimate them are presented as well as the adjustments which had to be effected to ensure a smooth incorporation into the large model. In the final sections is explained the use of the model itself to generate partial foresight parameters for the determination of return expectations particularly in view of CO 2 constraints and associated carbon values. (orig.)

  4. Essays on partial retirement

    NARCIS (Netherlands)

    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

  5. Computation of partially invariant solutions for the Einstein Walker manifolds' identifying equations

    Science.gov (United States)

    Nadjafikhah, Mehdi; Jafari, Mehdi

    2013-12-01

    In this paper, partially invariant solutions (PISs) method is applied in order to obtain new four-dimensional Einstein Walker manifolds. This method is based on subgroup classification for the symmetry group of partial differential equations (PDEs) and can be regarded as the generalization of the similarity reduction method. For this purpose, those cases of PISs which have the defect structure δ=1 and are resulted from two-dimensional subalgebras are considered in the present paper. Also it is shown that the obtained PISs are distinct from the invariant solutions that obtained by similarity reduction method.

  6. Hydrological balance and water transport processes of partially sealed soils

    Science.gov (United States)

    Timm, Anne; Wessolek, Gerd

    2017-04-01

    With increased urbanisation, soil sealing and its drastic effects on hydrological processes have received a lot of attention. Based on safety concerns, there has been a clear focus on urban drainage and prevention of urban floods caused by storm water events. For this reason, any kind of sealing is often seen as impermeable runoff generator that prevents infiltration and evaporation. While many hydrological models, especially storm water models, have been developed, there are only a handful of empirical studies actually measuring the hydrological balance of (partially) sealed surfaces. These challenge the general assumption of negligible infiltration and evaporation and show that these processes take place even for severe sealing such as asphalt. Depending on the material, infiltration from partially sealed surfaces can be equal to that of vegetated ones. Therefore, more detailed knowledge is needed to improve our understanding and models. In Berlin, two partially sealed weighable lysimeters were equipped with multiple temperature and soil moisture sensors in order to study their hydrological balance, as well as water and heat transport processes within the soil profile. This combination of methods affirms previous observations and offers new insights into altered hydrological processes of partially sealed surfaces at a small temporal scale. It could be verified that not all precipitation is transformed into runoff. Even for a relatively high sealing degree of concrete slabs with narrow seams, evaporation and infiltration may exceed runoff. Due to the lack of plant roots, the hydrological balance is mostly governed by precipitation events and evaporation generally occurs directly after rainfall. However, both surfaces allow for upward water transport from the upper underlying soil layers, sometimes resulting in relatively low evaporation rates on days without precipitation. The individual response of the surfaces differs considerably, which illustrates how

  7. Consideration on Singularities in Learning Theory and the Learning Coefficient

    Directory of Open Access Journals (Sweden)

    Miki Aoyagi

    2013-09-01

    Full Text Available We consider the learning coefficients in learning theory and give two new methods for obtaining these coefficients in a homogeneous case: a method for finding a deepest singular point and a method to add variables. In application to Vandermonde matrix-type singularities, we show that these methods are effective. The learning coefficient of the generalization error in Bayesian estimation serves to measure the learning efficiency in singular learning models. Mathematically, the learning coefficient corresponds to a real log canonical threshold of singularities for the Kullback functions (relative entropy in learning theory.

  8. The role of self-regulated learning in explaining examination performance of college students in first-semester general chemistry

    Science.gov (United States)

    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

  9. The Effect Of Islamic Education Learning Pai And Learning Results To Students Religious Behavior Of Stisip Widyapuri Mandiri Sukabumi Student

    Directory of Open Access Journals (Sweden)

    U. Abdullah Mumin

    2017-06-01

    Full Text Available The purpose of this study is to measure the level of the effect of Islamic Education learning and learning result on religious behaviour in STISIP Widyapuri Mandiri Sukabumi. The method used in this research is quantitative analysis based on inferential statistical model. The data collection is done by using observation techniques interviews and questionnaires. The researcher analize the data by using logic analysis for qualitative and statistical analysis for quantitative data by using descriptive statistics regression and correlation. Based on the hypothesis test simultaneously PAI learning and learning result have a positive and significant effect on students religious behaviour. Partially only PAI learning alone has a positive and significant impact on religious behavior.

  10. Some Common Fixed Point Theorems for F-Contraction Type Mappings in 0-Complete Partial Metric Spaces

    Directory of Open Access Journals (Sweden)

    Satish Shukla

    2013-01-01

    Full Text Available We prove some common fixed point theorems for F-contractions in 0-complete partial metric spaces. Our results extend, generalize, and unify several known results in the literature. Some examples are included which show that the generalization is proper.

  11. Lower bounds for the circuit size of partially homogeneous polynomials

    Czech Academy of Sciences Publication Activity Database

    Le, Hong-Van

    2017-01-01

    Roč. 225, č. 4 (2017), s. 639-657 ISSN 1072-3374 Institutional support: RVO:67985840 Keywords : partially homogeneous polynomials * polynomials Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) https://link.springer.com/article/10.1007/s10958-017-3483-4

  12. LEARNING TECHNOLOGIES FOR STUDENTS IN THE CLOUD ORIENTED LEARNING ENVIRONMENT OF COMPREHENSIVE EDUCATIONAL INSTITUTIONS

    Directory of Open Access Journals (Sweden)

    Svitlana G. Lytvynova

    2015-06-01

    Full Text Available The paper analyzes the «flipped» learning and «Web Quest» technologies. The features of the «flipped» learning technology are generalized, as well as compared with traditional learning, clarified the benefits of the technology for teachers and students, described the features of the technology used by teacher and students, developed a teacher’s and student’s flow chart for preparation to the lesson, generalized control and motivation components for activating learning activities of students, found out that a component of cloud oriented learning environment (COLE – Lync (Skype Pro can be used to develop video clips and support «flipped» learning technology. The author defines the concept of «Web Quest» technology, generalizes the «Web Quest» structure components. In the article the functions, features of this technology, the types of problems that can be solved with the help of this technology, as well as «Web Quest» classification are presented. It has been found out that the cloud oriented learning environment gives all the possibilities for «Web Quest» technology implementation in teaching of different subjects of all branches of science. With the help of «flipped» technology training and «Web Quest» a number of important problems of education can be solved – providing the continuous communication intensive training beyond general educational establishment and activation of learning activities of students.

  13. Partial pressures of oxygen, phosphorus and fluorine in some lunar lavas

    Science.gov (United States)

    Nash, W. P.; Hausel, W. D.

    1973-01-01

    Lunar sample 14310 is a feldspar-rich basalt which shows no evidence of shock deformation or recrystallization. Pyroxenes include Mg-rich orthopyroxene, pigeonite and augite; pyroxferroite occurs in the interstitial residuum. Plagioclase feldspars are zoned from An(96) to An(67), and variations in feldspar compositions do not necessarily indicate loss of Na during eruption of the lava. Opaque phases include ilmenite, ulvospinel, metallic iron, troilite, and schreibersite. Both whitlockite and apatite are present, and the interstitial residua contain baddeleyite, tranquillityite and barium-rich sanidine. Theoretical calculations provide estimates of partial pressures of oxygen, phosphorus, and fluorine in lunar magmas. In general, partial pressures of oxygen are restricted by the limiting assemblages of iron-wuestite and ilmenite-iron-rutile; phosphorus partial pressures are higher in lunar magmas than in terrestrial lavas. The occurrence of whitlockite indicates significantly lower fugacities of fluorine in lunar magmas than in terrestrial magmas.

  14. Representations of Lie algebras and partial differential equations

    CERN Document Server

    Xu, Xiaoping

    2017-01-01

    This book provides explicit representations of finite-dimensional simple Lie algebras, related partial differential equations, linear orthogonal algebraic codes, combinatorics and algebraic varieties, summarizing the author’s works and his joint works with his former students.  Further, it presents various oscillator generalizations of the classical representation theorem on harmonic polynomials, and highlights new functors from the representation category of a simple Lie algebra to that of another simple Lie algebra. Partial differential equations play a key role in solving certain representation problems. The weight matrices of the minimal and adjoint representations over the simple Lie algebras of types E and F are proved to generate ternary orthogonal linear codes with large minimal distances. New multi-variable hypergeometric functions related to the root systems of simple Lie algebras are introduced in connection with quantum many-body systems in one dimension. In addition, the book identifies certai...

  15. Test Framing Generates a Stability Bias for Predictions of Learning by Causing People to Discount their Learning Beliefs

    Science.gov (United States)

    Ariel, Robert; Hines, Jarrod C.; Hertzog, Christopher

    2014-01-01

    People estimate minimal changes in learning when making predictions of learning (POLs) for future study opportunities despite later showing increased performance and an awareness of that increase (Kornell & Bjork, 2009). This phenomenon is conceptualized as a stability bias in judgments about learning. We investigated the malleability of this effect, and whether it reflected people’s underlying beliefs about learning. We manipulated prediction framing to emphasize the role of testing vs. studying on memory and directly measured beliefs about multi-trial study effects on learning by having participants construct predicted learning curves before and after the experiment. Mean POLs were more sensitive to the number of study-test opportunities when performance was framed in terms of study benefits rather than testing benefits and POLs reflected pre-existing beliefs about learning. The stability bias is partially due to framing and reflects discounted beliefs about learning benefits rather than inherent belief in the stability of performance. PMID:25067885

  16. Conservation Laws for Partially Conservative Variable Mass Systems via d'Alembert's Principle

    International Nuclear Information System (INIS)

    Ahmed, Aftab; Ahmed, Naseer; Khan, Qudrat

    2008-01-01

    Conservation laws for partially conservative variable mass dynamical systems under symmetric infinitesimal transformations are determined. A generalization of Lagrange-d'Alembert's principle for a variable mass system in terms of asynchronous virtual variation is presented. The generalized Killing equations are obtained such that their solution yields the transformations and the associated conservation laws. An example illustrative of the theory is furnished at the end as well. (the physics of elementary particles and fields)

  17. Early adversity and learning: implications for typical and atypical behavioral development.

    Science.gov (United States)

    Hanson, Jamie L; van den Bos, Wouter; Roeber, Barbara J; Rudolph, Karen D; Davidson, Richard J; Pollak, Seth D

    2017-07-01

    Children who experience early adversity often develop emotion regulatory problems, but little is known about the mechanisms that mediate this relation. We tested whether general associative learning processes contribute to associations between adversity, in the form of child maltreatment, and negative behavioral outcomes. Eighty-one participants between 12 and 17 years of age were recruited for this study and completed a probabilistic learning Task. Forty-one of these participants had been exposed to physical abuse, a form of early adversity. Forty additional participants without any known history of maltreatment served as a comparison group. All participants (and their parents) also completed portions of the Youth Life Stress Interview to understand adolescent's behavior. We calculated measures of associative learning, and also constructed mathematical models of learning. We found that adolescents exposed to high levels of adversity early in their lives had lower levels of associative learning than comparison adolescents. In addition, we found that impaired associative learning partially explained the higher levels of behavioral problems among youth who suffered early adversity. Using mathematical models, we also found that two components of learning were specifically affected in children exposed to adversity: choice variability and biases in their beliefs about the likelihood of rewards in the environment. Participants who had been exposed to early adversity were less able than their peers to correctly learn which stimuli were likely to result in reward, even after repeated feedback. These individuals also used information about known rewards in their environments less often. In addition, individuals exposed to adversity made decisions early in the learning process as if rewards were less consistent and occurred more at random. These data suggest one mechanism through which early life experience shapes behavioral development. © 2017 Association for Child and

  18. On-line learning through simple perceptron learning with a margin.

    Science.gov (United States)

    Hara, Kazuyuki; Okada, Masato

    2004-03-01

    We analyze a learning method that uses a margin kappa a la Gardner for simple perceptron learning. This method corresponds to the perceptron learning when kappa = 0 and to the Hebbian learning when kappa = infinity. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and found that it was the same as for perceptron learning. We also investigated an adaptive margin control method.

  19. Learning from neural control.

    Science.gov (United States)

    Wang, Cong; Hill, David J

    2006-01-01

    One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.

  20. Learning Low-Dimensional Metrics

    OpenAIRE

    Jain, Lalit; Mason, Blake; Nowak, Robert

    2017-01-01

    This paper investigates the theoretical foundations of metric learning, focused on three key questions that are not fully addressed in prior work: 1) we consider learning general low-dimensional (low-rank) metrics as well as sparse metrics; 2) we develop upper and lower (minimax)bounds on the generalization error; 3) we quantify the sample complexity of metric learning in terms of the dimension of the feature space and the dimension/rank of the underlying metric;4) we also bound the accuracy ...

  1. 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...

  2. Reinforcement Learning State-of-the-Art

    CERN Document Server

    Wiering, Marco

    2012-01-01

    Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together the...

  3. A linearizing transformation for the Korteweg-de Vries equation; generalizations to higher-dimensional nonlinear partial differential equations

    NARCIS (Netherlands)

    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

  4. Multigrid for high dimensional elliptic partial differential equations on non-equidistant grids

    NARCIS (Netherlands)

    bin Zubair, H.; Oosterlee, C.E.; Wienands, R.

    2006-01-01

    This work presents techniques, theory and numbers for multigrid in a general d-dimensional setting. The main focus is the multigrid convergence for high-dimensional partial differential equations (PDEs). As a model problem we have chosen the anisotropic diffusion equation, on a unit hypercube. We

  5. Hospitalization for partial nephrectomy was not associated with intrathecal opioid analgesia: Retrospective analysis.

    Science.gov (United States)

    Weingarten, Toby N; Del Mundo, Serena B; Yeoh, Tze Yeng; Scavonetto, Federica; Leibovich, Bradley C; Sprung, Juraj

    2014-10-01

    The aim of this retrospective study is to test the hypothesis that the use of spinal analgesia shortens the length of hospital stay after partial nephrectomy. We reviewed all patients undergoing partial nephrectomy for malignancy through flank incision between January 1, 2008, and June 30, 2011. We excluded patients who underwent tumor thrombectomy, used sustained-release opioids, or had general anesthesia supplemented by epidural analgesia. Patients were grouped into "spinal" (intrathecal opioid injection for postoperative analgesia) versus "general anesthetic" group, and "early" discharge group (within 3 postoperative days) versus "late" group. Association between demographics, patient physical status, anesthetic techniques, and surgical complexity and hospital stay were analyzed using multivariable logistic regression analysis. Of 380 patients, 158 (41.6%) were discharged "early" and 151 (39.7%) were "spinal" cases. Both spinal and early discharge groups had better postoperative pain control and used less postoperative systemic opioids. Spinal analgesia was associated with early hospital discharge, odds ratio 1.52, (95% confidence interval 1.00-2.30), P = 0.05, but in adjusted analysis was no longer associated with early discharge, 1.16 (0.73-1.86), P = 0.52. Early discharge was associated with calendar year, with more recent years being associated with early discharge. Spinal analgesia combined with general anesthesia was associated with improved postoperative pain control during the 1(st) postoperative day, but not with shorter hospital stay following partial nephrectomy. Therefore, unaccounted practice changes that occurred during more recent times affected hospital stay.

  6. General Relativity: Geometry Meets Physics

    Science.gov (United States)

    Thomsen, Dietrick E.

    1975-01-01

    Observing the relationship of general relativity and the geometry of space-time, the author questions whether the rest of physics has geometrical explanations. As a partial answer he discusses current research on subatomic particles employing geometric transformations, and cites the existence of geometrical definitions of physical quantities such…

  7. Anatomic partial nephrectomy: technique evolution.

    Science.gov (United States)

    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.

  8. Nonclassical Symmetries for Nonlinear Partial Differential Equations via Compatibility

    International Nuclear Information System (INIS)

    El-Sabbagh, Mostafa F.; Ahmad, Ali T.

    2011-01-01

    The determining equations for the nonclassical symmetry reductions of nonlinear partial differential equations with arbitrary order can be obtained by requiring the compatibility between the original equations and the invariant surface conditions. The (2+1)-dimensional shallow water wave equation, Boussinesq equation, and the dispersive wave equations in shallow water serve as examples illustrating how compatibility leads quickly and easily to the determining equations for their nonclassical symmetries. (general)

  9. Definitions of Health Terms: General Health

    Science.gov (United States)

    ... needs to stay healthy. You can start by learning these general health terms. Find more definitions on Fitness | General Health | Minerals | Nutrition | Vitamins Basal Body Temperature Basal body temperature is your temperature at rest ...

  10. Surgeon General's Family Health History Initiative

    Science.gov (United States)

    ... Source Code The Surgeon General's Family Health History Initiative To help focus attention on the importance of ... health campaign, called the Surgeon General's Family History Initiative, to encourage all American families to learn more ...

  11. Two echelon partial trade credit financing in a supply chain derived algebraically

    Directory of Open Access Journals (Sweden)

    Jaggi Chandra K.

    2012-01-01

    Full Text Available Trade credit financing has become a powerful tool to improve sales & profit in an industry. In general, a supplier/retailer frequently offers trade credit to its credit risk downstream member in order to stimulate their respective sales. This trade credit may either be full or partial depending upon the past profile of the downstream member. Partial trade credit may be offered by the supplier/retailer to their credit risk downstream member who must pay a portion of the purchase amount at the time of placing an order and then receives a permissible delay on the rest of the outstanding amount to avoid non-payment risks. The present study investigates the retailer’s inventory problem under partial trade credit financing for two echelon supply chain where the supplier, as well as the retailer, offers partial trade credit to the subsequent downstream member. An algebraic approach has been applied for finding the retailer’s optimal ordering policy under minimizing the annual total relevant cost. Results have been validated with the help of examples followed by comprehensive sensitivity analysis.

  12. Partial quantization of Lagrangian-Hamiltonian systems

    International Nuclear Information System (INIS)

    Amaral, C.M. do; Soares Filho, P.C.

    1979-05-01

    A classical variational principle is constructed in the Weiss form, for dynamical systems with support spaces of the configuration-phase kind. This extended principle rules the dynamics of classical systems, partially Hamiltonian, in interaction with Lagrangean parameterized subsidiary dynamics. The variational family of equations obtained, consists of an equation of the Hamilton-Jacobi type, coupled to a family of differential equations of the Euler-Lagrange form. The basic dynamical function appearing in the equations is a function of the Routh kind. By means of an ansatz induced by the variationally obtained family, a generalized set of equation, is proposed constituted by a wave equation of Schroedinger type, coupled to a family of equations formaly analog to those Euler-Lagrange equations. A basic operator of Routh type appears in our generalized set of equations. This operator describes the interaction between a quantized Hamiltonian dynamics, with a parameterized classical Lagrangean dynamics in semi-classical closed models. (author) [pt

  13. Algebraic dynamics solutions and algebraic dynamics algorithm for nonlinear partial differential evolution equations of dynamical systems

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Using functional derivative technique in quantum field theory, the algebraic dy-namics approach for solution of ordinary differential evolution equations was gen-eralized to treat partial differential evolution equations. The partial differential evo-lution equations were lifted to the corresponding functional partial differential equations in functional space by introducing the time translation operator. The functional partial differential evolution equations were solved by algebraic dynam-ics. The algebraic dynamics solutions are analytical in Taylor series in terms of both initial functions and time. Based on the exact analytical solutions, a new nu-merical algorithm—algebraic dynamics algorithm was proposed for partial differ-ential evolution equations. The difficulty of and the way out for the algorithm were discussed. The application of the approach to and computer numerical experi-ments on the nonlinear Burgers equation and meteorological advection equation indicate that the algebraic dynamics approach and algebraic dynamics algorithm are effective to the solution of nonlinear partial differential evolution equations both analytically and numerically.

  14. Partial Thermalization of Correlations in pA and AA collisionss

    Science.gov (United States)

    Gavin, Sean; Moschelli, George; Zin, Christopher

    2017-09-01

    Correlations born before the onset of hydrodynamic flow can leave observable traces on the final state particles. Measurement of these correlations can yield important information on the isotropization and thermalization process. Starting with Israel-Stewart hydrodynamics and Boltzmann-like kinetic theory in the presence of dynamic Langevin noise, we derive new partial differential equations for two-particle correlation functions. To illustrate how these equations can be used, we study the effect of thermalization on long range correlations. We show quite generally that two particle correlations at early times depend on S, the average probability that a parton suffers no interactions. We extract S from transverse momentum fluctuations measured in Pb+Pb collisions and predict the degree of partial thermalization in pA experiments. NSF-PHY-1207687.

  15. Transform analysis of generalized functions

    CERN Document Server

    Misra, O P

    1986-01-01

    Transform Analysis of Generalized Functions concentrates on finite parts of integrals, generalized functions and distributions. It gives a unified treatment of the distributional setting with transform analysis, i.e. Fourier, Laplace, Stieltjes, Mellin, Hankel and Bessel Series.Included are accounts of applications of the theory of integral transforms in a distributional setting to the solution of problems arising in mathematical physics. Information on distributional solutions of differential, partial differential equations and integral equations is conveniently collected here.The volume will

  16. Generative Inferences Based on Learned Relations

    Science.gov (United States)

    Chen, Dawn; Lu, Hongjing; Holyoak, Keith J.

    2017-01-01

    A key property of relational representations is their "generativity": From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from…

  17. Do Science Teachers Distinguish Between Their own Learning and the Learning of Their Students?

    Science.gov (United States)

    Brauer, Heike; Wilde, Matthias

    2018-02-01

    Learning beliefs influence learning and teaching. For this reason, teachers and teacher educators need to be aware of them. To support students' knowledge construction, teachers must develop appropriate learning and teaching beliefs. Teachers appear to have difficulties when analysing students' learning. This seems to be due to the inability to differentiate the beliefs about their students' learning from those about their own learning. Both types of beliefs seem to be intertwined. This study focuses on whether pre-service teachers' beliefs about their own learning are identical to those about their students' learning. Using a sample of pre-service teachers, we measured general beliefs about "constructivist" and "transmissive" learning and science-specific beliefs about "connectivity" and "taking pre-concepts into account". We also analysed the development of these four beliefs during teacher professionalisation by comparing beginning and advanced pre-service teachers. Our results show that although pre-service teachers make the distinction between their own learning and the learning of their students for the general tenets of constructivist and transmissive learning, there is no significant difference for science-specific beliefs. The beliefs pre-service teachers hold about their students' science learning remain closely tied to their own.

  18. Learning Design Patterns for Hybrid Synchronous Video-Mediated Learning Environments

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    This article describes an innovative learning environment where remote and face-to-face full-time general upper secondary adult students jointly participate in the same live classes at VUC Storstrøm, an adult learning centre in Denmark. The teachers developed new learning designs as a part of the...... activating and equal learning designs for the students. This article is written on the basis of a chapter in the PhD–thesis by the author....

  19. Theoretical Foundations of Active Learning

    Science.gov (United States)

    2009-05-01

    I study the informational complexity of active learning in a statistical learning theory framework. Specifically, I derive bounds on the rates of...convergence achievable by active learning , under various noise models and under general conditions on the hypothesis class. I also study the theoretical...advantages of active learning over passive learning, and develop procedures for transforming passive learning algorithms into active learning algorithms

  20. Selected chapters from general chemistry in physics teaching with the help of e - learning

    Science.gov (United States)

    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.

  1. Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model.

    Science.gov (United States)

    De Leeuw, R A; Westerman, Michiel; Nelson, E; Ket, J C F; Scheele, F

    2016-07-08

    E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings.

  2. 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.

  3. Towards a Robuster Interpretive Parsing: learning from overt forms in Optimality Theory

    NARCIS (Netherlands)

    Biró, T.

    2013-01-01

    The input data to grammar learning algorithms often consist of overt forms that do not contain full structural descriptions. This lack of information may contribute to the failure of learning. Past work on Optimality Theory introduced Robust Interpretive Parsing (RIP) as a partial solution to this

  4. Improving maximum power point tracking of partially shaded photovoltaic system by using IPSO-BELBIC

    International Nuclear Information System (INIS)

    El-Garhy, M. Abd Al-Alim; Mubarak, R.I.; El-Bably, M.

    2017-01-01

    Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

  5. Improving maximum power point tracking of partially shaded photovoltaic system by using IPSO-BELBIC

    Science.gov (United States)

    Al-Alim El-Garhy, M. Abd; Mubarak, R. I.; El-Bably, M.

    2017-08-01

    Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

  6. A generalized partially linear mean-covariance regression model for longitudinal proportional data, with applications to the analysis of quality of life data from cancer clinical trials.

    Science.gov (United States)

    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.

  7. Learning to Read Empirical Articles in General Psychology

    Science.gov (United States)

    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…

  8. Impression Procedures for Metal Frame Removable Partial Dentures as Applied by General Dental Practitioners.

    Science.gov (United States)

    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.

  9. An analysis of how electromagnetic induction and Faraday's law are presented in general physics textbooks, focusing on learning difficulties

    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)

  10. Posthuman learning

    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...

  11. Noradrenergic Stimulation Impairs Memory Generalization in Women.

    Science.gov (United States)

    Kluen, Lisa Marieke; Agorastos, Agorastos; Wiedemann, Klaus; Schwabe, Lars

    2017-07-01

    Memory generalization is essential for adaptive decision-making and action. Our ability to generalize across past experiences relies on medial-temporal lobe structures, known to be highly sensitive to stress. Recent evidence suggests that stressful events may indeed interfere with memory generalization. Yet, the mechanisms involved in this generalization impairment are unknown. We tested here whether a pharmacological elevation of major stress mediators-noradrenaline and glucocorticoids-is sufficient to disrupt memory generalization. In a double-blind, placebo-controlled design, healthy men and women received orally a placebo, hydrocortisone, the α2-adrenoceptor antagonist yohimbine that leads to increased noradrenergic stimulation, or both drugs, before they completed an associative learning task probing memory generalization. Drugs left learning performance intact. Yohimbine, however, led to a striking generalization impairment in women, but not in men. Hydrocortisone, in turn, had no effect on memory generalization, neither in men nor in women. The present findings indicate that increased noradrenergic activity, but not cortisol, is sufficient to disrupt memory generalization in a sex-specific manner, with relevant implications for stress-related mental disorders characterized by generalization deficits.

  12. A Partial Test of Agnew's General Theory of Crime and Delinquency

    Science.gov (United States)

    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…

  13. Negatively-marked MCQ assessments that reward partial knowledge do not introduce gender bias yet increase student performance and satisfaction and reduce anxiety.

    Directory of Open Access Journals (Sweden)

    A Elizabeth Bond

    Full Text Available Multiple-choice question (MCQ examinations are increasingly used as the assessment method of theoretical knowledge in large class-size modules in many life science degrees. MCQ-tests can be used to objectively measure factual knowledge, ability and high-level learning outcomes, but may also introduce gender bias in performance dependent on topic, instruction, scoring and difficulty. The 'Single Answer' (SA test is often used in which students choose one correct answer, in which they are unable to demonstrate partial knowledge. Negatively marking eliminates the chance element of guessing but may be considered unfair. Elimination testing (ET is an alternative form of MCQ, which discriminates between all levels of knowledge, while rewarding demonstration of partial knowledge. Comparisons of performance and gender bias in negatively marked SA and ET tests have not yet been performed in the life sciences. Our results show that life science students were significantly advantaged by answering the MCQ test in elimination format compared to single answer format under negative marking conditions by rewarding partial knowledge of topics. Importantly, we found no significant difference in performance between genders in either cohort for either MCQ test under negative marking conditions. Surveys showed that students generally preferred ET-style MCQ testing over SA-style testing. Students reported feeling more relaxed taking ET MCQ and more stressed when sitting SA tests, while disagreeing with being distracted by thinking about best tactics for scoring high. Students agreed ET testing improved their critical thinking skills. We conclude that appropriately-designed MCQ tests do not systematically discriminate between genders. We recommend careful consideration in choosing the type of MCQ test, and propose to apply negative scoring conditions to each test type to avoid the introduction of gender bias. The student experience could be improved through the

  14. Negatively-marked MCQ assessments that reward partial knowledge do not introduce gender bias yet increase student performance and satisfaction and reduce anxiety.

    Science.gov (United States)

    Bond, A Elizabeth; Bodger, Owen; Skibinski, David O F; Jones, D Hugh; Restall, Colin J; Dudley, Edward; van Keulen, Geertje

    2013-01-01

    Multiple-choice question (MCQ) examinations are increasingly used as the assessment method of theoretical knowledge in large class-size modules in many life science degrees. MCQ-tests can be used to objectively measure factual knowledge, ability and high-level learning outcomes, but may also introduce gender bias in performance dependent on topic, instruction, scoring and difficulty. The 'Single Answer' (SA) test is often used in which students choose one correct answer, in which they are unable to demonstrate partial knowledge. Negatively marking eliminates the chance element of guessing but may be considered unfair. Elimination testing (ET) is an alternative form of MCQ, which discriminates between all levels of knowledge, while rewarding demonstration of partial knowledge. Comparisons of performance and gender bias in negatively marked SA and ET tests have not yet been performed in the life sciences. Our results show that life science students were significantly advantaged by answering the MCQ test in elimination format compared to single answer format under negative marking conditions by rewarding partial knowledge of topics. Importantly, we found no significant difference in performance between genders in either cohort for either MCQ test under negative marking conditions. Surveys showed that students generally preferred ET-style MCQ testing over SA-style testing. Students reported feeling more relaxed taking ET MCQ and more stressed when sitting SA tests, while disagreeing with being distracted by thinking about best tactics for scoring high. Students agreed ET testing improved their critical thinking skills. We conclude that appropriately-designed MCQ tests do not systematically discriminate between genders. We recommend careful consideration in choosing the type of MCQ test, and propose to apply negative scoring conditions to each test type to avoid the introduction of gender bias. The student experience could be improved through the incorporation of the

  15. Learning of Grammar-Like Visual Sequences by Adults with and without Language-Learning Disabilities

    Science.gov (United States)

    Aguilar, Jessica M.; Plante, Elena

    2014-01-01

    Purpose: Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. Method: In Study 1,…

  16. Sampling Assumptions in Inductive Generalization

    Science.gov (United States)

    Navarro, Daniel J.; Dry, Matthew J.; Lee, Michael D.

    2012-01-01

    Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key "sampling" assumption about how the available data were generated.…

  17. Partial lesions of the intratemporal segment of the facial nerve: graft versus partial reconstruction.

    Science.gov (United States)

    Bento, Ricardo F; Salomone, Raquel; Brito, Rubens; Tsuji, Robinson K; Hausen, Mariana

    2008-09-01

    In cases of partial lesions of the intratemporal segment of the facial nerve, should the surgeon perform an intraoperative partial reconstruction, or partially remove the injured segment and place a graft? We present results from partial lesion reconstruction on the intratemporal segment of the facial nerve. A retrospective study on 42 patients who presented partial lesions on the intratemporal segment of the facial nerve was performed between 1988 and 2005. The patients were divided into 3 groups based on the procedure used: interposition of the partial graft on the injured area of the nerve (group 1; 12 patients); keeping the preserved part and performing tubulization (group 2; 8 patients); and dividing the parts of the injured nerve (proximal and distal) and placing a total graft of the sural nerve (group 3; 22 patients). Fracture of the temporal bone was the most frequent cause of the lesion in all groups, followed by iatrogenic causes (p lesion of the facial nerve is still questionable. Among these 42 patients, the best results were those from the total graft of the facial nerve.

  18. Generalizations of the Nash Equilibrium Theorem in the KKM Theory

    Directory of Open Access Journals (Sweden)

    Sehie Park

    2010-01-01

    Full Text Available The partial KKM principle for an abstract convex space is an abstract form of the classical KKM theorem. In this paper, we derive generalized forms of the Ky Fan minimax inequality, the von Neumann-Sion minimax theorem, the von Neumann-Fan intersection theorem, the Fan-type analytic alternative, and the Nash equilibrium theorem for abstract convex spaces satisfying the partial KKM principle. These results are compared with previously known cases for G-convex spaces. Consequently, our results unify and generalize most of previously known particular cases of the same nature. Finally, we add some detailed historical remarks on related topics.

  19. Microwave measurements of water vapor partial pressure at high temperatures

    International Nuclear Information System (INIS)

    Latorre, V.R.

    1991-01-01

    One of the desired parameters in the Yucca Mountain Project is the capillary pressure of the rock comprising the repository. This parameter is related to the partial pressure of water vapor in the air when in equilibrium with the rock mass. Although there are a number of devices that will measure the relative humidity (directly related to the water vapor partial pressure), they generally will fail at temperatures on the order of 150C. Since thee author has observed borehole temperatures considerably in excess of this value in G-Tunnel at the Nevada Test Site (NTS), a different scheme is required to obtain the desired partial pressure data at higher temperatures. This chapter presents a microwave technique that has been developed to measure water vapor partial pressure in boreholes at temperatures up to 250C. The heart of the system is a microwave coaxial resonator whose resonant frequency is inversely proportional to the square root of the real part of the complex dielectric constant of the medium (air) filling the resonator. The real part of the dielectric constant of air is approximately equal to the square of the refractive index which, in turn, is proportional to the partial pressure of the water vapor in the air. Thus, a microwave resonant cavity can be used to measure changes in the relative humidity or partial pressure of water vapor in the air. Since this type of device is constructed of metal, it is able to withstand very high temperatures. The actual limitation is the temperature limit of the dielectric material in the cable connecting the resonator to its driving and monitoring equipment-an automatic network analyzer in our case. In the following sections, the theory of operation, design, construction, calibration and installation of the microwave diagnostics system is presented. The results and conclusions are also presented, along with suggestions for future work

  20. General practitioners′ attitudes toward reporting and learning from adverse events: results from a survey

    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...

  1. Regularization in Matrix Relevance Learning

    NARCIS (Netherlands)

    Schneider, Petra; Bunte, Kerstin; Stiekema, Han; Hammer, Barbara; Villmann, Thomas; Biehl, Michael

    A In this paper, we present a regularization technique to extend recently proposed matrix learning schemes in learning vector quantization (LVQ). These learning algorithms extend the concept of adaptive distance measures in LVQ to the use of relevance matrices. In general, metric learning can

  2. Automata learning algorithms and processes for providing more complete systems requirements specification by scenario generation, CSP-based syntax-oriented model construction, and R2D2C system requirements transformation

    Science.gov (United States)

    Hinchey, Michael G. (Inventor); Margaria, Tiziana (Inventor); Rash, James L. (Inventor); Rouff, Christopher A. (Inventor); Steffen, Bernard (Inventor)

    2010-01-01

    Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.

  3. General method and exact solutions to a generalized variable-coefficient two-dimensional KdV equation

    International Nuclear Information System (INIS)

    Chen, Yong; Shanghai Jiao-Tong Univ., Shangai; Chinese Academy of sciences, Beijing

    2005-01-01

    A general method to uniformly construct exact solutions in terms of special function of nonlinear partial differential equations is presented by means of a more general ansatz and symbolic computation. Making use of the general method, we can successfully obtain the solutions found by the method proposed by Fan (J. Phys. A., 36 (2003) 7009) and find other new and more general solutions, which include polynomial solutions, exponential solutions, rational solutions, triangular periodic wave solution, soliton solutions, soliton-like solutions and Jacobi, Weierstrass doubly periodic wave solutions. A general variable-coefficient two-dimensional KdV equation is chosen to illustrate the method. As a result, some new exact soliton-like solutions are obtained. planets. The numerical results are given in tables. The results are discussed in the conclusion

  4. Scaffolded Semi-Flipped General Chemistry Designed to Support Rural Students' Learning

    Science.gov (United States)

    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…

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

    Science.gov (United States)

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

    2008-03-01

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

  6. Complexity of universality and related problems for partially ordered NFAs

    Czech Academy of Sciences Publication Activity Database

    Krötzsch, M.; Masopust, Tomáš; Thomazo, M.

    2017-01-01

    Roč. 255, č. 1 (2017), s. 177-192 ISSN 0890-5401 Institutional support: RVO:67985840 Keywords : nondeterministic automata * partial order * universal ity Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 1.050, year: 2016 http://www.sciencedirect.com/science/article/pii/S0890540117300998?via%3Dihub

  7. 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....

  8. Computing generalized Langevin equations and generalized Fokker-Planck equations.

    Science.gov (United States)

    Darve, Eric; Solomon, Jose; Kia, Amirali

    2009-07-07

    The Mori-Zwanzig formalism is an effective tool to derive differential equations describing the evolution of a small number of resolved variables. In this paper we present its application to the derivation of generalized Langevin equations and generalized non-Markovian Fokker-Planck equations. We show how long time scales rates and metastable basins can be extracted from these equations. Numerical algorithms are proposed to discretize these equations. An important aspect is the numerical solution of the orthogonal dynamics equation which is a partial differential equation in a high dimensional space. We propose efficient numerical methods to solve this orthogonal dynamics equation. In addition, we present a projection formalism of the Mori-Zwanzig type that is applicable to discrete maps. Numerical applications are presented from the field of Hamiltonian systems.

  9. New Solutions of Three Nonlinear Space- and Time-Fractional Partial Differential Equations in Mathematical Physics

    International Nuclear Information System (INIS)

    Yao Ruo-Xia; Wang Wei; Chen Ting-Hua

    2014-01-01

    Motivated by the widely used ansätz method and starting from the modified Riemann—Liouville derivative together with a fractional complex transformation that can be utilized to transform nonlinear fractional partial differential equations to nonlinear ordinary differential equations, new types of exact traveling wave solutions to three important nonlinear space- and time-fractional partial differential equations are obtained simultaneously in terms of solutions of a Riccati equation. The results are new and first reported in this paper. (general)

  10. Beginning partial differential equations

    CERN Document Server

    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

  11. Applicability of the theory of planned behavior in explaining the general practitioners eLearning use in continuing medical education.

    Science.gov (United States)

    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.

  12. Cognitive-Linguistic Functioning and Learning to Read in Preschoolers

    Science.gov (United States)

    Goldstein, David M.

    1976-01-01

    The major results partially confirm the hypothesis of a reciprocal relationship between the experience of learning to read and the cognitive-linguistic skills which undergo development between the ages of five and seven. (RC)

  13. ERC Workshop on Geometric Partial Differential Equations

    CERN Document Server

    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.

  14. A Bayesian concept learning approach to crowdsourcing

    DEFF Research Database (Denmark)

    Viappiani, P.; Zilles, S.; Hamilton, H.J.

    2011-01-01

    techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing......We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...

  15. Deep Learning Policy Quantization

    NARCIS (Netherlands)

    van de Wolfshaar, Jos; Wiering, Marco; Schomaker, Lambertus

    2018-01-01

    We introduce a novel type of actor-critic approach for deep reinforcement learning which is based on learning vector quantization. We replace the softmax operator of the policy with a more general and more flexible operator that is similar to the robust soft learning vector quantization algorithm.

  16. Daily Reservoir Inflow Forecasting using Deep Learning with Downscaled Multi-General Circulation Models (GCMs) Platform

    Science.gov (United States)

    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.

  17. Effect of Topography on Learning Military Tactics - Integration of Generalized Intelligent Framework for Tutoring (GIFT) and Augmented REality Sandtable (ARES)

    Science.gov (United States)

    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

  18. Partial breaking of N = 1, D = 10 supersymmetry

    International Nuclear Information System (INIS)

    Bellucci, S.

    1999-01-01

    In this paper is described the spontaneous partial breaking of N =1, D =10 supersymmetry to N = (1, 0), d = 6 and its dimensionally-reduced versions in the framework of nonlinear realizations. The basic Goldstone superfield is N = (1, 0), d = 6 hyper multiplet superfield satisfying a nonlinear generalization of the standard hyper multiplet constraint. It is here interpreted the generalized constraint as the manifestly world volume supersymmetric form of equations of motion of the type 1 super 5-brane in D 10. The related issues here addressed are a possible existence of brane extension of off-shell hyper multiplet actions, the possibility to utilize vector N = (1, 0), d =6 supermultiplet as the Goldstone one, and the description of 1/4 breaking of N =1, D = 11 supersymmetry

  19. Hyperbolic partial differential equations

    CERN Document Server

    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

  20. Partial differential equations mathematical techniques for engineers

    CERN Document Server

    Epstein, Marcelo

    2017-01-01

    This monograph presents a graduate-level treatment of partial differential equations (PDEs) for engineers. The book begins with a review of the geometrical interpretation of systems of ODEs, the appearance of PDEs in engineering is motivated by the general form of balance laws in continuum physics. Four chapters are devoted to a detailed treatment of the single first-order PDE, including shock waves and genuinely non-linear models, with applications to traffic design and gas dynamics. The rest of the book deals with second-order equations. In the treatment of hyperbolic equations, geometric arguments are used whenever possible and the analogy with discrete vibrating systems is emphasized. The diffusion and potential equations afford the opportunity of dealing with questions of uniqueness and continuous dependence on the data, the Fourier integral, generalized functions (distributions), Duhamel's principle, Green's functions and Dirichlet and Neumann problems. The target audience primarily comprises graduate s...