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Sample records for learning conditional random

  1. Document page structure learning for fixed-layout e-books using conditional random fields

    Science.gov (United States)

    Tao, Xin; Tang, Zhi; Xu, Canhui

    2013-12-01

    In this paper, a model is proposed to learn logical structure of fixed-layout document pages by combining support vector machine (SVM) and conditional random fields (CRF). Features related to each logical label and their dependencies are extracted from various original Portable Document Format (PDF) attributes. Both local evidence and contextual dependencies are integrated in the proposed model so as to achieve better logical labeling performance. With the merits of SVM as local discriminative classifier and CRF modeling contextual correlations of adjacent fragments, it is capable of resolving the ambiguities of semantic labels. The experimental results show that CRF based models with both tree and chain graph structures outperform the SVM model with an increase of macro-averaged F1 by about 10%.

  2. Learning a constrained conditional random field for enhanced segmentation of fallen trees in ALS point clouds

    Science.gov (United States)

    Polewski, Przemyslaw; Yao, Wei; Heurich, Marco; Krzystek, Peter; Stilla, Uwe

    2018-06-01

    In this study, we present a method for improving the quality of automatic single fallen tree stem segmentation in ALS data by applying a specialized constrained conditional random field (CRF). The entire processing pipeline is composed of two steps. First, short stem segments of equal length are detected and a subset of them is selected for further processing, while in the second step the chosen segments are merged to form entire trees. The first step is accomplished using the specialized CRF defined on the space of segment labelings, capable of finding segment candidates which are easier to merge subsequently. To achieve this, the CRF considers not only the features of every candidate individually, but incorporates pairwise spatial interactions between adjacent segments into the model. In particular, pairwise interactions include a collinearity/angular deviation probability which is learned from training data as well as the ratio of spatial overlap, whereas unary potentials encode a learned probabilistic model of the laser point distribution around each segment. Each of these components enters the CRF energy with its own balance factor. To process previously unseen data, we first calculate the subset of segments for merging on a grid of balance factors by minimizing the CRF energy. Then, we perform the merging and rank the balance configurations according to the quality of their resulting merged trees, obtained from a learned tree appearance model. The final result is derived from the top-ranked configuration. We tested our approach on 5 plots from the Bavarian Forest National Park using reference data acquired in a field inventory. Compared to our previous segment selection method without pairwise interactions, an increase in detection correctness and completeness of up to 7 and 9 percentage points, respectively, was observed.

  3. Variational Infinite Hidden Conditional Random Fields

    NARCIS (Netherlands)

    Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja; Ghahramani, Zoubin

    2015-01-01

    Hidden conditional random fields (HCRFs) are discriminative latent variable models which have been shown to successfully learn the hidden structure of a given classification problem. An Infinite hidden conditional random field is a hidden conditional random field with a countably infinite number of

  4. Comparison of three problem-based learning conditions (real patients, digital and paper) with lecture-based learning in a dermatology course: a prospective randomized study from China.

    Science.gov (United States)

    Li, Jie; Li, Qing Ling; Li, Ji; Chen, Ming Liang; Xie, Hong Fu; Li, Ya Ping; Chen, Xiang

    2013-01-01

    The precise effect and the quality of different cases used in dermatology problem-based learning (PBL) curricula are yet unclear. To prospectively compare the impact of real patients, digital, paper PBL (PPBL) and traditional lecture-based learning (LBL) on academic results and student perceptions. A total of 120 students were randomly allocated into either real-patients PBL (RPBL) group studied via real-patient cases, digital PBL (DPBL) group studied via digital-form cases, PPBL group studied via paper-form cases, or conventional group who received didactic lectures. Academic results were assessed through review of written examination, objective structured clinical examination and student performance scores. A five-point Likert scale questionnaire was used to evaluate student perceptions. Compared to those receiving lectures only, all PBL participants had better results for written examination, clinical examination and overall performance. Students in RPBL group exhibited better overall performance than those in the other two PBL groups. Real-patient cases were more effective in helping develop students' self-directed learning skills, improving their confidence in future patient encounters and encouraging them to learn more about the discussed condition, compared to digital and paper cases. Both real patient and digital triggers are helpful in improving students' clinical problem-handling skills. However, real patients provide greater benefits to students.

  5. Learning conditional Gaussian networks

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard

    This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

  6. Efficient robust conditional random fields.

    Science.gov (United States)

    Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

    2015-10-01

    Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

  7. Efficient Training Methods for Conditional Random Fields

    National Research Council Canada - National Science Library

    Sutton, Charles A

    2008-01-01

    .... In this thesis, I investigate efficient training methods for conditional random fields with complex graphical structure, focusing on local methods which avoid propagating information globally along the graph...

  8. Learning strategies during fear conditioning

    OpenAIRE

    Carpenter, Russ E.; Summers, Cliff H.

    2009-01-01

    This paper describes a model of fear learning, in which subjects have an option of behavioral responses to impending social defeat. The model generates two types of learning: social avoidance and classical conditioning, dependent upon 1) escape from or 2) social subordination to an aggressor. We hypothesized that social stress provides the impetus as well as the necessary information to stimulate dichotomous goal-oriented learning. Specialized tanks were constructed to subject rainbow trout t...

  9. Infinite conditional random fields for human behavior analysis

    NARCIS (Netherlands)

    Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

    Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF

  10. Uniqueness conditions for finitely dependent random fields

    International Nuclear Information System (INIS)

    Dobrushin, R.L.; Pecherski, E.A.

    1981-01-01

    The authors consider a random field for which uniqueness and some additional conditions guaranteeing that the correlations between the variables of the field decrease rapidly enough with the distance between the values of the parameter occur. The main result of the paper states that in such a case uniqueness is true for any other field with transition probabilities sufficiently close to those of the original field. Then they apply this result to some ''degenerate'' classes of random fields for which one can check this condition of correlation to decay, and thus obtain some new conditions of uniqueness. (Auth.)

  11. Boundary conditions in random sequential adsorption

    Science.gov (United States)

    Cieśla, Michał; Ziff, Robert M.

    2018-04-01

    The influence of different boundary conditions on the density of random packings of disks is studied. Packings are generated using the random sequential adsorption algorithm with three different types of boundary conditions: periodic, open, and wall. It is found that the finite size effects are smallest for periodic boundary conditions, as expected. On the other hand, in the case of open and wall boundaries it is possible to introduce an effective packing size and a constant correction term to significantly improve the packing densities.

  12. Deep recurrent conditional random field network for protein secondary prediction

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Sønderby, Søren Kaae; Sønderby, Casper Kaae

    2017-01-01

    Deep learning has become the state-of-the-art method for predicting protein secondary structure from only its amino acid residues and sequence profile. Building upon these results, we propose to combine a bi-directional recurrent neural network (biRNN) with a conditional random field (CRF), which...... of the labels for all time-steps. We condition the CRF on the output of biRNN, which learns a distributed representation based on the entire sequence. The biRNN-CRF is therefore close to ideally suited for the secondary structure task because a high degree of cross-talk between neighboring elements can...

  13. Solution to random differential equations with boundary conditions

    Directory of Open Access Journals (Sweden)

    Fairouz Tchier

    2017-04-01

    Full Text Available We study a family of random differential equations with boundary conditions. Using a random fixed point theorem, we prove an existence theorem that yields a unique random solution.

  14. Evolving Random Forest for Preference Learning

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through a combination of an evolutionary method and random forest. Grammatical evolution is used to describe the structure of the trees in the Random Forest (RF) and to handle the process of evolution. Evolved random forests ...... obtained for predicting pairwise self-reports of users for the three emotional states engagement, frustration and challenge show very promising results that are comparable and in some cases superior to those obtained from state-of-the-art methods....

  15. Randomized Prediction Games for Adversarial Machine Learning.

    Science.gov (United States)

    Rota Bulo, Samuel; Biggio, Battista; Pillai, Ignazio; Pelillo, Marcello; Roli, Fabio

    In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time, e.g., malware code is typically obfuscated using random strings or byte sequences to hide known exploits. Interestingly, randomization has also been proposed to improve security of learning algorithms against evasion attacks, as it results in hiding information about the classifier to the attacker. Recent work has proposed game-theoretical formulations to learn secure classifiers, by simulating different evasion attacks and modifying the classification function accordingly. However, both the classification function and the simulated data manipulations have been modeled in a deterministic manner, without accounting for any form of randomization. In this paper, we overcome this limitation by proposing a randomized prediction game, namely, a noncooperative game-theoretic formulation in which the classifier and the attacker make randomized strategy selections according to some probability distribution defined over the respective strategy set. We show that our approach allows one to improve the tradeoff between attack detection and false alarms with respect to the state-of-the-art secure classifiers, even against attacks that are different from those hypothesized during design, on application examples including handwritten digit recognition, spam, and malware detection.In spam and malware detection, attackers exploit randomization to obfuscate malicious data and increase their chances of evading detection at test time, e.g., malware code is typically obfuscated using random strings or byte sequences to hide known exploits. Interestingly, randomization has also been proposed to improve security of learning algorithms against evasion attacks, as it results in hiding information about the classifier to the attacker. Recent work has proposed game-theoretical formulations to learn secure classifiers, by simulating different

  16. Learning Random Numbers: A Matlab Anomaly

    Czech Academy of Sciences Publication Activity Database

    Savický, Petr; Robnik-Šikonja, M.

    2008-01-01

    Roč. 22, č. 3 (2008), s. 254-265 ISSN 0883-9514 R&D Projects: GA AV ČR 1ET100300517 Institutional research plan: CEZ:AV0Z10300504 Keywords : random number s * machine learning * classification * attribute evaluation * regression Subject RIV: BA - General Mathematics Impact factor: 0.795, year: 2008

  17. Learning Conditions for Non-Formal and Informal Workplace Learning

    Science.gov (United States)

    Kyndt, Eva; Dochy, Filip; Nijs, Hanne

    2009-01-01

    Purpose: The purpose of this research paper is to investigate the presence of learning conditions for non-formal and informal workplace learning in relation to the characteristics of the employee and the organisation he or she works for. Design/methodology/approach: The questionnaire developed by Clauwaert and Van Bree on learning conditions was…

  18. Changing Conditions for Networked Learning?

    DEFF Research Database (Denmark)

    Ryberg, Thomas

    2011-01-01

    in describing the novel pedagogical potentials of these new technologies and practices (e.g. in debates around virtual learning environments versus personal learning environment). Likewise, I shall briefly discuss the notions of ‘digital natives’ or ‘the net generation’ from a critical perspective...... of social technologies. I argue that we are seeing the emergence of new architectures and scales of participation, collaboration and networking e.g. through interesting formations of learning networks at different levels of scale, for different purposes and often bridging boundaries such as formal...

  19. Conditional discrimination learning: A critique and amplification

    OpenAIRE

    Schrier, Allan M.; Thompson, Claudia R.

    1980-01-01

    Carter and Werner recently reviewed the literature on conditional discrimination learning by pigeons, which consists of studies of matching-to-sample and oddity-from-sample. They also discussed three models of such learning: the “multiple-rule” model (learning of stimulus-specific relations), the “configuration” model, and the “single-rule” model (concept learning). Although their treatment of the multiple-rule model, which seems most applicable to the pigeon data, is generally excellent, the...

  20. Efficient Training Methods for Conditional Random Fields

    Science.gov (United States)

    2008-02-01

    Learning (ICML), 2007. [63] Bruce G. Lindsay. Composite likelihood methods. Contemporary Mathematics, pages 221–239, 1988. 189 [64] Yan Liu, Jaime ...Conference on Machine Learning (ICML), pages 737–744, 2005. [107] Erik F. Tjong Kim Sang and Sabine Buchholz. Introduction to the CoNLL-2000 shared task

  1. Randomized Algorithms for Scalable Machine Learning

    OpenAIRE

    Kleiner, Ariel Jacob

    2012-01-01

    Many existing procedures in machine learning and statistics are computationally intractable in the setting of large-scale data. As a result, the advent of rapidly increasing dataset sizes, which should be a boon yielding improved statistical performance, instead severely blunts the usefulness of a variety of existing inferential methods. In this work, we use randomness to ameliorate this lack of scalability by reducing complex, computationally difficult inferential problems to larger sets o...

  2. Maximum Likelihood Learning of Conditional MTE Distributions

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael

    2009-01-01

    We describe a procedure for inducing conditional densities within the mixtures of truncated exponentials (MTE) framework. We analyse possible conditional MTE specifications and propose a model selection scheme, based on the BIC score, for partitioning the domain of the conditioning variables....... Finally, experimental results demonstrate the applicability of the learning procedure as well as the expressive power of the conditional MTE distribution....

  3. Dissociable Learning Processes Underlie Human Pain Conditioning.

    Science.gov (United States)

    Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben

    2016-01-11

    Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection [1], escape and avoidance learning [2], and endogenous analgesia [3]. Although a central role for the amygdala is well established [4], both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum [5]. It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  4. Infinite hidden conditional random fields for human behavior analysis.

    Science.gov (United States)

    Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

    2013-01-01

    Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.

  5. Learning of couplings for random asymmetric kinetic Ising models revisited: random correlation matrices and learning curves

    International Nuclear Information System (INIS)

    Bachschmid-Romano, Ludovica; Opper, Manfred

    2015-01-01

    We study analytically the performance of a recently proposed algorithm for learning the couplings of a random asymmetric kinetic Ising model from finite length trajectories of the spin dynamics. Our analysis shows the importance of the nontrivial equal time correlations between spins induced by the dynamics for the speed of learning. These correlations become more important as the spin’s stochasticity is decreased. We also analyse the deviation of the estimation error (paper)

  6. Conditions for Productive Learning in Network Learning Environments

    DEFF Research Database (Denmark)

    Ponti, M.; Dirckinck-Holmfeld, Lone; Lindström, B.

    2004-01-01

    are designed without a deep understanding of the pedagogical, communicative and collaborative conditions embedded in networked learning. Despite the existence of good theoretical views pointing to a social understanding of learning, rather than a traditional individualistic and information processing approach......The Kaleidoscope1 Jointly Executed Integrating Research Project (JEIRP) on Conditions for Productive Networked Learning Environments is developing and elaborating conceptual understandings of Computer Supported Collaborative Learning (CSCL) emphasizing the use of cross-cultural comparative......: Pedagogical design and the dialectics of the digital artefacts, the concept of collaboration, ethics/trust, identity and the role of scaffolding of networked learning environments.   The JEIRP is motivated by the fact that many networked learning environments in various European educational settings...

  7. Some common random fixed point theorems for contractive type conditions in cone random metric spaces

    Directory of Open Access Journals (Sweden)

    Saluja Gurucharan S.

    2016-08-01

    Full Text Available In this paper, we establish some common random fixed point theorems for contractive type conditions in the setting of cone random metric spaces. Our results unify, extend and generalize many known results from the current existing literature.

  8. Conditions of Practice in Perceptual Skill Learning

    Science.gov (United States)

    Memmert, D.; Hagemann, N.; Althoetmar, R.; Geppert, S.; Seiler, D.

    2009-01-01

    This study uses three experiments with different kinds of training conditions to investigate the "easy-to-hard" principle, context interference conditions, and feedback effects for learning anticipatory skills in badminton. Experiment 1 (N = 60) showed that a training program that gradually increases the difficulty level has no advantage over the…

  9. Spatial Learning: Conditions and Basic Effects

    Directory of Open Access Journals (Sweden)

    Victoria D. Chamizo

    2002-01-01

    Full Text Available A growing body of evidence suggests that the spatial and the temporal domains seem to share the same or similar conditions, basic effects, and mechanisms. The blocking, unblocking and overshadowing experiments (and also those of latent inhibition and perceptual learning reviewed by Prados and Redhead in this issue show that to exclude associative learning as a basic mechanism responsible for spatial learning is quite inappropriate. All these results, especially those obtained with strictly spatial tasks, seem inconsistent with O’Keefe and Nadel’s account of true spatial learning or locale learning. Their theory claims that this kind of learning is fundamentally different and develops with total independence from other ways of learning (like classical and instrumental conditioning -taxon learning. In fact, the results reviewed can be explained appealing on to a sophisticated guidance system, like for example the one proposed by Leonard and McNaughton (1990; see also McNaughton and cols, 1996. Such a system would allow that an animal generates new space information: given the distance and address from of A to B and from A to C, being able to infer the distance and the address from B to C, even when C is invisible from B (see Chapuis and Varlet, 1987 -the contribution by McLaren in this issue constitutes a good example of a sophisticated guidance system.

  10. Geomagnetic storm under laboratory conditions: randomized experiment

    Science.gov (United States)

    Gurfinkel, Yu I.; Vasin, A. L.; Pishchalnikov, R. Yu; Sarimov, R. M.; Sasonko, M. L.; Matveeva, T. A.

    2017-10-01

    The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

  11. Geomagnetic storm under laboratory conditions: randomized experiment.

    Science.gov (United States)

    Gurfinkel, Yu I; Vasin, A L; Pishchalnikov, R Yu; Sarimov, R M; Sasonko, M L; Matveeva, T A

    2018-04-01

    The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

  12. Some psycholinguistic conditions for second language learning

    Directory of Open Access Journals (Sweden)

    Bernard Spolsky

    2013-02-01

    Full Text Available The author discusses some psycho linguistic conditions for second language learning based on a preference rr ode! in linguistics. The outcome of second language learning depends on a number of conditions. Second language learning takes place in a social context, and social conditions determine a learner's attitudes. These attitudes are twofold in nature, namely those towards the community speaking the target language and those towards the learning situation. The two kinds of attitudes lead to motivation. The social context also provides opportunities for language learning and can be divided into formal and informal situations. There are also individual conditions of the learner. The author is concerned with the exploration of several specific psycholinguistic factors, as well as the kinds of rules which they contribute to the theory. Die skrywer bespreek enkele psigolinguistiese voorwaardes vir die aanleer van 'n tweede taal, gebaseer op 'n voorkeurmodel in die l!nguistiek. Die aanleer van 'n tweede taal geskied bin ne 'n sosiale konteks, en sosiale omstandighede bepaal 'n leerder se houding. Hierdie houding kan bestaan ten opsigte van die gemeenskap wat die teikentaal praat, sowel as ten opsigte van die leersituasie. Motivering word bepaal deur hierdie tweeledige houding. Die sosiale konteks bepaal ook geleenthede vir die aanleer van 'n taal en kan verdeel word in forme le en informele situasies. Verder is daar die individuele omstandighede van elke leerder. Die skrywer hou horn besig met 'n verkenning van spesifieke psigolinguistiese faktore, sowel as die soort reels wat hydra tot die teorie.

  13. Conditioning and learning in relation to disease.

    Science.gov (United States)

    Ban, T A; Guy, W

    1985-12-01

    Of the two generally recognized processes through which learning occurs--imprinting and conditioning--only the latter with its two paradigms, classical and operant, has both practical and heuristic implications for disease. From the classical conditioning experiments of Pavlov's laboratory over 100 years ago to the later work in operant conditioning by Skinner and others in the past four decades has evolved much of the basis of modern learning theory and its applications to disease in the form of behavior therapy. Variants of behavior therapy have been employed in the treatment of wide variety of medical and psychiatric illnesses. Recent developments in the study of brain function and biochemistry have led to renewed interest in the conditioning paradigm and its value as tool in these areas of research.

  14. Learning context conditions for BDI plan selection

    NARCIS (Netherlands)

    Singh, D.; Sardina, S.; Padgham, L.; Airiau, S.; van der Hoek, W.; Kaminka, G.A.; Lespérance, Y.; Luck, M.; Sen, S.

    2010-01-01

    An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-called context conditions of plans, on which the whole model relies for plan selection, are restricted to be boolean formulas

  15. Operant Conditioning and Learning: Examples, Sources, Technology.

    Science.gov (United States)

    Pedrini, Bonnie C.; Pedrini, D. T.

    The purpose of this paper is to relate psychology to teaching generally, and to relate behavior shaping to curriculum, specifically. Focusing on operant conditioning and learning, many studies are cited which illustrate some of the work being done toward effectively shaping or modifying student behavior whether in terms of subject matter or…

  16. Creating conditions for cooperative learning: Basic elements

    Directory of Open Access Journals (Sweden)

    Ševkušić-Mandić Slavica G.

    2003-01-01

    Full Text Available Although a large number of research evidence speak out in favor of cooperative learning, its effectiveness in teaching does not depend only on teacher’s and students’ enthusiasm and willingness to work in such a manner. Creating cooperative situations in learning demands a serious preparation and engagement on the part of teacher who is structuring various aspects of work in the classroom. Although there exist a large number of models and techniques of cooperative learning, which vary in the way in which students work together, in the structure of learning tasks as well as in the degree to which cooperative efforts of students are coupled with competition among groups, some elements should be present in the structure of conditions irrespective of the type of group work in question. Potential effects of cooperation are not likely to emerge unless teachers apply five basic elements of cooperative structure: 1. structuring of the learning task and students’ positive interdependence, 2. individual responsibility, 3. upgrading of "face to face" interaction, 4. training of students’ social skills, and 5. evaluation of group processes. The paper discusses various strategies for establishing the mentioned elements and concrete examples for teaching practice are provided, which should be of assistance to teachers for as much successful cooperative learning application as possible in work with children.

  17. Conditional Monte Carlo randomization tests for regression models.

    Science.gov (United States)

    Parhat, Parwen; Rosenberger, William F; Diao, Guoqing

    2014-08-15

    We discuss the computation of randomization tests for clinical trials of two treatments when the primary outcome is based on a regression model. We begin by revisiting the seminal paper of Gail, Tan, and Piantadosi (1988), and then describe a method based on Monte Carlo generation of randomization sequences. The tests based on this Monte Carlo procedure are design based, in that they incorporate the particular randomization procedure used. We discuss permuted block designs, complete randomization, and biased coin designs. We also use a new technique by Plamadeala and Rosenberger (2012) for simple computation of conditional randomization tests. Like Gail, Tan, and Piantadosi, we focus on residuals from generalized linear models and martingale residuals from survival models. Such techniques do not apply to longitudinal data analysis, and we introduce a method for computation of randomization tests based on the predicted rate of change from a generalized linear mixed model when outcomes are longitudinal. We show, by simulation, that these randomization tests preserve the size and power well under model misspecification. Copyright © 2014 John Wiley & Sons, Ltd.

  18. Research on machine learning framework based on random forest algorithm

    Science.gov (United States)

    Ren, Qiong; Cheng, Hui; Han, Hai

    2017-03-01

    With the continuous development of machine learning, industry and academia have released a lot of machine learning frameworks based on distributed computing platform, and have been widely used. However, the existing framework of machine learning is limited by the limitations of machine learning algorithm itself, such as the choice of parameters and the interference of noises, the high using threshold and so on. This paper introduces the research background of machine learning framework, and combined with the commonly used random forest algorithm in machine learning classification algorithm, puts forward the research objectives and content, proposes an improved adaptive random forest algorithm (referred to as ARF), and on the basis of ARF, designs and implements the machine learning framework.

  19. Drosophila Courtship Conditioning As a Measure of Learning and Memory.

    Science.gov (United States)

    Koemans, Tom S; Oppitz, Cornelia; Donders, Rogier A T; van Bokhoven, Hans; Schenck, Annette; Keleman, Krystyna; Kramer, Jamie M

    2017-06-05

    Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model organisms such as the fruit fly, Drosophila melanogaster. Drosophila is useful for understanding the basic neurobiology underlying cognitive deficits resulting from mutations in genes associated with human cognitive disorders, such as intellectual disability (ID) and autism. This work describes a methodology for testing learning and memory using a classic paradigm in Drosophila known as courtship conditioning. Male flies court females using a distinct pattern of easily recognizable behaviors. Premated females are not receptive to mating and will reject the male's copulation attempts. In response to this rejection, male flies reduce their courtship behavior. This learned reduction in courtship behavior is measured over time, serving as an indicator of learning and memory. The basic numerical output of this assay is the courtship index (CI), which is defined as the percentage of time that a male spends courting during a 10 min interval. The learning index (LI) is the relative reduction of CI in flies that have been exposed to a premated female compared to naïve flies with no previous social encounters. For the statistical comparison of LIs between genotypes, a randomization test with bootstrapping is used. To illustrate how the assay can be used to address the role of a gene relating to learning and memory, the pan-neuronal knockdown of Dihydroxyacetone phosphate acyltransferase (Dhap-at) was characterized here. The human ortholog of Dhap-at, glyceronephosphate O-acyltransferase (GNPT), is involved in rhizomelic chondrodysplasia punctata type 2, an autosomal-recessive syndrome characterized by severe ID. Using the courtship conditioning assay, it was determined that Dhap-at is required for long-term memory, but not for short-term memory. This result serves as a basis for further investigation of the underlying molecular

  20. Informal Workplace Learning among Nurses: Organisational Learning Conditions and Personal Characteristics That Predict Learning Outcomes

    Science.gov (United States)

    Kyndt, Eva; Vermeire, Eva; Cabus, Shana

    2016-01-01

    Purpose: This paper aims to examine which organisational learning conditions and individual characteristics predict the learning outcomes nurses achieve through informal learning activities. There is specific relevance for the nursing profession because of the rapidly changing healthcare systems. Design/Methodology/Approach: In total, 203 nurses…

  1. Algorithmic learning in a random world

    CERN Document Server

    Vovk, Vladimir; Shafer, Glenn

    2005-01-01

    A new scientific monograph developing significant new algorithmic foundations in machine learning theory. Researchers and postgraduates in CS, statistics, and A.I. will find the book an authoritative and formal presentation of some of the most promising theoretical developments in machine learning.

  2. Circular random motion in diatom gliding under isotropic conditions

    International Nuclear Information System (INIS)

    Gutiérrez-Medina, Braulio; Maldonado, Ana Iris Peña; Guerra, Andrés Jiménez; Rubio, Yadiralia Covarrubias; Meza, Jessica Viridiana García

    2014-01-01

    How cells migrate has been investigated primarily for the case of trajectories composed by joined straight segments. In contrast, little is known when cellular motion follows intrinsically curved paths. Here, we use time-lapse optical microscopy and automated trajectory tracking to investigate how individual cells of the diatom Nitzschia communis glide across surfaces under isotropic environmental conditions. We find a distinct kind of random motion, where trajectories are formed by circular arcs traveled at constant speed, alternated with random stoppages, direction reversals and changes in the orientation of the arcs. Analysis of experimental and computer-simulated trajectories show that the circular random motion of diatom gliding is not optimized for long-distance travel but rather for recurrent coverage of limited surface area. These results suggest that one main biological role for this type of diatom motility is to efficiently build the foundation of algal biofilms. (paper)

  3. Joint Conditional Random Field Filter for Multi-Object Tracking

    Directory of Open Access Journals (Sweden)

    Luo Ronghua

    2011-03-01

    Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

  4. Generative Learning Objects Instantiated with Random Numbers Based Expressions

    Directory of Open Access Journals (Sweden)

    Ciprian Bogdan Chirila

    2015-12-01

    Full Text Available The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise betweenstatic, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We find that random numbers based automatic initialization learning objects increases content diversity, interactivity thus enabling learners’ engagement. The resulted learning object model is at a limited level of complexity related to special e-learning software, intuitive and capable of increasing learners’ interactivity, engagement and motivation through dynamic content. The approach was applied successfully on several computer programing disciplines.

  5. Learning Conditions, Members' Motivation and Satisfaction: A Multilevel Analysis

    Science.gov (United States)

    Dimas, Isabel Dórdio; Rebelo, Teresa; Lourenço, Paulo Renato

    2015-01-01

    Purpose: The purpose of this paper was to contribute to the clarification of the conditions under which teams can be successful, especially those related to team learning. To attain this goal, in the present study, the mediating role played by team members' motivation on the relationship between team learning conditions (shared learning beliefs…

  6. Monte Carlo learning/biasing experiment with intelligent random numbers

    International Nuclear Information System (INIS)

    Booth, T.E.

    1985-01-01

    A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs

  7. Random accumulated damage evaluation under multiaxial fatigue loading conditions

    Directory of Open Access Journals (Sweden)

    V. Anes

    2015-07-01

    Full Text Available Multiaxial fatigue is a very important physical phenomenon to take into account in several mechanical components; its study is of utmost importance to avoid unexpected failure of equipment, vehicles or structures. Among several fatigue characterization tools, a correct definition of a damage parameter and a load cycle counting method under multiaxial loading conditions show to be crucial to estimate multiaxial fatigue life. In this paper, the SSF equivalent stress and the virtual cycle counting method are presented and discussed, regarding their physical foundations and their capability to characterize multiaxial fatigue damage under complex loading blocks. Moreover, it is presented their applicability to evaluate random fatigue damage.

  8. Comparing Young and Elderly Serial Reaction Time Task Performance on Repeated and Random Conditions

    Directory of Open Access Journals (Sweden)

    Fatemeh Ehsani

    2012-07-01

    Full Text Available Objectives: Acquisition motor skill training in elderly is at great importance. The main purpose of this study was to compare young and elderly performance in serial reaction time task on different repeated and random conditions. Methods & Materials: A serial reaction time task by using software was applied for studying motor learning in 30 young and 30 elderly. Each group divided randomly implicitly and explicitly into subgroups. A task 4 squares with different colors appeared on the monitor and subjects were asked to press its defined key immediately after observing it. Subjects practiced 8 motor blocks (4 repeated blocks, then 2 random blocks and 2 repeated blocks. Block time that was dependent variable measured and Independent-samples t- test with repeated ANOVA measures were used in this test. Results: young groups performed both repeated and random sequences significantly faster than elderly (P0.05. Explicit older subgroup performed 7,8 blocks slower than 6 block with a significant difference (P<0.05. Conclusion: Young adults discriminate high level performance than elderly in both repeated and random practice. Elderly performed random practice better than repeated practice.

  9. Smooth conditional distribution function and quantiles under random censorship.

    Science.gov (United States)

    Leconte, Eve; Poiraud-Casanova, Sandrine; Thomas-Agnan, Christine

    2002-09-01

    We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).

  10. Biomimetic propulsion under random heaving conditions, using active pitch control

    Science.gov (United States)

    Politis, Gerasimos; Politis, Konstantinos

    2014-05-01

    Marine mammals travel long distances by utilizing and transforming wave energy to thrust through proper control of their caudal fin. On the other hand, manmade ships traveling in a wavy sea store large amounts of wave energy in the form of kinetic energy for heaving, pitching, rolling and other ship motions. A natural way to extract this energy and transform it to useful propulsive thrust is by using a biomimetic wing. The aim of this paper is to show how an actively pitched biomimetic wing could achieve this goal when it performs a random heaving motion. More specifically, we consider a biomimetic wing traveling with a given translational velocity in an infinitely extended fluid and performing a random heaving motion with a given energy spectrum which corresponds to a given sea state. A formula is invented by which the instantaneous pitch angle of the wing is determined using the heaving data of the current and past time steps. Simulations are then performed for a biomimetic wing at different heave energy spectra, using an indirect Source-Doublet 3-D-BEM, together with a time stepping algorithm capable to track the random motion of the wing. A nonlinear pressure type Kutta condition is applied at the trailing edge of the wing. With a mollifier-based filtering technique, the 3-D unsteady rollup pattern created by the random motion of the wing is calculated without any simplifying assumptions regarding its geometry. Calculated unsteady forces, moments and useful power, show that the proposed active pitch control always results in thrust producing motions, with significant propulsive power production and considerable beneficial stabilizing action to ship motions. Calculation of the power required to set the pitch angle prove it to be a very small percentage of the useful power and thus making the practical application of the device very tractable.

  11. Random ensemble learning for EEG classification.

    Science.gov (United States)

    Hosseini, Mohammad-Parsa; Pompili, Dario; Elisevich, Kost; Soltanian-Zadeh, Hamid

    2018-01-01

    Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features. The feature space is divided into subspaces via random selection and multichannel support vector machines (SVMs) are used to classify these subspaces. The result of each classifier is then combined by majority voting to establish the final output. In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem. To evaluate the solution, a benchmark ECoG of eight patients with temporal and extratemporal epilepsy was implemented in a distributed computing framework as a multitier cloud-computing architecture. Using leave-one-out cross-validation, the accuracy, sensitivity, specificity, and both false positive and false negative ratios of the proposed method were found to be 0.97, 0.98, 0.96, 0.04, and 0.02, respectively. Application of the solution to cases under investigation with ECoG has also been effected to demonstrate its utility. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Mediating Parent Learning to Promote Social Communication for Toddlers with Autism: Effects from a Randomized Controlled Trial

    Science.gov (United States)

    Schertz, Hannah H.; Odom, Samuel L.; Baggett, Kathleen M.; Sideris, John H.

    2018-01-01

    A randomized controlled trial was conducted to evaluate effects of the Joint Attention Mediated Learning (JAML) intervention. Toddlers with autism spectrum disorders (ASD) aged 16-30 months (n = 144) were randomized to intervention and community control conditions. Parents, who participated in 32 weekly home-based sessions, followed a mediated…

  13. Experienced teachers' informal workplace learning and perceptions of workplace conditions

    NARCIS (Netherlands)

    Hoekstra, A.; Korthagen, F.; Brekelmans, M.; Beijaard, D.; Imants, J.

    2009-01-01

    Purpose: The purpose of this paper is to explore in detail how teachers' perceptions of workplace conditions for learning are related to their informal workplace learning activities and learning outcomes. Design/methodology/approach: From a sample of 32 teachers, a purposeful sampling technique of

  14. Typed Linear Chain Conditional Random Fields and Their Application to Intrusion Detection

    Science.gov (United States)

    Elfers, Carsten; Horstmann, Mirko; Sohr, Karsten; Herzog, Otthein

    Intrusion detection in computer networks faces the problem of a large number of both false alarms and unrecognized attacks. To improve the precision of detection, various machine learning techniques have been proposed. However, one critical issue is that the amount of reference data that contains serious intrusions is very sparse. In this paper we present an inference process with linear chain conditional random fields that aims to solve this problem by using domain knowledge about the alerts of different intrusion sensors represented in an ontology.

  15. Imaging learning and memory: classical conditioning.

    Science.gov (United States)

    Schreurs, B G; Alkon, D L

    2001-12-15

    The search for the biological basis of learning and memory has, until recently, been constrained by the limits of technology to classic anatomic and electrophysiologic studies. With the advent of functional imaging, we have begun to delve into what, for many, was a "black box." We review several different types of imaging experiments, including steady state animal experiments that image the functional labeling of fixed tissues, and dynamic human studies based on functional imaging of the intact brain during learning. The data suggest that learning and memory involve a surprising conservation of mechanisms and the integrated networking of a number of structures and processes. Copyright 2001 Wiley-Liss, Inc.

  16. Conditional Random Fields for Morphological Analysis of Wireless ECG Signals

    Science.gov (United States)

    Natarajan, Annamalai; Gaiser, Edward; Angarita, Gustavo; Malison, Robert; Ganesan, Deepak; Marlin, Benjamin

    2015-01-01

    Thanks to advances in mobile sensing technologies, it has recently become practical to deploy wireless electrocardiograph sensors for continuous recording of ECG signals. This capability has diverse applications in the study of human health and behavior, but to realize its full potential, new computational tools are required to effectively deal with the uncertainty that results from the noisy and highly non-stationary signals collected using these devices. In this work, we present a novel approach to the problem of extracting the morphological structure of ECG signals based on the use of dynamically structured conditional random field (CRF) models. We apply this framework to the problem of extracting morphological structure from wireless ECG sensor data collected in a lab-based study of habituated cocaine users. Our results show that the proposed CRF-based approach significantly out-performs independent prediction models using the same features, as well as a widely cited open source toolkit. PMID:26726321

  17. The Effects of Hypertext Gloss on Comprehension and Vocabulary Retention under Incidental and Intentional Learning Conditions

    Science.gov (United States)

    Zandieh, Zeinab; Jafarigohar, Manoochehr

    2012-01-01

    The present study investigated comprehension, immediate and delayed vocabulary retention under incidental and intentional learning conditions via computer mediated hypertext gloss. One hundred and eighty four (N = 184) intermediate students of English as a foreign language at an English school participated in the study. They were randomly assigned…

  18. Rapid learning dynamics in individual honeybees during classical conditioning

    Directory of Open Access Journals (Sweden)

    Evren ePamir

    2014-09-01

    Full Text Available Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3,298 animals. We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response in learners, and the high stability of the conditioned response during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla-Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.

  19. Active Learning Not Associated with Student Learning in a Random Sample of College Biology Courses

    Science.gov (United States)

    Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.

    2011-01-01

    Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373

  20. Conditional Random Fields for Pattern Recognition Applied to Structured Data

    Directory of Open Access Journals (Sweden)

    Tom Burr

    2015-07-01

    Full Text Available Pattern recognition uses measurements from an input domain, X, to predict their labels from an output domain, Y. Image analysis is one setting where one might want to infer whether a pixel patch contains an object that is “manmade” (such as a building or “natural” (such as a tree. Suppose the label for a pixel patch is “manmade”; if the label for a nearby pixel patch is then more likely to be “manmade” there is structure in the output domain that can be exploited to improve pattern recognition performance. Modeling P(X is difficult because features between parts of the model are often correlated. Therefore, conditional random fields (CRFs model structured data using the conditional distribution P(Y|X = x, without specifying a model for P(X, and are well suited for applications with dependent features. This paper has two parts. First, we overview CRFs and their application to pattern recognition in structured problems. Our primary examples are image analysis applications in which there is dependence among samples (pixel patches in the output domain. Second, we identify research topics and present numerical examples.

  1. Rapid learning dynamics in individual honeybees during classical conditioning.

    Science.gov (United States)

    Pamir, Evren; Szyszka, Paul; Scheiner, Ricarda; Nawrot, Martin P

    2014-01-01

    Associative learning in insects has been studied extensively by a multitude of classical conditioning protocols. However, so far little emphasis has been put on the dynamics of learning in individuals. The honeybee is a well-established animal model for learning and memory. We here studied associative learning as expressed in individual behavior based on a large collection of data on olfactory classical conditioning (25 datasets, 3298 animals). We show that the group-averaged learning curve and memory retention score confound three attributes of individual learning: the ability or inability to learn a given task, the generally fast acquisition of a conditioned response (CR) in learners, and the high stability of the CR during consecutive training and memory retention trials. We reassessed the prevailing view that more training results in better memory performance and found that 24 h memory retention can be indistinguishable after single-trial and multiple-trial conditioning in individuals. We explain how inter-individual differences in learning can be accommodated within the Rescorla-Wagner theory of associative learning. In both data-analysis and modeling we demonstrate how the conflict between population-level and single-animal perspectives on learning and memory can be disentangled.

  2. Bearing Fault Classification Based on Conditional Random Field

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2013-01-01

    Full Text Available Condition monitoring of rolling element bearing is paramount for predicting the lifetime and performing effective maintenance of the mechanical equipment. To overcome the drawbacks of the hidden Markov model (HMM and improve the diagnosis accuracy, conditional random field (CRF model based classifier is proposed. In this model, the feature vectors sequences and the fault categories are linked by an undirected graphical model in which their relationship is represented by a global conditional probability distribution. In comparison with the HMM, the main advantage of the CRF model is that it can depict the temporal dynamic information between the observation sequences and state sequences without assuming the independence of the input feature vectors. Therefore, the interrelationship between the adjacent observation vectors can also be depicted and integrated into the model, which makes the classifier more robust and accurate than the HMM. To evaluate the effectiveness of the proposed method, four kinds of bearing vibration signals which correspond to normal, inner race pit, outer race pit and roller pit respectively are collected from the test rig. And the CRF and HMM models are built respectively to perform fault classification by taking the sub band energy features of wavelet packet decomposition (WPD as the observation sequences. Moreover, K-fold cross validation method is adopted to improve the evaluation accuracy of the classifier. The analysis and comparison under different fold times show that the accuracy rate of classification using the CRF model is higher than the HMM. This method brings some new lights on the accurate classification of the bearing faults.

  3. Conditioning Factors of an Organizational Learning Culture

    Science.gov (United States)

    Rebelo, Teresa Manuela; Gomes, Adelino Duarte

    2011-01-01

    Purpose: The aim of this study is to assess the relationship between some variables (organizational structure, organizational dimension and age, human resource characteristics, the external environment, strategy and quality) and organizational learning culture and evaluate the way they interact with this kind of culture.…

  4. Sex differences in learning processes of classical and operant conditioning.

    Science.gov (United States)

    Dalla, Christina; Shors, Tracey J

    2009-05-25

    Males and females learn and remember differently at different times in their lives. These differences occur in most species, from invertebrates to humans. We review here sex differences as they occur in laboratory rodent species. We focus on classical and operant conditioning paradigms, including classical eyeblink conditioning, fear-conditioning, active avoidance and conditioned taste aversion. Sex differences have been reported during acquisition, retention and extinction in most of these paradigms. In general, females perform better than males in the classical eyeblink conditioning, in fear-potentiated startle and in most operant conditioning tasks, such as the active avoidance test. However, in the classical fear-conditioning paradigm, in certain lever-pressing paradigms and in the conditioned taste aversion, males outperform females or are more resistant to extinction. Most sex differences in conditioning are dependent on organizational effects of gonadal hormones during early development of the brain, in addition to modulation by activational effects during puberty and adulthood. Critically, sex differences in performance account for some of the reported effects on learning and these are discussed throughout the review. Because so many mental disorders are more prevalent in one sex than the other, it is important to consider sex differences in learning when applying animal models of learning for these disorders. Finally, we discuss how sex differences in learning continue to alter the brain throughout the lifespan. Thus, sex differences in learning are not only mediated by sex differences in the brain, but also contribute to them.

  5. Random synaptic feedback weights support error backpropagation for deep learning

    Science.gov (United States)

    Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

    2016-01-01

    The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning. PMID:27824044

  6. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa

    The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....

  7. The conditions that promote fear learning: prediction error and Pavlovian fear conditioning.

    Science.gov (United States)

    Li, Susan Shi Yuan; McNally, Gavan P

    2014-02-01

    A key insight of associative learning theory is that learning depends on the actions of prediction error: a discrepancy between the actual and expected outcomes of a conditioning trial. When positive, such error causes increments in associative strength and, when negative, such error causes decrements in associative strength. Prediction error can act directly on fear learning by determining the effectiveness of the aversive unconditioned stimulus or indirectly by determining the effectiveness, or associability, of the conditioned stimulus. Evidence from a variety of experimental preparations in human and non-human animals suggest that discrete neural circuits code for these actions of prediction error during fear learning. Here we review the circuits and brain regions contributing to the neural coding of prediction error during fear learning and highlight areas of research (safety learning, extinction, and reconsolidation) that may profit from this approach to understanding learning. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  8. Game-based learning as a vehicle to teach first aid content: a randomized experiment.

    Science.gov (United States)

    Charlier, Nathalie; De Fraine, Bieke

    2013-07-01

    Knowledge of first aid (FA), which constitutes lifesaving treatments for injuries or illnesses, is important for every individual. In this study, we have set up a group-randomized controlled trial to assess the effectiveness of a board game for learning FA. Four class groups (120 students) were randomly assigned to 2 conditions, a board game or a traditional lecture method (control condition). The effect of the learning environment on students' achievement was examined through a paper-and-pencil test of FA knowledge. Two months after the intervention, the participants took a retention test and completed a questionnaire assessing enjoyment, interest, and motivation. An analysis of pre- and post-test knowledge scores showed that both conditions produced significant increases in knowledge. The lecture was significantly more effective in increasing knowledge, as compared to the board game. Participants indicated that they liked the game condition more than their fellow participants in the traditional lecture condition. These results suggest that traditional lectures are more effective in increasing student knowledge, whereas educational games are more effective for student enjoyment. From this case study we recommend alteration or a combination of these teaching methods to make learning both effective and enjoyable. © 2013, American School Health Association.

  9. Contingency learning in human fear conditioning involves the ventral striatum.

    Science.gov (United States)

    Klucken, Tim; Tabbert, Katharina; Schweckendiek, Jan; Merz, Christian Josef; Kagerer, Sabine; Vaitl, Dieter; Stark, Rudolf

    2009-11-01

    The ability to detect and learn contingencies between fearful stimuli and their predictive cues is an important capacity to cope with the environment. Contingency awareness refers to the ability to verbalize the relationships between conditioned and unconditioned stimuli. Although there is a heated debate about the influence of contingency awareness on conditioned fear responses, neural correlates behind the formation process of contingency awareness have gained only little attention in human fear conditioning. Recent animal studies indicate that the ventral striatum (VS) could be involved in this process, but in human studies the VS is mostly associated with positive emotions. To examine this question, we reanalyzed four recently published classical fear conditioning studies (n = 117) with respect to the VS at three distinct levels of contingency awareness: subjects, who did not learn the contingencies (unaware), subjects, who learned the contingencies during the experiment (learned aware) and subjects, who were informed about the contingencies in advance (instructed aware). The results showed significantly increased activations in the left and right VS in learned aware compared to unaware subjects. Interestingly, this activation pattern was only found in learned but not in instructed aware subjects. We assume that the VS is not involved when contingency awareness does not develop during conditioning or when contingency awareness is unambiguously induced already prior to conditioning. VS involvement seems to be important for the transition from a contingency unaware to a contingency aware state. Implications for fear conditioning models as well as for the contingency awareness debate are discussed.

  10. Leveraging Random Number Generation for Mastery of Learning in Teaching Quantitative Research Courses via an E-Learning Method

    Science.gov (United States)

    Boonsathorn, Wasita; Charoen, Danuvasin; Dryver, Arthur L.

    2014-01-01

    E-Learning brings access to a powerful but often overlooked teaching tool: random number generation. Using random number generation, a practically infinite number of quantitative problem-solution sets can be created. In addition, within the e-learning context, in the spirit of the mastery of learning, it is possible to assign online quantitative…

  11. Conditioning Factors for Group Management in Blended Learning Scenarios

    NARCIS (Netherlands)

    Pérez-Sanagustín, Mar; Hernández-Leo, Davinia; Blat, Josep

    2009-01-01

    Pérez-Sanagustín, M., Hernández-Leo D., & Blat, J. (accepted). Conditioning Factors for Group Management in Blended Learning Scenarios. The 9th IEEE International Conference on Advanced Learning Technologies. July, 14-18, 2009, Riga, Latvia.

  12. Learning Mixtures of Polynomials of Conditional Densities from Data

    DEFF Research Database (Denmark)

    L. López-Cruz, Pedro; Nielsen, Thomas Dyhre; Bielza, Concha

    2013-01-01

    Mixtures of polynomials (MoPs) are a non-parametric density estimation technique for hybrid Bayesian networks with continuous and discrete variables. We propose two methods for learning MoP ap- proximations of conditional densities from data. Both approaches are based on learning MoP approximatio...

  13. Wordless intervention for epilepsy in learning disabilities (WIELD): study protocol for a randomized controlled feasibility trial.

    Science.gov (United States)

    Durand, Marie-Anne; Gates, Bob; Parkes, Georgina; Zia, Asif; Friedli, Karin; Barton, Garry; Ring, Howard; Oostendorp, Linda; Wellsted, David

    2014-11-20

    Epilepsy is the most common neurological problem that affects people with learning disabilities. The high seizure frequency, resistance to treatments, associated skills deficit and co-morbidities make the management of epilepsy particularly challenging for people with learning disabilities. The Books Beyond Words booklet for epilepsy uses images to help people with learning disabilities manage their condition and improve quality of life. Our aim is to conduct a randomized controlled feasibility trial exploring key methodological, design and acceptability issues, in order to subsequently undertake a large-scale randomized controlled trial of the Books Beyond Words booklet for epilepsy. We will use a two-arm, single-centre randomized controlled feasibility design, over a 20-month period, across five epilepsy clinics in Hertfordshire, United Kingdom. We will recruit 40 eligible adults with learning disabilities and a confirmed diagnosis of epilepsy and will randomize them to use either the Books Beyond Words booklet plus usual care (intervention group) or to receive routine information and services (control group). We will collect quantitative data about the number of eligible participants, number of recruited participants, demographic data, discontinuation rates, variability of the primary outcome measure (quality of life: Epilepsy and Learning Disabilities Quality of Life scale), seizure severity, seizure control, intervention's patterns of use, use of other epilepsy-related information, resource use and the EQ-5D-5L health questionnaire. We will also gather qualitative data about the feasibility and acceptability of the study procedures and the Books Beyond Words booklet. Ethical approval for this study was granted on 28 April 2014, by the Wales Research Ethics Committee 5. Recruitment began on 1 July 2014. The outcomes of this feasibility study will be used to inform the design and methodology of a definitive study, adequately powered to determine the impact of

  14. Collaborative learning in condition based maintenance

    NARCIS (Netherlands)

    Koochaki, J.; Ao, SI; Gelman, L; Hukins, DWL; Hunter, A; Korsunsky, AM

    2009-01-01

    In recent years, the importance of reliable and consistent production equipments has increased. As a result, companies are shifting their maintenance policy from preventive maintenance towards Condition Based Maintenance (CBM). Despite the growing trend in this area and success stories of CBM

  15. Analysis of random number generators in abnormal usage conditions

    International Nuclear Information System (INIS)

    Soucarros, M.

    2012-01-01

    Random numbers have been used through the ages for games of chance, more recently for secret codes and today they are necessary to the execution of computer programs. Random number generators have now evolved from simple dices to electronic circuits and algorithms. Accordingly, the ability to distinguish between random and non-random numbers has become more difficult. Furthermore, whereas in the past dices were loaded in order to increase winning chances, it is now possible to influence the outcome of random number generators. In consequence, this subject is still very much an issue and has recently made the headlines. Indeed, there was talks about the PS3 game console which generates constant random numbers and redundant distribution of secret keys on the internet. This thesis presents a study of several generators as well as different means to perturb them. It shows the inherent defects of their conceptions and possible consequences of their failure when they are embedded inside security components. Moreover, this work highlights problems yet to be solved concerning the testing of random numbers and the post-processing eliminating bias in these numbers distribution. (author) [fr

  16. Women's Learning in Contract Work: Practicing Contradictions in Boundaryless Conditions

    Science.gov (United States)

    Fenwick, Tara

    2008-01-01

    The general rise in contractors, particularly among knowledge workers negotiating "boundaryless" employment conditions, has generated interest in the nature and forms of contract work. This article explores the learning of contract workers as they negotiate these conditions, with a focus on women. Drawing from a qualitative study of…

  17. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model.

    Science.gov (United States)

    Liu, Dan; Liu, Xuejun; Wu, Yiguang

    2018-04-24

    This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  18. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model

    Directory of Open Access Journals (Sweden)

    Dan Liu

    2018-04-01

    Full Text Available This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN and a continuous pairwise Conditional Random Field (CRF model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  19. Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Hossein Bashashati

    2017-07-01

    Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.

  20. Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features

    Science.gov (United States)

    Bouboulis, Pantelis; Chouvardas, Symeon; Theodoridis, Sergios

    2018-04-01

    We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parameters as time iterations evolve. Besides complexity, this leads to an increased need of communication resources, in a distributed setting. In contrast, the proposed method approximates the solution as a fixed-size vector (of larger dimension than the input space) using Random Fourier Features. This paves the way to use standard linear combine-then-adapt techniques. To the best of our knowledge, this is the first time that a complete protocol for distributed online learning in RKHS is presented. Conditions for asymptotic convergence and boundness of the networkwise regret are also provided. The simulated tests illustrate the performance of the proposed scheme.

  1. Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields

    National Research Council Canada - National Science Library

    Mann, Gideon S; McCallum, Andrew

    2007-01-01

    Entropy regularization is a straightforward and successful method of semi-supervised learning that augments the traditional conditional likelihood objective function with an additional term that aims...

  2. Extremely Randomized Machine Learning Methods for Compound Activity Prediction

    Directory of Open Access Journals (Sweden)

    Wojciech M. Czarnecki

    2015-11-01

    Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  3. Reinforcement Learning Explains Conditional Cooperation and Its Moody Cousin.

    Directory of Open Access Journals (Sweden)

    Takahiro Ezaki

    2016-07-01

    Full Text Available Direct reciprocity, or repeated interaction, is a main mechanism to sustain cooperation under social dilemmas involving two individuals. For larger groups and networks, which are probably more relevant to understanding and engineering our society, experiments employing repeated multiplayer social dilemma games have suggested that humans often show conditional cooperation behavior and its moody variant. Mechanisms underlying these behaviors largely remain unclear. Here we provide a proximate account for this behavior by showing that individuals adopting a type of reinforcement learning, called aspiration learning, phenomenologically behave as conditional cooperator. By definition, individuals are satisfied if and only if the obtained payoff is larger than a fixed aspiration level. They reinforce actions that have resulted in satisfactory outcomes and anti-reinforce those yielding unsatisfactory outcomes. The results obtained in the present study are general in that they explain extant experimental results obtained for both so-called moody and non-moody conditional cooperation, prisoner's dilemma and public goods games, and well-mixed groups and networks. Different from the previous theory, individuals are assumed to have no access to information about what other individuals are doing such that they cannot explicitly use conditional cooperation rules. In this sense, myopic aspiration learning in which the unconditional propensity of cooperation is modulated in every discrete time step explains conditional behavior of humans. Aspiration learners showing (moody conditional cooperation obeyed a noisy GRIM-like strategy. This is different from the Pavlov, a reinforcement learning strategy promoting mutual cooperation in two-player situations.

  4. Comparing Exploration Strategies for Q-learning in Random Stochastic Mazes

    NARCIS (Netherlands)

    Tijsma, Arryon; Drugan, Madalina; Wiering, Marco

    2016-01-01

    Balancing the ratio between exploration and exploitation is an important problem in reinforcement learning. This paper evaluates four different exploration strategies combined with Q-learning using random stochastic mazes to investigate their performances. We will compare: UCB-1, softmax,

  5. On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

    Science.gov (United States)

    Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

    2017-11-01

    Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

  6. Cerebral cortex classification by conditional random fields applied to intraoperative thermal imaging

    Directory of Open Access Journals (Sweden)

    Hoffmann Nico

    2016-09-01

    Full Text Available Intraoperative thermal neuroimaging is a novel intraoperative imaging technique for the characterization of perfusion disorders, neural activity and other pathological changes of the brain. It bases on the correlation of (sub-cortical metabolism and perfusion with the emitted heat of the cortical surface. In order to minimize required computational resources and prevent unwanted artefacts in subsequent data analysis workflows foreground detection is a important preprocessing technique to differentiate pixels representing the cerebral cortex from background objects. We propose an efficient classification framework that integrates characteristic dynamic thermal behaviour into this classification task to include additional discriminative features. The first stage of our framework consists of learning this representation of characteristic thermal time-frequency behaviour. This representation models latent interconnections in the time-frequency domain that cover specific, yet a priori unknown, thermal properties of the cortex. In a second stage these features are then used to classify each pixel’s state with conditional random fields. We quantitatively evaluate several approaches to learning high-level features and their impact to the overall prediction accuracy. The introduction of high-level features leads to a significant accuracy improvement compared to a baseline classifier.

  7. Second-order conditioning and conditioned inhibition: influences of speed versus accuracy on human causal learning.

    Directory of Open Access Journals (Sweden)

    Jessica C Lee

    Full Text Available In human causal learning, excitatory and inhibitory learning effects can sometimes be found in the same paradigm by altering the learning conditions. This study aims to explore whether learning in the feature negative paradigm can be dissociated by emphasising speed over accuracy. In two causal learning experiments, participants were given a feature negative discrimination in which the outcome caused by one cue was prevented by the addition of another. Participants completed training trials either in a self-paced fashion with instructions emphasising accuracy, or under strict time constraints with instructions emphasising speed. Using summation tests in which the preventative cue was paired with another causal cue, participants in the accuracy groups correctly rated the preventative cue as if it reduced the probability of the outcome. However, participants in the speed groups rated the preventative cue as if it increased the probability of the outcome. In Experiment 1, both speed and accuracy groups later judged the same cue to be preventative in a reasoned inference task. Experiment 2 failed to find evidence of similar dissociations in retrospective revaluation (release from overshadowing vs. mediated extinction or learning about a redundant cue (blocking vs. augmentation. However in the same experiment, the tendency for the accuracy group to show conditioned inhibition and the speed group to show second-order conditioning was consistent even across sub-sets of the speed and accuracy groups with equivalent accuracy in training, suggesting that second-order conditioning is not merely a consequence of poorer acquisition. This dissociation mirrors the trade-off between second-order conditioning and conditioned inhibition observed in animal conditioning when training is extended.

  8. Influence of visual observational conditions on tongue motor learning

    DEFF Research Database (Denmark)

    Kothari, Mohit; Liu, Xuimei; Baad-Hansen, Lene

    2016-01-01

    To investigate the impact of visual observational conditions on performance during a standardized tongue-protrusion training (TPT) task and to evaluate subject-based reports of helpfulness, disturbance, pain, and fatigue due to the observational conditions on 0-10 numerical rating scales. Forty...... regarding the level of disturbance, pain or fatigue. Self-observation of tongue-training facilitated behavioral aspects of tongue motor learning compared with model-observation but not compared with control....

  9. Role of classical conditioning in learning gastrointestinal symptoms

    OpenAIRE

    Stockhorst, Ursula; Enck, Paul; Klosterhalfen, Sibylle

    2007-01-01

    Nausea and/or vomiting are aversive gastrointestinal (GI) symptoms. Nausea and vomiting manifest unconditionally after a nauseogenic experience. However, there is correlative, quasiexperimental and experimental evidence that nausea and vomiting can also be learned via classical (Pavlovian) conditioning and might occur in anticipation of the nauseogenic event. Classical conditioning of nausea can develop with chemotherapy in cancer patients. Initially, nausea and vomiting occur during and afte...

  10. Are environmental conditions in South African classrooms conducive for learning?

    CSIR Research Space (South Africa)

    Gibberd, Jeremy T

    2013-10-01

    Full Text Available not provide an environment that promotes productivity and comfort for particular summer conditions, and therefore is unlikely to be conducive for learning. The paper draws a number of conclusions from the study and makes recommendations for further research....

  11. Online Learning in Higher Education: Necessary and Sufficient Conditions

    Science.gov (United States)

    Lim, Cher Ping

    2005-01-01

    The spectacular development of information and communication technologies through the Internet has provided opportunities for students to explore the virtual world of information. In this article, the author discusses the necessary and sufficient conditions for successful online learning in educational institutions. The necessary conditions…

  12. Emotional eating and Pavlovian learning: evidence for conditioned appetitive responding to negative emotional states.

    Science.gov (United States)

    Bongers, Peggy; Jansen, Anita

    2017-02-01

    Appetitive learning has been demonstrated several times using neutral cues or contexts as a predictor of food intake and it has been shown that humans easily learn cued desires for foods. It has, however, never been studied whether internal cues are also capable of appetitive conditioning. In this study, we tested whether humans can learn cued eating desires to negative moods as conditioned stimuli (CS), thereby offering a potential explanation of emotional eating (EE). Female participants were randomly presented with 10 different stimuli eliciting either negative or neutral emotional states, with one of these states paired with eating chocolate. Expectancy to eat, desire to eat, salivation, and unpleasantness of experiencing negative emotions were assessed. After conditioning, participants were brought into a negative emotional state and were asked to choose between money and chocolate. Data showed differential conditioned responding on the expectancy and desire measures, but not on salivation. Specific conditioned effects were obtained for participants with a higher BMI (body mass index) on the choice task, and for participants high on EE on the unpleasantness ratings. These findings provide the first experimental evidence for the idea that negative emotions can act as conditioned stimuli, and might suggest that classical conditioning is involved in EE.

  13. Rare Events and Conditional Events on Random Strings

    Directory of Open Access Journals (Sweden)

    Mireille Régnier

    2004-12-01

    Full Text Available Some strings -the texts- are assumed to be randomly generated, according to a probability model that is either a Bernoulli model or a Markov model. A rare event is the over or under-representation of a word or a set of words. The aim of this paper is twofold. First, a single word is given. One studies the tail distribution of the number of its occurrences. Sharp large deviation estimates are derived. Second, one assumes that a given word is overrepresented. The distribution of a second word is studied; formulae for the expectation and the variance are derived. In both cases, the formulae are accurate and actually computable. These results have applications in computational biology, where a genome is viewed as a text.

  14. Conditioned random walks and interaction-driven condensation

    International Nuclear Information System (INIS)

    Szavits-Nossan, Juraj; Evans, Martin R; Majumdar, Satya N

    2017-01-01

    We consider a discrete-time continuous-space random walk under the constraints that the number of returns to the origin (local time) and the total area under the walk are fixed. We first compute the joint probability of an excursion having area a and returning to the origin for the first time after time τ . We then show how condensation occurs when the total area constraint is increased: an excursion containing a finite fraction of the area emerges. Finally we show how the phenomena generalises previously studied cases of condensation induced by several constraints and how it is related to interaction-driven condensation which allows us to explain the phenomenon in the framework of large deviation theory. (paper)

  15. Variability in Second Language Learning: The Roles of Individual Differences, Learning Conditions, and Linguistic Complexity

    Science.gov (United States)

    Tagarelli, Kaitlyn M.; Ruiz, Simón; Vega, José Luis Moreno; Rebuschat, Patrick

    2016-01-01

    Second language learning outcomes are highly variable, due to a variety of factors, including individual differences, exposure conditions, and linguistic complexity. However, exactly how these factors interact to influence language learning is unknown. This article examines the relationship between these three variables in language learners.…

  16. Classification of Phishing Email Using Random Forest Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Andronicus A. Akinyelu

    2014-01-01

    Full Text Available Phishing is one of the major challenges faced by the world of e-commerce today. Thanks to phishing attacks, billions of dollars have been lost by many companies and individuals. In 2012, an online report put the loss due to phishing attack at about $1.5 billion. This global impact of phishing attacks will continue to be on the increase and thus requires more efficient phishing detection techniques to curb the menace. This paper investigates and reports the use of random forest machine learning algorithm in classification of phishing attacks, with the major objective of developing an improved phishing email classifier with better prediction accuracy and fewer numbers of features. From a dataset consisting of 2000 phishing and ham emails, a set of prominent phishing email features (identified from the literature were extracted and used by the machine learning algorithm with a resulting classification accuracy of 99.7% and low false negative (FN and false positive (FP rates.

  17. De-identification of clinical notes via recurrent neural network and conditional random field.

    Science.gov (United States)

    Liu, Zengjian; Tang, Buzhou; Wang, Xiaolong; Chen, Qingcai

    2017-11-01

    De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsychiatric Genome-scale and RDOC Individualized Domains (N-GRID) clinical natural language processing (NLP) challenge contains a de-identification track in de-identifying electronic medical records (EMRs) (i.e., track 1). The challenge organizers provide 1000 annotated mental health records for this track, 600 out of which are used as a training set and 400 as a test set. We develop a hybrid system for the de-identification task on the training set. Firstly, four individual subsystems, that is, a subsystem based on bidirectional LSTM (long-short term memory, a variant of recurrent neural network), a subsystem-based on bidirectional LSTM with features, a subsystem based on conditional random field (CRF) and a rule-based subsystem, are used to identify PHI instances. Then, an ensemble learning-based classifiers is deployed to combine all PHI instances predicted by above three machine learning-based subsystems. Finally, the results of the ensemble learning-based classifier and the rule-based subsystem are merged together. Experiments conducted on the official test set show that our system achieves the highest micro F1-scores of 93.07%, 91.43% and 95.23% under the "token", "strict" and "binary token" criteria respectively, ranking first in the 2016 CEGS N-GRID NLP challenge. In addition, on the dataset of 2014 i2b2 NLP challenge, our system achieves the highest micro F1-scores of 96.98%, 95.11% and 98.28% under the "token", "strict" and "binary token" criteria respectively, outperforming other state-of-the-art systems. All these experiments prove the effectiveness of our proposed method. Copyright © 2017. Published by Elsevier Inc.

  18. Does peer learning or higher levels of e-learning improve learning abilities? A randomized controlled trial.

    Science.gov (United States)

    Worm, Bjarne Skjødt; Jensen, Kenneth

    2013-01-01

    Background and aims The fast development of e-learning and social forums demands us to update our understanding of e-learning and peer learning. We aimed to investigate if higher, pre-defined levels of e-learning or social interaction in web forums improved students' learning ability. Methods One hundred and twenty Danish medical students were randomized to six groups all with 20 students (eCases level 1, eCases level 2, eCases level 2+, eTextbook level 1, eTextbook level 2, and eTextbook level 2+). All students participated in a pre-test, Group 1 participated in an interactive case-based e-learning program, while Group 2 was presented with textbook material electronically. The 2+ groups were able to discuss the material between themselves in a web forum. The subject was head injury and associated treatment and observation guidelines in the emergency room. Following the e-learning, all students completed a post-test. Pre- and post-tests both consisted of 25 questions randomly chosen from a pool of 50 different questions. Results All students concluded the study with comparable pre-test results. Students at Level 2 (in both groups) improved statistically significant compared to students at level 1 (p>0.05). There was no statistically significant difference between level 2 and level 2+. However, level 2+ was associated with statistically significant greater student's satisfaction than the rest of the students (p>0.05). Conclusions This study applies a new way of comparing different types of e-learning using a pre-defined level division and the possibility of peer learning. Our findings show that higher levels of e-learning does in fact provide better results when compared with the same type of e-learning at lower levels. While social interaction in web forums increase student satisfaction, learning ability does not seem to change. Both findings are relevant when designing new e-learning materials.

  19. Does peer learning or higher levels of e-learning improve learning abilities? A randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Bjarne Skjødt Worm

    2013-11-01

    Full Text Available Background and aims : The fast development of e-learning and social forums demands us to update our understanding of e-learning and peer learning. We aimed to investigate if higher, pre-defined levels of e-learning or social interaction in web forums improved students’ learning ability. Methods : One hundred and twenty Danish medical students were randomized to six groups all with 20 students (eCases level 1, eCases level 2, eCases level 2+, eTextbook level 1, eTextbook level 2, and eTextbook level 2+. All students participated in a pre-test, Group 1 participated in an interactive case-based e-learning program, while Group 2 was presented with textbook material electronically. The 2+ groups were able to discuss the material between themselves in a web forum. The subject was head injury and associated treatment and observation guidelines in the emergency room. Following the e-learning, all students completed a post-test. Pre- and post-tests both consisted of 25 questions randomly chosen from a pool of 50 different questions. Results : All students concluded the study with comparable pre-test results. Students at Level 2 (in both groups improved statistically significant compared to students at level 1 (p>0.05. There was no statistically significant difference between level 2 and level 2+. However, level 2+ was associated with statistically significant greater student's satisfaction than the rest of the students (p>0.05. Conclusions : This study applies a new way of comparing different types of e-learning using a pre-defined level division and the possibility of peer learning. Our findings show that higher levels of e-learning does in fact provide better results when compared with the same type of e-learning at lower levels. While social interaction in web forums increase student satisfaction, learning ability does not seem to change. Both findings are relevant when designing new e-learning materials.

  20. Does peer learning or higher levels of e-learning improve learning abilities? A randomized controlled trial

    Science.gov (United States)

    Worm, Bjarne Skjødt; Jensen, Kenneth

    2013-01-01

    Background and aims The fast development of e-learning and social forums demands us to update our understanding of e-learning and peer learning. We aimed to investigate if higher, pre-defined levels of e-learning or social interaction in web forums improved students’ learning ability. Methods One hundred and twenty Danish medical students were randomized to six groups all with 20 students (eCases level 1, eCases level 2, eCases level 2+, eTextbook level 1, eTextbook level 2, and eTextbook level 2+). All students participated in a pre-test, Group 1 participated in an interactive case-based e-learning program, while Group 2 was presented with textbook material electronically. The 2+ groups were able to discuss the material between themselves in a web forum. The subject was head injury and associated treatment and observation guidelines in the emergency room. Following the e-learning, all students completed a post-test. Pre- and post-tests both consisted of 25 questions randomly chosen from a pool of 50 different questions. Results All students concluded the study with comparable pre-test results. Students at Level 2 (in both groups) improved statistically significant compared to students at level 1 (p>0.05). There was no statistically significant difference between level 2 and level 2+. However, level 2+ was associated with statistically significant greater student's satisfaction than the rest of the students (p>0.05). Conclusions This study applies a new way of comparing different types of e-learning using a pre-defined level division and the possibility of peer learning. Our findings show that higher levels of e-learning does in fact provide better results when compared with the same type of e-learning at lower levels. While social interaction in web forums increase student satisfaction, learning ability does not seem to change. Both findings are relevant when designing new e-learning materials. PMID:24229729

  1. Conditional High-Order Boltzmann Machines for Supervised Relation Learning.

    Science.gov (United States)

    Huang, Yan; Wang, Wei; Wang, Liang; Tan, Tieniu

    2017-09-01

    Relation learning is a fundamental problem in many vision tasks. Recently, high-order Boltzmann machine and its variants have shown their great potentials in learning various types of data relation in a range of tasks. But most of these models are learned in an unsupervised way, i.e., without using relation class labels, which are not very discriminative for some challenging tasks, e.g., face verification. In this paper, with the goal to perform supervised relation learning, we introduce relation class labels into conventional high-order multiplicative interactions with pairwise input samples, and propose a conditional high-order Boltzmann Machine (CHBM), which can learn to classify the data relation in a binary classification way. To be able to deal with more complex data relation, we develop two improved variants of CHBM: 1) latent CHBM, which jointly performs relation feature learning and classification, by using a set of latent variables to block the pathway from pairwise input samples to output relation labels and 2) gated CHBM, which untangles factors of variation in data relation, by exploiting a set of latent variables to multiplicatively gate the classification of CHBM. To reduce the large number of model parameters generated by the multiplicative interactions, we approximately factorize high-order parameter tensors into multiple matrices. Then, we develop efficient supervised learning algorithms, by first pretraining the models using joint likelihood to provide good parameter initialization, and then finetuning them using conditional likelihood to enhance the discriminant ability. We apply the proposed models to a series of tasks including invariant recognition, face verification, and action similarity labeling. Experimental results demonstrate that by exploiting supervised relation labels, our models can greatly improve the performance.

  2. Mitigating randomness of consumer preferences under certain conditional choices

    Science.gov (United States)

    Bothos, John M. A.; Thanos, Konstantinos-Georgios; Papadopoulou, Eirini; Daveas, Stelios; Thomopoulos, Stelios C. A.

    2017-05-01

    Agent-based crowd behaviour consists a significant field of research that has drawn a lot of attention in recent years. Agent-based crowd simulation techniques have been used excessively to forecast the behaviour of larger or smaller crowds in terms of certain given conditions influenced by specific cognition models and behavioural rules and norms, imposed from the beginning. Our research employs conditional event algebra, statistical methodology and agent-based crowd simulation techniques in developing a behavioural econometric model about the selection of certain economic behaviour by a consumer that faces a spectre of potential choices when moving and acting in a multiplex mall. More specifically we try to analyse the influence of demographic, economic, social and cultural factors on the economic behaviour of a certain individual and then we try to link its behaviour with the general behaviour of the crowds of consumers in multiplex malls using agent-based crowd simulation techniques. We then run our model using Generalized Least Squares and Maximum Likelihood methods to come up with the most probable forecast estimations, regarding the agent's behaviour. Our model is indicative about the formation of consumers' spectre of choices in multiplex malls under the condition of predefined preferences and can be used as a guide for further research in this area.

  3. Statistical learning of action: the role of conditional probability.

    Science.gov (United States)

    Meyer, Meredith; Baldwin, Dare

    2011-12-01

    Identification of distinct units within a continuous flow of human action is fundamental to action processing. Such segmentation may rest in part on statistical learning. In a series of four experiments, we examined what types of statistics people can use to segment a continuous stream involving many brief, goal-directed action elements. The results of Experiment 1 showed no evidence for sensitivity to conditional probability, whereas Experiment 2 displayed learning based on joint probability. In Experiment 3, we demonstrated that additional exposure to the input failed to engender sensitivity to conditional probability. However, the results of Experiment 4 showed that a subset of adults-namely, those more successful at identifying actions that had been seen more frequently than comparison sequences-were also successful at learning conditional-probability statistics. These experiments help to clarify the mechanisms subserving processing of intentional action, and they highlight important differences from, as well as similarities to, prior studies of statistical learning in other domains, including language.

  4. Segmentation of RGB-D indoor scenes by stacking random forests and conditional random fields

    DEFF Research Database (Denmark)

    Thøgersen, Mikkel; Guerrero, Sergio Escalera; Gonzàlez, Jordi

    2016-01-01

    Depth images have granted new possibilities to computer vision researchers across the field. A prominent task is scene understanding and segmentation on which the present work is concerned. In this paper, we present a procedure combining well known methods in a unified learning framework based on...

  5. Role of classical conditioning in learning gastrointestinal symptoms.

    Science.gov (United States)

    Stockhorst, Ursula; Enck, Paul; Klosterhalfen, Sibylle

    2007-07-07

    Nausea and/or vomiting are aversive gastrointestinal (GI) symptoms. Nausea and vomiting manifest unconditionally after a nauseogenic experience. However, there is correlative, quasiexperimental and experimental evidence that nausea and vomiting can also be learned via classical (Pavlovian) conditioning and might occur in anticipation of the nauseogenic event. Classical conditioning of nausea can develop with chemotherapy in cancer patients. Initially, nausea and vomiting occur during and after the administration of cytotoxic drugs (post-treatment nausea and vomiting) as unconditioned responses (UR). In addition, 20%-30% of cancer patients receiving chemotherapy report these side effects, despite antiemetic medication, when being re-exposed to the stimuli that usually signal the chemotherapy session and its drug infusion. These symptoms are called anticipatory nausea (AN) and/or anticipatory vomiting (ANV) and are explained by classical conditioning. Moreover, there is recent evidence for the assumption that post-chemotherapy nausea is at least partly influenced by learning. After summarizing the relevant assumptions of the conditioning model, revealing that a context can become a conditioned stimulus (CS), the present paper summarizes data that nausea and/or vomiting is acquired by classical conditioning and, consequently, may be alleviated by conditioning techniques. Our own research has focussed on two aspects and is emphasized here. First, a conditioned nausea model was established in healthy humans using body rotation as the nausea-inducing treatment. The validity of this motion-sickness model to examine conditioning mechanisms in the acquisition and alleviation of conditioned nausea and associated endocrine and immunological responses is summarized. Results from the rotation-induced motion sickness model showed that gender is an important moderator variable to be considered in further studies. This paper concludes with a review of the application of the

  6. A Machine LearningFramework to Forecast Wave Conditions

    Science.gov (United States)

    Zhang, Y.; James, S. C.; O'Donncha, F.

    2017-12-01

    Recently, significant effort has been undertaken to quantify and extract wave energy because it is renewable, environmental friendly, abundant, and often close to population centers. However, a major challenge is the ability to accurately and quickly predict energy production, especially across a 48-hour cycle. Accurate forecasting of wave conditions is a challenging undertaking that typically involves solving the spectral action-balance equation on a discretized grid with high spatial resolution. The nature of the computations typically demands high-performance computing infrastructure. Using a case-study site at Monterey Bay, California, a machine learning framework was trained to replicate numerically simulated wave conditions at a fraction of the typical computational cost. Specifically, the physics-based Simulating WAves Nearshore (SWAN) model, driven by measured wave conditions, nowcast ocean currents, and wind data, was used to generate training data for machine learning algorithms. The model was run between April 1st, 2013 and May 31st, 2017 generating forecasts at three-hour intervals yielding 11,078 distinct model outputs. SWAN-generated fields of 3,104 wave heights and a characteristic period could be replicated through simple matrix multiplications using the mapping matrices from machine learning algorithms. In fact, wave-height RMSEs from the machine learning algorithms (9 cm) were less than those for the SWAN model-verification exercise where those simulations were compared to buoy wave data within the model domain (>40 cm). The validated machine learning approach, which acts as an accurate surrogate for the SWAN model, can now be used to perform real-time forecasts of wave conditions for the next 48 hours using available forecasted boundary wave conditions, ocean currents, and winds. This solution has obvious applications to wave-energy generation as accurate wave conditions can be forecasted with over a three-order-of-magnitude reduction in

  7. Assessing the Effectiveness of Case-Based Collaborative Learning via Randomized Controlled Trial.

    Science.gov (United States)

    Krupat, Edward; Richards, Jeremy B; Sullivan, Amy M; Fleenor, Thomas J; Schwartzstein, Richard M

    2016-05-01

    Case-based collaborative learning (CBCL) is a novel small-group approach that borrows from team-based learning principles and incorporates elements of problem-based learning (PBL) and case-based learning. CBCL includes a preclass readiness assurance process and case-based in-class activities in which students respond to focused, open-ended questions individually, discuss their answers in groups of 4, and then reach consensus in larger groups of 16. This study introduces CBCL and assesses its effectiveness in one course at Harvard Medical School. In a 2013 randomized controlled trial, 64 medical and dental student volunteers were assigned randomly to one of four 8-person PBL tutorial groups (control; n = 32) or one of two 16-person CBCL tutorial groups (experimental condition; n = 32) as part of a required first-year physiology course. Outcomes for the PBL and CBCL groups were compared using final exam scores, student responses to a postcourse survey, and behavioral coding of portions of video-recorded class sessions. Overall, the course final exam scores for CBCL and PBL students were not significantly different. However, CBCL students whose mean exam performance in prior courses was below the participant median scored significantly higher than their PBL counterparts on the physiology course final exam. The most common adjectives students used to describe CBCL were "engaging," "fun," and "thought-provoking." Coding of observed behaviors indicated that individual affect was significantly higher in the CBCL groups than in the PBL groups. CBCL is a viable, engaging, active learning method. It may particularly benefit students with lower academic performance.

  8. Random neural Q-learning for obstacle avoidance of a mobile robot in unknown environments

    Directory of Open Access Journals (Sweden)

    Jing Yang

    2016-07-01

    Full Text Available The article presents a random neural Q-learning strategy for the obstacle avoidance problem of an autonomous mobile robot in unknown environments. In the proposed strategy, two independent modules, namely, avoidance without considering the target and goal-seeking without considering obstacles, are first trained using the proposed random neural Q-learning algorithm to obtain their best control policies. Then, the two trained modules are combined based on a switching function to realize the obstacle avoidance in unknown environments. For the proposed random neural Q-learning algorithm, a single-hidden layer feedforward network is used to approximate the Q-function to estimate the Q-value. The parameters of the single-hidden layer feedforward network are modified using the recently proposed neural algorithm named the online sequential version of extreme learning machine, where the parameters of the hidden nodes are assigned randomly and the sample data can come one by one. However, different from the original online sequential version of extreme learning machine algorithm, the initial output weights are estimated subjected to quadratic inequality constraint to improve the convergence speed. Finally, the simulation results demonstrate that the proposed random neural Q-learning strategy can successfully solve the obstacle avoidance problem. Also, the higher learning efficiency and better generalization ability are achieved by the proposed random neural Q-learning algorithm compared with the Q-learning based on the back-propagation method.

  9. Efficacy of the LiSN & Learn auditory training software: randomized blinded controlled study

    Directory of Open Access Journals (Sweden)

    Sharon Cameron

    2012-09-01

    Full Text Available Children with a spatial processing disorder (SPD require a more favorable signal-to-noise ratio in the classroom because they have difficulty perceiving sound source location cues. Previous research has shown that a novel training program - LiSN & Learn - employing spatialized sound, overcomes this deficit. Here we investigate whether improvements in spatial processing ability are specific to the LiSN & Learn training program. Participants were ten children (aged between 6;0 [years;months] and 9;9 with normal peripheral hearing who were diagnosed as having SPD using the Listening in Spatialized Noise - Sentences test (LiSN-S. In a blinded controlled study, the participants were randomly allocated to train with either the LiSN & Learn or another auditory training program - Earobics - for approximately 15 min per day for twelve weeks. There was a significant improvement post-training on the conditions of the LiSN-S that evaluate spatial processing ability for the LiSN & Learn group (P=0.03 to 0.0008, η 2=0.75 to 0.95, n=5, but not for the Earobics group (P=0.5 to 0.7, η 2=0.1 to 0.04, n=5. Results from questionnaires completed by the participants and their parents and teachers revealed improvements in real-world listening performance post-training were greater in the LiSN & Learn group than the Earobics group. LiSN & Learn training improved binaural processing ability in children with SPD, enhancing their ability to understand speech in noise. Exposure to non-spatialized auditory training does not produce similar outcomes, emphasizing the importance of deficit-specific remediation.

  10. Efficacy of the LiSN & Learn Auditory Training Software: randomized blinded controlled study

    Directory of Open Access Journals (Sweden)

    Sharon Cameron

    2012-01-01

    Full Text Available Background: Children with a spatial processing disorder (SPD require a more favorable signal-to-noise ratio in the classroom because they have difficulty perceiving sound source location cues. Previous research has shown that a novel training program - LiSN & Learn - employing spatialized sound, overcomes this deficit. Here we investigate whether improvements in spatial processing ability are specific to the LiSN & Learn training program. Materials and methods: Participants were ten children (aged between 6;0 [years;months] and 9;9 with normal peripheral hearing who were diagnosed as having SPD using the Listening in Spatialized Noise – Sentences Test (LISN-S. In a blinded controlled study, the participants were randomly allocated to train with either the LiSN & Learn or another auditory training program – Earobics - for approximately 15 minutes per day for twelve weeks. Results: There was a significant improvement post-training on the conditions of the LiSN-S that evaluate spatial processing ability for the LiSN & Learn group (p=0.03 to 0.0008, η2=0.75 to 0.95, n=5, but not for the Earobics group (p=0.5 to 0.7, η2=0.1 to 0.04, n=5. Results from questionnaires completed by the participants and their parents and teachers revealed improvements in real-world listening performance post-training were greater in the LiSN & Learn group than the Earobics group. Conclusions: LiSN & Learn training improved binaural processing ability in children with SPD, enhancing their ability to understand speech in noise. Exposure to non-spatialized auditory training does not produce similar outcomes, emphasizing the importance of deficit-specific remediation.

  11. Residential roof condition assessment system using deep learning

    Science.gov (United States)

    Wang, Fan; Kerekes, John P.; Xu, Zhuoyi; Wang, Yandong

    2018-01-01

    The emergence of high resolution (HR) and ultra high resolution (UHR) airborne remote sensing imagery is enabling humans to move beyond traditional land cover analysis applications to the detailed characterization of surface objects. A residential roof condition assessment method using techniques from deep learning is presented. The proposed method operates on individual roofs and divides the task into two stages: (1) roof segmentation, followed by (2) condition classification of the segmented roof regions. As the first step in this process, a self-tuning method is proposed to segment the images into small homogeneous areas. The segmentation is initialized with simple linear iterative clustering followed by deep learned feature extraction and region merging, with the optimal result selected by an unsupervised index, Q. After the segmentation, a pretrained residual network is fine-tuned on the augmented roof segments using a proposed k-pixel extension technique for classification. The effectiveness of the proposed algorithm was demonstrated on both HR and UHR imagery collected by EagleView over different study sites. The proposed algorithm has yielded promising results and has outperformed traditional machine learning methods using hand-crafted features.

  12. Mechanisms of radiation-induced conditioned taste aversion learning

    International Nuclear Information System (INIS)

    Rabin, B.M.; Hunt, W.A.

    1986-01-01

    The literature on taste aversion learning is reviewed and discussed, with particular emphasis on those studies that have used exposure to ionizing radiation as an unconditioned stimulus to produce a conditioned taste aversion. The primary aim of the review is to attempt to define the mechanisms that lead to the initiation of the taste aversion response following exposure to ionizing radiation. Studies using drug treatments to produce a taste aversion have been included to the extent that they are relevant to understanding the mechanisms by which exposure to ionizing radiation can affect the behavior of the organism. 141 references

  13. Exploring the Relation between Teachers' Perceptions of Workplace Conditions and Their Professional Learning Goals

    Science.gov (United States)

    Louws, Monika L.; Meirink, Jacobiene A.; van Veen, Klaas; van Driel, Jan H.

    2017-01-01

    Schools' structural workplace conditions (e.g. learning resources and professional development policies) and cultural workplace conditions (e.g. school leadership, teachers' collaborative culture) have been found to affect the way teachers learn. It is not so much the objective conditions that support or impede professional learning but the way…

  14. Game-Based Learning as a Vehicle to Teach First Aid Content: A Randomized Experiment

    Science.gov (United States)

    Charlier, Nathalie; De Fraine, Bieke

    2013-01-01

    Background: Knowledge of first aid (FA), which constitutes lifesaving treatments for injuries or illnesses, is important for every individual. In this study, we have set up a group-randomized controlled trial to assess the effectiveness of a board game for learning FA. Methods: Four class groups (120 students) were randomly assigned to 2…

  15. An improved segmentation-based HMM learning method for Condition-based Maintenance

    International Nuclear Information System (INIS)

    Liu, T; Lemeire, J; Cartella, F; Meganck, S

    2012-01-01

    In the domain of condition-based maintenance (CBM), persistence of machine states is a valid assumption. Based on this assumption, we present an improved Hidden Markov Model (HMM) learning algorithm for the assessment of equipment states. By a good estimation of initial parameters, more accurate learning can be achieved than by regular HMM learning methods which start with randomly chosen initial parameters. It is also better in avoiding getting trapped in local maxima. The data is segmented with a change-point analysis method which uses a combination of cumulative sum charts (CUSUM) and bootstrapping techniques. The method determines a confidence level that a state change happens. After the data is segmented, in order to label and combine the segments corresponding to the same states, a clustering technique is used based on a low-pass filter or root mean square (RMS) values of the features. The segments with their labelled hidden state are taken as 'evidence' to estimate the parameters of an HMM. Then, the estimated parameters are served as initial parameters for the traditional Baum-Welch (BW) learning algorithms, which are used to improve the parameters and train the model. Experiments on simulated and real data demonstrate that both performance and convergence speed is improved.

  16. Friend or Foe? Flipped Classroom for Undergraduate Electrocardiogram Learning: a Randomized Controlled Study.

    Science.gov (United States)

    Rui, Zeng; Lian-Rui, Xiang; Rong-Zheng, Yue; Jing, Zeng; Xue-Hong, Wan; Chuan, Zuo

    2017-03-07

    Interpreting an electrocardiogram (ECG) is not only one of the most important parts of clinical diagnostics but also one of the most difficult topics to teach and learn. In order to enable medical students to master ECG interpretation skills in a limited teaching period, the flipped teaching method has been recommended by previous research to improve teaching effect on undergraduate ECG learning. A randomized controlled trial for ECG learning was conducted, involving 181 junior-year medical undergraduates using a flipped classroom as an experimental intervention, compared with Lecture-Based Learning (LBL) as a control group. All participants took an examination one week after the intervention by analysing 20 ECGs from actual clinical cases and submitting their ECG reports. A self-administered questionnaire was also used to evaluate the students' attitudes, total learning time, and conditions under each teaching method. The students in the experimental group scored significantly higher than the control group (8.72 ± 1.01 vs 8.03 ± 1.01, t = 4.549, P = 0.000) on ECG interpretation. The vast majority of the students in the flipped classroom group held positive attitudes toward the flipped classroom method and also supported LBL. There was no significant difference (4.07 ± 0.96 vs 4.16 ± 0.89, Z = - 0.948, P = 0.343) between the groups. Prior to class, the students in the flipped class group devoted significantly more time than those in the control group (42.33 ± 22.19 vs 30.55 ± 10.15, t = 4.586, P = 0.000), whereas after class, the time spent by the two groups were not significantly different (56.50 ± 46.80 vs 54.62 ± 31.77, t = 0.317, P = 0.752). Flipped classroom teaching can improve medical students' interest in learning and their self-learning abilities. It is an effective teaching model that needs to be further studied and promoted.

  17. Conditional Random Fields versus Hidden Markov Models for activity recognition in temporal sensor data

    NARCIS (Netherlands)

    van Kasteren, T.L.M.; Noulas, A.K.; Kröse, B.J.A.; Smit, G.J.M.; Epema, D.H.J.; Lew, M.S.

    2008-01-01

    Conditional Random Fields are a discriminative probabilistic model which recently gained popularity in applications that require modeling nonindependent observation sequences. In this work, we present the basic advantages of this model over generative models and argue about its suitability in the

  18. Modeling Random Telegraph Noise Under Switched Bias Conditions Using Cyclostationary RTS Noise

    NARCIS (Netherlands)

    van der Wel, A.P.; Klumperink, Eric A.M.; Vandamme, L.K.J.; Nauta, Bram

    In this paper, we present measurements and simulation of random telegraph signal (RTS) noise in n-channel MOSFETs under periodic large signal gate-source excitation (switched bias conditions). This is particularly relevant to analog CMOS circuit design where large signal swings occur and where LF

  19. MULTITEMPORAL CROP TYPE CLASSIFICATION USING CONDITIONAL RANDOM FIELDS AND RAPIDEYE DATA

    Directory of Open Access Journals (Sweden)

    T. Hoberg

    2012-09-01

    Full Text Available The task of crop type classification with multitemporal imagery is nowadays often done applying classifiers that are originally developed for single images like support vector machines (SVM. These approaches do not model temporal dependencies in an explicit way. Existing approaches that make use of temporal dependencies are in most cases quite simple and based on rules. Approaches that integrate temporal dependencies to statistical models are very rare and at an early stage of development. Here our approach CRFmulti, based on conditional random fields (CRF, should make a contribution. Conditional random fields consider context knowledge among neighboring primitives in the same way as Markov random fields (MRF do. Furthermore conditional random fields handle the feature vectors of the neighboring primitives and not only the class labels. Additional to taking spatial context into account, we present an approach for multitemporal data processing where a temporal association potential has been integrated to the common CRF approach to model temporal dependencies. The classification works on pixel ‐level using spectral image features, whereas all available single images are taken separately. For our experiments a high resolution RapidEye satellite data set of 2010 consisting of 4 images made during the whole vegetation period from April to October is taken. Six crop type categories are distinguished, namely grassland, corn, winter crop, rapeseed, root crops and other crops. To evaluate the potential of the new conditional random field approach the classification result is compared to a manual reference on pixel‐ and on object‐level. Additional a SVM approach is applied under the same conditions and should serve as a benchmark.

  20. EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

    Science.gov (United States)

    Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin

    2018-05-01

    Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.

  1. VALIDATION OF A SCALE OF LEVELS AND CONDITIONS OF ORGANIZATIONAL LEARNING

    Directory of Open Access Journals (Sweden)

    DELIO IGNACIO CASTAÑEDA

    2007-08-01

    Full Text Available Organizational learning has been studied from the perspective of levels of learning: individual, group and organizational,as well as from the needed conditions for learning in order to be produced. An instrument of six dimensions wasvalidated, three of them levels: individual, group and organizational, and three of them conditions: culture oforganizational learning, training and transmission of information. Participants were 845 workers of a public institution.From results support was found for the three levels of learning and for two conditions: culture of organizationallearning and training. Additionally a condition called strategic clarity was identified.

  2. 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.

  3. Revisiting Boltzmann learning: parameter estimation in Markov random fields

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Andersen, Lars Nonboe; Kjems, Ulrik

    1996-01-01

    This article presents a generalization of the Boltzmann machine that allows us to use the learning rule for a much wider class of maximum likelihood and maximum a posteriori problems, including both supervised and unsupervised learning. Furthermore, the approach allows us to discuss regularization...... and generalization in the context of Boltzmann machines. We provide an illustrative example concerning parameter estimation in an inhomogeneous Markov field. The regularized adaptation produces a parameter set that closely resembles the “teacher” parameters, hence, will produce segmentations that closely reproduce...

  4. Determination of Initial Conditions for the Safety Analysis by Random Sampling of Operating Parameters

    International Nuclear Information System (INIS)

    Jeong, Hae-Yong; Park, Moon-Ghu

    2015-01-01

    In most existing evaluation methodologies, which follow a conservative approach, the most conservative initial conditions are searched for each transient scenario through tremendous assessment for wide operating windows or limiting conditions for operation (LCO) allowed by the operating guidelines. In this procedure, a user effect could be involved and a remarkable time and human resources are consumed. In the present study, we investigated a more effective statistical method for the selection of the most conservative initial condition by the use of random sampling of operating parameters affecting the initial conditions. A method for the determination of initial conditions based on random sampling of plant design parameters is proposed. This method is expected to be applied for the selection of the most conservative initial plant conditions in the safety analysis using a conservative evaluation methodology. In the method, it is suggested that the initial conditions of reactor coolant flow rate, pressurizer level, pressurizer pressure, and SG level are adjusted by controlling the pump rated flow, setpoints of PLCS, PPCS, and FWCS, respectively. The proposed technique is expected to contribute to eliminate the human factors introduced in the conventional safety analysis procedure and also to reduce the human resources invested in the safety evaluation of nuclear power plants

  5. The Impact of Using Randomized Homework Values on Student Learning

    Science.gov (United States)

    Berardi, Victor

    2011-01-01

    Much of the recent research on homework focuses on using online, web-based, or computerized homework systems. These systems have many reported capabilities and benefits, including the ability to randomize values, which enables multiple attempts by a student or to reduce academic dishonesty. This study reports on the impact of using randomized…

  6. Random Forests for Evaluating Pedagogy and Informing Personalized Learning

    Science.gov (United States)

    Spoon, Kelly; Beemer, Joshua; Whitmer, John C.; Fan, Juanjuan; Frazee, James P.; Stronach, Jeanne; Bohonak, Andrew J.; Levine, Richard A.

    2016-01-01

    Random forests are presented as an analytics foundation for educational data mining tasks. The focus is on course- and program-level analytics including evaluating pedagogical approaches and interventions and identifying and characterizing at-risk students. As part of this development, the concept of individualized treatment effects (ITE) is…

  7. Learning outdoors: male lizards show flexible spatial learning under semi-natural conditions

    Science.gov (United States)

    Noble, Daniel W. A.; Carazo, Pau; Whiting, Martin J.

    2012-01-01

    Spatial cognition is predicted to be a fundamental component of fitness in many lizard species, and yet some studies suggest that it is relatively slow and inflexible. However, such claims are based on work conducted using experimental designs or in artificial contexts that may underestimate their cognitive abilities. We used a biologically realistic experimental procedure (using simulated predatory attacks) to study spatial learning and its flexibility in the lizard Eulamprus quoyii in semi-natural outdoor enclosures under similar conditions to those experienced by lizards in the wild. To evaluate the flexibility of spatial learning, we conducted a reversal spatial-learning task in which positive and negative reinforcements of learnt spatial stimuli were switched. Nineteen (32%) male lizards learnt both tasks within 10 days (spatial task mean: 8.16 ± 0.69 (s.e.) and reversal spatial task mean: 10.74 ± 0.98 (s.e.) trials). We demonstrate that E. quoyii are capable of flexible spatial learning and suggest that future studies focus on a range of lizard species which differ in phylogeny and/or ecology, using biologically relevant cognitive tasks, in an effort to bridge the cognitive divide between ecto- and endotherms. PMID:23075525

  8. Mixed-Handedness Advantages in Episodic Memory Obtained under Conditions of Intentional Learning Extend to Incidental Learning

    Science.gov (United States)

    Christman, Stephen D.; Butler, Michael

    2011-01-01

    The existence of handedness differences in the retrieval of episodic memories is well-documented, but virtually all have been obtained under conditions of intentional learning. Two experiments are reported that extend the presence of such handedness differences to memory retrieval under conditions of incidental learning. Experiment 1 used Craik…

  9. Exploring the relation between teachers’ perceptions of workplace conditions and their professional learning goals

    NARCIS (Netherlands)

    Louws, Monika L.; Meirink, Jacobiene A.; van Veen, Klaas; van Driel, Jan H.

    2017-01-01

    Schools’ structural workplace conditions (e.g. learning resources and professional development policies) and cultural workplace conditions (e.g. school leadership, teachers’ collaborative culture) have been found to affect the way teachers learn. It is not so much the objective conditions that

  10. A Modified FCM Classifier Constrained by Conditional Random Field Model for Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    WANG Shaoyu

    2016-12-01

    Full Text Available Remote sensing imagery has abundant spatial correlation information, but traditional pixel-based clustering algorithms don't take the spatial information into account, therefore the results are often not good. To this issue, a modified FCM classifier constrained by conditional random field model is proposed. Adjacent pixels' priori classified information will have a constraint on the classification of the center pixel, thus extracting spatial correlation information. Spectral information and spatial correlation information are considered at the same time when clustering based on second order conditional random field. What's more, the global optimal inference of pixel's classified posterior probability can be get using loopy belief propagation. The experiment shows that the proposed algorithm can effectively maintain the shape feature of the object, and the classification accuracy is higher than traditional algorithms.

  11. Equivalent conditions of complete moment convergence for extended negatively dependent random variables

    Directory of Open Access Journals (Sweden)

    Qunying Wu

    2017-05-01

    Full Text Available Abstract In this paper, we study the equivalent conditions of complete moment convergence for sequences of identically distributed extended negatively dependent random variables. As a result, we extend and generalize some results of complete moment convergence obtained by Chow (Bull. Inst. Math. Acad. Sin. 16:177-201, 1988 and Li and Spătaru (J. Theor. Probab. 18:933-947, 2005 from the i.i.d. case to extended negatively dependent sequences.

  12. Vibrational spectra of four-coordinated random networks with periodic boundary conditions

    International Nuclear Information System (INIS)

    Guttman, L.

    1976-01-01

    Examples of perfectly four-coordinated networks satisfying periodic boundary conditions are constructed by a pseudo-random process, starting from a crystalline region. The unphysical features (high density, large deviations from the tetrahedral bond-angle) are removed by systematic modification of the bonding scheme. The vibrational spectra are calculated, using a valence-force potential, and the neutron scattering is computed by a phonon-expansion approximation

  13. Genetic correlations among body condition score, yield and fertility in multiparous cows using random regression models

    OpenAIRE

    Bastin, Catherine; Gillon, Alain; Massart, Xavier; Bertozzi, Carlo; Vanderick, Sylvie; Gengler, Nicolas

    2010-01-01

    Genetic correlations between body condition score (BCS) in lactation 1 to 3 and four economically important traits (days open, 305-days milk, fat, and protein yields recorded in the first 3 lactations) were estimated on about 12,500 Walloon Holstein cows using 4-trait random regression models. Results indicated moderate favorable genetic correlations between BCS and days open (from -0.46 to -0.62) and suggested the use of BCS for indirect selection on fertility. However, unfavorable genetic c...

  14. Deep learning the quantum phase transitions in random two-dimensional electron systems

    International Nuclear Information System (INIS)

    Ohtsuki, Tomoki; Ohtsuki, Tomi

    2016-01-01

    Random electron systems show rich phases such as Anderson insulator, diffusive metal, quantum Hall and quantum anomalous Hall insulators, Weyl semimetal, as well as strong/weak topological insulators. Eigenfunctions of each matter phase have specific features, but owing to the random nature of systems, determining the matter phase from eigenfunctions is difficult. Here, we propose the deep learning algorithm to capture the features of eigenfunctions. Localization-delocalization transition, as well as disordered Chern insulator-Anderson insulator transition, is discussed. (author)

  15. Classification of high resolution remote sensing image based on geo-ontology and conditional random fields

    Science.gov (United States)

    Hong, Liang

    2013-10-01

    The availability of high spatial resolution remote sensing data provides new opportunities for urban land-cover classification. More geometric details can be observed in the high resolution remote sensing image, Also Ground objects in the high resolution remote sensing image have displayed rich texture, structure, shape and hierarchical semantic characters. More landscape elements are represented by a small group of pixels. Recently years, the an object-based remote sensing analysis methodology is widely accepted and applied in high resolution remote sensing image processing. The classification method based on Geo-ontology and conditional random fields is presented in this paper. The proposed method is made up of four blocks: (1) the hierarchical ground objects semantic framework is constructed based on geoontology; (2) segmentation by mean-shift algorithm, which image objects are generated. And the mean-shift method is to get boundary preserved and spectrally homogeneous over-segmentation regions ;(3) the relations between the hierarchical ground objects semantic and over-segmentation regions are defined based on conditional random fields framework ;(4) the hierarchical classification results are obtained based on geo-ontology and conditional random fields. Finally, high-resolution remote sensed image data -GeoEye, is used to testify the performance of the presented method. And the experimental results have shown the superiority of this method to the eCognition method both on the effectively and accuracy, which implies it is suitable for the classification of high resolution remote sensing image.

  16. Reconstruction of photon number conditioned states using phase randomized homodyne measurements

    International Nuclear Information System (INIS)

    Chrzanowski, H M; Assad, S M; Bernu, J; Hage, B; Lam, P K; Symul, T; Lund, A P; Ralph, T C

    2013-01-01

    We experimentally demonstrate the reconstruction of a photon number conditioned state without using a photon number discriminating detector. By using only phase randomized homodyne measurements, we reconstruct up to the three photon subtracted squeezed vacuum state. The reconstructed Wigner functions of these states show regions of pronounced negativity, signifying the non-classical nature of the reconstructed states. The techniques presented allow for complete characterization of the role of a conditional measurement on an ensemble of states, and might prove useful in systems where photon counting still proves technically challenging. (paper)

  17. Classification of Phishing Email Using Random Forest Machine Learning Technique

    OpenAIRE

    Akinyelu, Andronicus A.; Adewumi, Aderemi O.

    2013-01-01

    Phishing is one of the major challenges faced by the world of e-commerce today. Thanks to phishing attacks, billions of dollars have been lost by many companies and individuals. In 2012, an online report put the loss due to phishing attack at about $1.5 billion. This global impact of phishing attacks will continue to be on the increase and thus requires more efficient phishing detection techniques to curb the menace. This paper investigates and reports the use of random forest machine learnin...

  18. A Randomized Crossover Design to Assess Learning Impact and Student Preference for Active and Passive Online Learning Modules.

    Science.gov (United States)

    Prunuske, Amy J; Henn, Lisa; Brearley, Ann M; Prunuske, Jacob

    Medical education increasingly involves online learning experiences to facilitate the standardization of curriculum across time and space. In class, delivering material by lecture is less effective at promoting student learning than engaging students in active learning experience and it is unclear whether this difference also exists online. We sought to evaluate medical student preferences for online lecture or online active learning formats and the impact of format on short- and long-term learning gains. Students participated online in either lecture or constructivist learning activities in a first year neurologic sciences course at a US medical school. In 2012, students selected which format to complete and in 2013, students were randomly assigned in a crossover fashion to the modules. In the first iteration, students strongly preferred the lecture modules and valued being told "what they need to know" rather than figuring it out independently. In the crossover iteration, learning gains and knowledge retention were found to be equivalent regardless of format, and students uniformly demonstrated a strong preference for the lecture format, which also on average took less time to complete. When given a choice for online modules, students prefer passive lecture rather than completing constructivist activities, and in the time-limited environment of medical school, this choice results in similar performance on multiple-choice examinations with less time invested. Instructors need to look more carefully at whether assessments and learning strategies are helping students to obtain self-directed learning skills and to consider strategies to help students learn to value active learning in an online environment.

  19. Prospective randomized clinical studies involving reirradiation. Lessons learned

    International Nuclear Information System (INIS)

    Nieder, Carsten; Langendijk, Johannes A.; Guckenberger, Matthias; Grosu, Anca L.

    2016-01-01

    Reirradiation is a potentially useful option for many patients with recurrent cancer. The purpose of this study was to review all recently published randomized trials in order to identify methodological strengths and weaknesses, comment on the results, clinical implications and open questions, and give advice for the planning of future trials. Systematic review of trials published between 2000 and 2015 (databases searched were PubMed, Scopus and Web of Science). We reviewed 9 trials, most of which addressed reirradiation of head and neck tumours. The median number of patients was 69. Trial design, primary endpoint and statistical hypotheses varied widely. The results contribute mainly to decision making for reirradiation of nasopharynx cancer and bone metastases. The trials with relatively long median follow-up confirm that serious toxicity remains a concern after high cumulative total doses. Multi-institutional collaboration is encouraged to complete sufficiently large trials. Despite a paucity of large randomized studies, reirradiation has been adopted in different clinical scenarios by many institutions. Typically, the patients have been assessed by multidisciplinary tumour boards and advanced technologies are used to create highly conformal dose distributions. (orig.) [de

  20. E-learning in pediatric basic life support: a randomized controlled non-inferiority study.

    Science.gov (United States)

    Krogh, Lise Qvirin; Bjørnshave, Katrine; Vestergaard, Lone Due; Sharma, Maja Bendtsen; Rasmussen, Stinne Eika; Nielsen, Henrik Vendelbo; Thim, Troels; Løfgren, Bo

    2015-05-01

    Dissemination of pediatric basic life support (PBLS) skills is recommended. E-learning is accessible and cost-effective, but it is currently unknown whether laypersons can learn PBLS through e-learning. The hypothesis of this study was to investigate whether e-learning PBLS is non-inferior to instructor-led training. Participants were recruited among child-minders and parents of children aged 0-6 years. Participants were randomized to either 2-h instructor-led training or e-learning using an e-learning program (duration 17 min) including an inflatable manikin. After training, participants were assessed in a simulated pediatric cardiac arrest scenario. Tests were video recorded and PBLS skills were assessed independently by two assessors blinded to training method. Primary outcome was the pass rate of the PBLS test (≥8 of 15 skills adequately performed) with a pre-specified non-inferiority margin of 20%. In total 160 participants were randomized 1:1. E-learning was non-inferior to instructor-led training (difference in pass rate -4%; 95% CI -9:0.5). Pass rates were 100% among instructor-led trained (n=67) and 96% among e-learned (n=71). E-learners median time spent on the e-learning program was 30 min (range: 15-120 min) and the median number of log-ons was 2 (range: 1-5). After the study, all participants felt that their skills had improved. E-learning PBLS is non-inferior to instructor-led training among child-minders and parents with children aged 0-6 years, although the pass rate was 4% (95% CI -9:0.5) lower with e-learning. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  1. The effect of adaptive versus static practicing on student learning - evidence from a randomized field experiment

    NARCIS (Netherlands)

    van Klaveren, Chris; Vonk, Sebastiaan; Cornelisz, Ilja

    2017-01-01

    Schools and governments are increasingly investing in adaptive practice software. To date, the evidence whether adaptivity improves learning outcomes is limited and mixed. A large-scale randomized control trial is conducted in Dutch secondary schools to evaluate the effectiveness of an adaptive

  2. Bayesian structure learning for Markov Random Fields with a spike and slab prior

    NARCIS (Netherlands)

    Chen, Y.; Welling, M.; de Freitas, N.; Murphy, K.

    2012-01-01

    In recent years a number of methods have been developed for automatically learning the (sparse) connectivity structure of Markov Random Fields. These methods are mostly based on L1-regularized optimization which has a number of disadvantages such as the inability to assess model uncertainty and

  3. Oncology E-Learning for Undergraduate. A Prospective Randomized Controlled Trial.

    Science.gov (United States)

    da Costa Vieira, René Aloisio; Lopes, Ana Helena; Sarri, Almir José; Benedetti, Zuleica Caulada; de Oliveira, Cleyton Zanardo

    2017-06-01

    The e-learning education is a promising method, but there are few prospective randomized publications in oncology. The purpose of this study was to assess the level of retention of information in oncology from undergraduate students of physiotherapy. A prospective, controlled, randomized, crossover study, 72 undergraduate students of physiotherapy, from the second to fourth years, were randomized to perform a course of physiotherapy in oncology (PHO) using traditional classroom or e-learning. Students were offered the same content of the subject. The teacher in the traditional classroom model and the e-learning students used the Articulate® software. The course tackled the main issues related to PHO, and it was divided into six modules, 18 lessons, evaluated by 126 questions. A diagnosis evaluation was performed previous to the course and after every module. The sample consisted of 67 students, allocated in groups A (n = 35) and B (n = 32), and the distribution was homogeneous between the groups. Evaluating the correct answers, we observed a limited score in the pre-test (average grade 44.6 %), which has significant (p e-learning, a fact that encourages the use of e-learning in oncology. REBECU1111-1142-1963.

  4. Prospective randomized clinical studies involving reirradiation. Lessons learned

    Energy Technology Data Exchange (ETDEWEB)

    Nieder, Carsten [Nordland Hospital, Department of Oncology and Palliative Medicine, Bodoe (Norway); University of Tromsoe, Department of Clinical Medicine, Faculty of Health Sciences, Tromsoe (Norway); Langendijk, Johannes A. [University Medical Centre Groningen, Department of Radiation Oncology, Groningen (Netherlands); Guckenberger, Matthias [University Hospital Zuerich, Department of Radiation Oncology, Zuerich (Switzerland); Grosu, Anca L. [University Hospital Freiburg, Department of Radiation Oncology, Freiburg (Germany)

    2016-10-15

    Reirradiation is a potentially useful option for many patients with recurrent cancer. The purpose of this study was to review all recently published randomized trials in order to identify methodological strengths and weaknesses, comment on the results, clinical implications and open questions, and give advice for the planning of future trials. Systematic review of trials published between 2000 and 2015 (databases searched were PubMed, Scopus and Web of Science). We reviewed 9 trials, most of which addressed reirradiation of head and neck tumours. The median number of patients was 69. Trial design, primary endpoint and statistical hypotheses varied widely. The results contribute mainly to decision making for reirradiation of nasopharynx cancer and bone metastases. The trials with relatively long median follow-up confirm that serious toxicity remains a concern after high cumulative total doses. Multi-institutional collaboration is encouraged to complete sufficiently large trials. Despite a paucity of large randomized studies, reirradiation has been adopted in different clinical scenarios by many institutions. Typically, the patients have been assessed by multidisciplinary tumour boards and advanced technologies are used to create highly conformal dose distributions. (orig.) [German] Eine Rebestrahlung kann fuer viele Patienten mit rezidivierenden Malignomen eine nuetzliche Option bieten. Der Zweck dieser Studie bestand darin, alle in der juengeren Vergangenheit publizierten randomisierten Studien zu beurteilen, da deren methodische Staerken und Schwaechen, Ergebnisse und resultierende Implikationen bzw. offene Fragen die Planung kuenftiger Studien wesentlich beeinflussen koennen. Systematische Uebersicht aller zwischen 2000 und 2015 veroeffentlichten Studien (Literatursuche ueber PubMed, Scopus und Web of Science). Ausgewertet wurden 9 Studien, in die vor allem Patienten mit Kopf-Hals-Tumoren eingeschlossen waren. Im Median hatten 69 Patienten teilgenommen. Das

  5. Mental health first aid training by e-learning: a randomized controlled trial.

    Science.gov (United States)

    Jorm, Anthony F; Kitchener, Betty A; Fischer, Julie-Anne; Cvetkovski, Stefan

    2010-12-01

    Mental Health First Aid training is a course for the public that teaches how to give initial help to a person developing a mental health problem or in a mental health crisis. The present study evaluated the effects of Mental Health First Aid training delivered by e-learning on knowledge about mental disorders, stigmatizing attitudes and helping behaviour. A randomized controlled trial was carried out with 262 members of the Australian public. Participants were randomly assigned to complete an e-learning CD, read a Mental Health First Aid manual or be in a waiting list control group. The effects of the interventions were evaluated using online questionnaires pre- and post-training and at 6-months follow up. The questionnaires covered mental health knowledge, stigmatizing attitudes, confidence in providing help to others, actions taken to implement mental health first aid and participant mental health. Both e-learning and the printed manual increased aspects of knowledge, reduced stigma and increased confidence compared to waiting list. E-learning also improved first aid actions taken more than waiting list, and was superior to the printed manual in reducing stigma and disability due to mental ill health. Mental Health First Aid information received by either e-learning or printed manual had positive effects, but e-learning was better at reducing stigma.

  6. Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base

    Directory of Open Access Journals (Sweden)

    Chuan Gu

    2015-01-01

    Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.

  7. Initial conditions for slow-roll inflation in a random Gaussian landscape

    Energy Technology Data Exchange (ETDEWEB)

    Masoumi, Ali; Vilenkin, Alexander; Yamada, Masaki, E-mail: ali@cosmos.phy.tufts.edu, E-mail: vilenkin@cosmos.phy.tufts.edu, E-mail: Masaki.Yamada@tufts.edu [Institute of Cosmology, Department of Physics and Astronomy, Tufts University, Medford, MA 02155 (United States)

    2017-07-01

    In the landscape perspective, our Universe begins with a quantum tunneling from an eternally-inflating parent vacuum, followed by a period of slow-roll inflation. We investigate the tunneling process and calculate the probability distribution for the initial conditions and for the number of e-folds of slow-roll inflation, modeling the landscape by a small-field one-dimensional random Gaussian potential. We find that such a landscape is fully consistent with observations, but the probability for future detection of spatial curvature is rather low, P ∼ 10{sup −3}.

  8. Using Conditional Random Fields to Extract Contexts and Answers of Questions from Online Forums

    DEFF Research Database (Denmark)

    Ding, Shilin; Cong, Gao; Lin, Chin-Yew

    2008-01-01

    Online forum discussions often contain vast amounts of questions that are the focuses of discussions. Extracting contexts and answers together with the questions will yield not only a coherent forum summary but also a valuable QA knowledge base. In this paper, we propose a general framework based...... on Conditional Random Fields (CRFs) to detect the contexts and answers of questions from forum threads. We improve the basic framework by Skip-chain CRFs and 2D CRFs to better accommodate the features of forums for better performance. Experimental results show that our techniques are very promising....

  9. Condition for invariant spectrum of an electromagnetic wave scattered from an anisotropic random media.

    Science.gov (United States)

    Li, Jia; Wu, Pinghui; Chang, Liping

    2015-08-24

    Within the accuracy of the first-order Born approximation, sufficient conditions are derived for the invariance of spectrum of an electromagnetic wave, which is generated by the scattering of an electromagnetic plane wave from an anisotropic random media. We show that the following restrictions on properties of incident fields and the anisotropic media must be simultaneously satisfied: 1) the elements of the dielectric susceptibility matrix of the media must obey the scaling law; 2) the spectral components of the incident field are proportional to each other; 3) the second moments of the elements of the dielectric susceptibility matrix of the media are inversely proportional to the frequency.

  10. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

    Science.gov (United States)

    Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

  11. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

    Directory of Open Access Journals (Sweden)

    Emre O. Neftci

    2017-06-01

    Full Text Available An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

  12. Conditional random slope: A new approach for estimating individual child growth velocity in epidemiological research.

    Science.gov (United States)

    Leung, Michael; Bassani, Diego G; Racine-Poon, Amy; Goldenberg, Anna; Ali, Syed Asad; Kang, Gagandeep; Premkumar, Prasanna S; Roth, Daniel E

    2017-09-10

    Conditioning child growth measures on baseline accounts for regression to the mean (RTM). Here, we present the "conditional random slope" (CRS) model, based on a linear-mixed effects model that incorporates a baseline-time interaction term that can accommodate multiple data points for a child while also directly accounting for RTM. In two birth cohorts, we applied five approaches to estimate child growth velocities from 0 to 12 months to assess the effect of increasing data density (number of measures per child) on the magnitude of RTM of unconditional estimates, and the correlation and concordance between the CRS and four alternative metrics. Further, we demonstrated the differential effect of the choice of velocity metric on the magnitude of the association between infant growth and stunting at 2 years. RTM was minimally attenuated by increasing data density for unconditional growth modeling approaches. CRS and classical conditional models gave nearly identical estimates with two measures per child. Compared to the CRS estimates, unconditional metrics had moderate correlation (r = 0.65-0.91), but poor agreement in the classification of infants with relatively slow growth (kappa = 0.38-0.78). Estimates of the velocity-stunting association were the same for CRS and classical conditional models but differed substantially between conditional versus unconditional metrics. The CRS can leverage the flexibility of linear mixed models while addressing RTM in longitudinal analyses. © 2017 The Authors American Journal of Human Biology Published by Wiley Periodicals, Inc.

  13. Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial.

    Science.gov (United States)

    Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

    2014-01-01

    This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (Pvideo group performed better on the follow-up test (P=0.04). Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.

  14. Learning to Dislike Chocolate: Conditioning Negative Attitudes toward Chocolate and Its Effect on Chocolate Consumption

    OpenAIRE

    Wang, Yan; Wang, Guosen; Zhang, Dingyuan; Wang, Lei; Cui, Xianghua; Zhu, Jinglei; Fang, Yuan

    2017-01-01

    Evaluative conditioning (EC) procedures can be used to form and change attitudes toward a wide variety of objects. The current study examined the effects of a negative EC procedure on attitudes toward chocolate, and whether it influenced chocolate evaluation and consumption. Participants were randomly assigned to the experimental condition in which chocolate images were paired with negative stimuli, or the control condition in which chocolate images were randomly paired with positive stimuli ...

  15. Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

    Science.gov (United States)

    Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2018-01-01

    Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by

  16. Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

    Science.gov (United States)

    Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2017-09-01

    Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven

  17. Effect of improving the usability of an e-learning resource: a randomized trial.

    Science.gov (United States)

    Davids, Mogamat Razeen; Chikte, Usuf M E; Halperin, Mitchell L

    2014-06-01

    Optimizing the usability of e-learning materials is necessary to reduce extraneous cognitive load and maximize their potential educational impact. However, this is often neglected, especially when time and other resources are limited. We conducted a randomized trial to investigate whether a usability evaluation of our multimedia e-learning resource, followed by fixing of all problems identified, would translate into improvements in usability parameters and learning by medical residents. Two iterations of our e-learning resource [version 1 (V1) and version 2 (V2)] were compared. V1 was the first fully functional version and V2 was the revised version after all identified usability problems were addressed. Residents in internal medicine and anesthesiology were randomly assigned to one of the versions. Usability was evaluated by having participants complete a user satisfaction questionnaire and by recording and analyzing their interactions with the application. The effect on learning was assessed by questions designed to test the retention and transfer of knowledge. Participants reported high levels of satisfaction with both versions, with good ratings on the System Usability Scale and adjective rating scale. In contrast, analysis of video recordings revealed significant differences in the occurrence of serious usability problems between the two versions, in particular in the interactive HandsOn case with its treatment simulation, where there was a median of five serious problem instances (range: 0-50) recorded per participant for V1 and zero instances (range: 0-1) for V2 (P e-learning resource resulted in significant improvements in usability. This is likely to translate into improved motivation and willingness to engage with the learning material. In this population of relatively high-knowledge participants, learning scores were similar across the two versions. Copyright © 2014 The American Physiological Society.

  18. Drosophila Courtship Conditioning As a Measure of Learning and Memory

    NARCIS (Netherlands)

    Koemans, T.S.; Oppitz, C.; Donders, R.; Bokhoven, H. van; Schenck, A.; Keleman, K.; Kramer, J.M.

    2017-01-01

    Many insights into the molecular mechanisms underlying learning and memory have been elucidated through the use of simple behavioral assays in model organisms such as the fruit fly, Drosophila melanogaster. Drosophila is useful for understanding the basic neurobiology underlying cognitive deficits

  19. Estimators for initial conditions for optimisation in learning hydraulic systems

    NARCIS (Netherlands)

    Post, W.J.A.E.M.; Burrows, C.R.; Edge, K.A.

    1998-01-01

    In Learning Hydraulic Systems (LHS1. developed at the Eindhoven University of Technology, a specialised optimisation routine is employed In order to reduce energy losses in hydraulic systems. Typical load situations which can be managed by LHS are variable cyclic loads, as can be observed In many

  20. Necessary conditions for the invariant measure of a random walk to be a sum of geometric terms

    NARCIS (Netherlands)

    Chen, Y.; Boucherie, Richardus J.; Goseling, Jasper

    We consider the invariant measure of homogeneous random walks in the quarter-plane. In particular, we consider measures that can be expressed as an infinite sum of geometric terms. We present necessary conditions for the invariant measure of a random walk to be a sum of geometric terms. We

  1. Condition-Based Conveyor Belt Replacement Strategy in Lignite Mines with Random Belt Deterioration

    Science.gov (United States)

    Blazej, Ryszard; Jurdziak, Leszek

    2017-12-01

    In Polish lignite surface mines, condition-based belt replacement strategies are applied in order to assure profitable refurbishment of worn out belts performed by external firms specializing in belt maintenance. In two of three lignite mines, staff asses belt condition subjectively during visual inspections. Only one mine applies specialized diagnostic device (HRDS) allowing objective magnetic evaluation of belt core condition in order to choose the most profitable moment for the dismantling of worn out belt segments from conveyors and sending them to the maintenance firm which provides their refurbishment. This article describes the advantages of a new diagnostic device called DiagBelt. It was developed at the Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology. Economic gains from its application are calculated for the lignite mine and for the belt maintenance firm, taking into account random life (durability) of new and reconditioned belts (after the 1st and the 2nd refurbishment). Recursive calculations for following years allow the estimation of the length and costs of replaced, reconditioned and purchased belts on an annual basis, while the use of the Monte Carlo method allows the estimation of their variability caused by random deterioration of belts. Savings are obtained due to better selection of moments (times) for the replacement of belt segments and die to the possibility to qualify worn out belts for refurbishment without the need to remove their covers. In effect, increased belt durability and lowered share of waste belts (which were not qualified for reconditioning) create savings which can quickly cover expenditures on new diagnostic tools and regular belt inspections in the mine.

  2. Mountain Plains Learning Experience Guide: Heating, Refrigeration, & Air Conditioning.

    Science.gov (United States)

    Carey, John

    This Heating, Refrigeration, and Air Conditioning course is comprised of eleven individualized units: (1) Refrigeration Tools, Materials, and Refrigerant; (2) Basic Heating and Air Conditioning; (3) Sealed System Repairs; (4) Basic Refrigeration Systems; (5) Compression Systems and Compressors; (6) Refrigeration Controls; (7) Electric Circuit…

  3. A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

    Directory of Open Access Journals (Sweden)

    Joseph Mascaro

    Full Text Available Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus. The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag", which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

  4. A tale of two "forests": random forest machine learning AIDS tropical forest carbon mapping.

    Science.gov (United States)

    Mascaro, Joseph; Asner, Gregory P; Knapp, David E; Kennedy-Bowdoin, Ty; Martin, Roberta E; Anderson, Christopher; Higgins, Mark; Chadwick, K Dana

    2014-01-01

    Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including--in the latter case--x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called "out-of-bag"), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha(-1) when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

  5. Subgeometric Ergodicity Analysis of Continuous-Time Markov Chains under Random-Time State-Dependent Lyapunov Drift Conditions

    Directory of Open Access Journals (Sweden)

    Mokaedi V. Lekgari

    2014-01-01

    Full Text Available We investigate random-time state-dependent Foster-Lyapunov analysis on subgeometric rate ergodicity of continuous-time Markov chains (CTMCs. We are mainly concerned with making use of the available results on deterministic state-dependent drift conditions for CTMCs and on random-time state-dependent drift conditions for discrete-time Markov chains and transferring them to CTMCs.

  6. Pediatric emergency medicine asynchronous e-learning: a multicenter randomized controlled Solomon four-group study.

    Science.gov (United States)

    Chang, Todd P; Pham, Phung K; Sobolewski, Brad; Doughty, Cara B; Jamal, Nazreen; Kwan, Karen Y; Little, Kim; Brenkert, Timothy E; Mathison, David J

    2014-08-01

    Asynchronous e-learning allows for targeted teaching, particularly advantageous when bedside and didactic education is insufficient. An asynchronous e-learning curriculum has not been studied across multiple centers in the context of a clinical rotation. We hypothesize that an asynchronous e-learning curriculum during the pediatric emergency medicine (EM) rotation improves medical knowledge among residents and students across multiple participating centers. Trainees on pediatric EM rotations at four large pediatric centers from 2012 to 2013 were randomized in a Solomon four-group design. The experimental arms received an asynchronous e-learning curriculum consisting of nine Web-based, interactive, peer-reviewed Flash/HTML5 modules. Postrotation testing and in-training examination (ITE) scores quantified improvements in knowledge. A 2 × 2 analysis of covariance (ANCOVA) tested interaction and main effects, and Pearson's correlation tested associations between module usage, scores, and ITE scores. A total of 256 of 458 participants completed all study elements; 104 had access to asynchronous e-learning modules, and 152 were controls who used the current education standards. No pretest sensitization was found (p = 0.75). Use of asynchronous e-learning modules was associated with an improvement in posttest scores (p effect (partial η(2) = 0.19). Posttest scores correlated with ITE scores (r(2) = 0.14, p e-learning is an effective educational tool to improve knowledge in a clinical rotation. Web-based asynchronous e-learning is a promising modality to standardize education among multiple institutions with common curricula, particularly in clinical rotations where scheduling difficulties, seasonality, and variable experiences limit in-hospital learning. © 2014 by the Society for Academic Emergency Medicine.

  7. Random Forest Approach to QSPR Study of Fluorescence Properties Combining Quantum Chemical Descriptors and Solvent Conditions.

    Science.gov (United States)

    Chen, Chia-Hsiu; Tanaka, Kenichi; Funatsu, Kimito

    2018-04-22

    The Quantitative Structure - Property Relationship (QSPR) approach was performed to study the fluorescence absorption wavelengths and emission wavelengths of 413 fluorescent dyes in different solvent conditions. The dyes included the chromophore derivatives of cyanine, xanthene, coumarin, pyrene, naphthalene, anthracene and etc., with the wavelength ranging from 250 nm to 800 nm. An ensemble method, random forest (RF), was employed to construct nonlinear prediction models compared with the results of linear partial least squares and nonlinear support vector machine regression models. Quantum chemical descriptors derived from density functional theory method and solvent information were also used by constructing models. The best prediction results were obtained from RF model, with the squared correlation coefficients [Formula: see text] of 0.940 and 0.905 for λ abs and λ em , respectively. The descriptors used in the models were discussed in detail in this report by comparing the feature importance of RF.

  8. Ice Water Classification Using Statistical Distribution Based Conditional Random Fields in RADARSAT-2 Dual Polarization Imagery

    Science.gov (United States)

    Zhang, Y.; Li, F.; Zhang, S.; Hao, W.; Zhu, T.; Yuan, L.; Xiao, F.

    2017-09-01

    In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.

  9. Sign Language Recognition with the Kinect Sensor Based on Conditional Random Fields

    Directory of Open Access Journals (Sweden)

    Hee-Deok Yang

    2014-12-01

    Full Text Available Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D space. In this research, we use 3D depth information from hand motions, generated from Microsoft’s Kinect sensor and apply a hierarchical conditional random field (CRF that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%.

  10. Hidden State Conditional Random Field for Abnormal Activity Recognition in Smart Homes

    Directory of Open Access Journals (Sweden)

    Yu Tong

    2015-03-01

    Full Text Available As the number of elderly people has increased worldwide, there has been a surge of research into assistive technologies to provide them with better care by recognizing their normal and abnormal activities. However, existing abnormal activity recognition (AAR algorithms rarely consider sub-activity relations when recognizing abnormal activities. This paper presents an application of the Hidden State Conditional Random Field (HCRF method to detect and assess abnormal activities that often occur in elderly persons’ homes. Based on HCRF, this paper designs two AAR algorithms, and validates them by comparing them with a feature vector distance based algorithm in two experiments. The results demonstrate that the proposed algorithms favorably outperform the competitor, especially when abnormal activities have same sensor type and sensor number as normal activities.

  11. Learning by random walks in the weight space of the Ising perceptron

    International Nuclear Information System (INIS)

    Huang, Haiping; Zhou, Haijun

    2010-01-01

    Several variants of a stochastic local search process for constructing the synaptic weights of an Ising perceptron are studied. In this process, binary patterns are sequentially presented to the Ising perceptron and are then learned as the synaptic weight configuration is modified through a chain of single- or double-weight flips within the compatible weight configuration space of the earlier learned patterns. This process is able to reach a storage capacity of α≈0.63 for pattern length N = 101 and α≈0.41 for N = 1001. If in addition a relearning process is exploited, the learning performance is further improved to a storage capacity of α≈0.80 for N = 101 and α≈0.42 for N = 1001. We found that, for a given learning task, the solutions constructed by the random walk learning process are separated by a typical Hamming distance, which decreases with the constraint density α of the learning task; at a fixed value of α, the width of the Hamming distance distribution decreases with N

  12. Collaborative Random Faces-Guided Encoders for Pose-Invariant Face Representation Learning.

    Science.gov (United States)

    Shao, Ming; Zhang, Yizhe; Fu, Yun

    2018-04-01

    Learning discriminant face representation for pose-invariant face recognition has been identified as a critical issue in visual learning systems. The challenge lies in the drastic changes of facial appearances between the test face and the registered face. To that end, we propose a high-level feature learning framework called "collaborative random faces (RFs)-guided encoders" toward this problem. The contributions of this paper are three fold. First, we propose a novel supervised autoencoder that is able to capture the high-level identity feature despite of pose variations. Second, we enrich the identity features by replacing the target values of conventional autoencoders with random signals (RFs in this paper), which are unique for each subject under different poses. Third, we further improve the performance of the framework by incorporating deep convolutional neural network facial descriptors and linking discriminative identity features from different RFs for the augmented identity features. Finally, we conduct face identification experiments on Multi-PIE database, and face verification experiments on labeled faces in the wild and YouTube Face databases, where face recognition rate and verification accuracy with Receiver Operating Characteristic curves are rendered. In addition, discussions of model parameters and connections with the existing methods are provided. These experiments demonstrate that our learning system works fairly well on handling pose variations.

  13. A Mock Randomized Controlled Trial With Audience Response Technology for Teaching and Learning Epidemiology.

    Science.gov (United States)

    Baker, Philip R A; Francis, Daniel P; Cathcart, Abby

    2017-04-01

    The study's objective was to apply and assess an active learning approach to epidemiology and critical appraisal. Active learning comprised a mock, randomized controlled trial (RCT) conducted with learners in 3 countries. The mock trial consisted of blindly eating red Smarties candy (intervention) compared to yellow Smarties (control) to determine whether red Smarties increase happiness. Audience response devices were employed with the 3-fold purposes to produce outcome data for analysis of the effects of red Smarties, identify baseline and subsequent changes in participant's knowledge and confidence in understanding of RCTs, and assess the teaching approach. Of those attending, 82% (117 of 143 learners) participated in the trial component. Participating in the mock trial was a positive experience, and the use of the technology aided learning. The trial produced data that learners analyzed in "real time" during the class. The mock RCT is a fun and engaging approach to teaching RCTs and helping students to develop skills in critical appraisal.

  14. Food2Learn: Randomized control trial investigating influence of krill oil supplementation on learning, cognition, and behaviour in healthy adolescents. Design presentation

    NARCIS (Netherlands)

    Van der Wurff, Inge; Von Schacky, Clemens; Berge, Kjetil; Kirschner, Paul A.; De Groot, Renate

    2014-01-01

    Food2Learn is a double blind randomized controlled trial which looks at the influence of Krill oil (rich in LCPUFA) on the cognitive performance, academic performance and mental well-being of student of lower vocational schools.

  15. Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Hummel, Hans; Koper, Rob

    2008-01-01

    Drachsler, H., Hummel, H. G. K., & Koper, R. (2009). Identifying the Goal, User model and Conditions of Recommender Systems for Formal and Informal Learning. Journal of Digital Information, 10(2), 4-24.

  16. Does reviewing lead to better learning and decision making? Answers from a randomized stock market experiment.

    Science.gov (United States)

    Wessa, Patrick; Holliday, Ian E

    2012-01-01

    The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. We conducted a randomized experiment, assigning students randomly to receive PR or non-PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re-use statistical results from peers, Collaborative PR, and an AI-enhanced Stock Market Engine. The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non-Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

  17. Self-reported recognition of undiagnosed life threatening conditions in chiropractic practice: a random survey

    Directory of Open Access Journals (Sweden)

    Daniel Dwain M

    2012-07-01

    Full Text Available Abstract Background The purpose of this study was to identify the type and frequency of previously undiagnosed life threatening conditions (LTC, based on self-reports of chiropractic physicians, which were first recognized by the chiropractic physician. Additionally this information may have a preliminary role in determining whether chiropractic education provides the knowledge necessary to recognize these events. Methods The study design was a postal, cross-sectional, epidemiological self-administered survey. Two thousand Doctors of Chiropractic in the US were randomly selected from a list of 57878. The survey asked respondents to state the number of cases from the list where they were the first physician to recognize the condition over the course of their practice careers. Space was provided for unlisted conditions. Results The response rate was 29.9%. Respondents represented 11442 years in practice and included 3861 patients with a reported undiagnosed LTC. The most commonly presenting conditions were in rank order: carcinoma, abdominal aneurysm, deep vein thrombosis, stroke, myocardial infarction, subdural hematoma and a large group of other diagnoses. The occurrence of a previously undiagnosed LTC can be expected to present to the chiropractic physician every 2.5 years based on the responding doctors reports. Conclusion Based on this survey chiropractic physicians report encountering undiagnosed LTC’s in the normal course of practice. The findings of this study are of importance to the chiropractic profession and chiropractic education. Increased awareness and emphasis on recognition of LTC is a critical part of the education process and practice life.

  18. A randomized controlled trial of an online, modular, active learning training program for behavioral activation for depression.

    Science.gov (United States)

    Puspitasari, Ajeng J; Kanter, Jonathan W; Busch, Andrew M; Leonard, Rachel; Dunsiger, Shira; Cahill, Shawn; Martell, Christopher; Koerner, Kelly

    2017-08-01

    This randomized-controlled trial assessed the efficacy of a trainer-led, active-learning, modular, online behavioral activation (BA) training program compared with a self-paced online BA training with the same modular content. Seventy-seven graduate students (M = 30.3 years, SD = 6.09; 76.6% female) in mental health training programs were randomly assigned to receive either the trainer-led or self-paced BA training. Both trainings consisted of 4 weekly sessions covering 4 core BA strategies. Primary outcomes were changes in BA skills as measured by an objective role-play assessment and self-reported use of BA strategies. Assessments were conducted at pre-, post-, and 6-weeks after training. A series of longitudinal mixed effect models assessed changes in BA skills and a longitudinal model implemented with generalized estimating equations assessed BA use over time. Significantly greater increases in total BA skills were found in the trainer-led training condition. The trainer-led training condition also showed greater increases in all core BA skills either at posttraining, follow-up, or both. Reported use of BA strategies with actual clients increased significantly from pre- to posttraining and maintained at follow-up in both training conditions. This trial adds to the literature on the efficacy of online training as a method to disseminate BA. Online training with an active learning, modular approach may be a promising and accessible implementation strategy. Additional strategies may need to be paired with the online BA training to assure the long-term implementation and sustainability of BA in clinical practice. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  19. 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...

  20. Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

    Science.gov (United States)

    Lindsay, Grace W.

    2017-01-01

    Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (

  1. Mechanisms of Radiation-Induced Conditioned Taste Aversion Learning

    Science.gov (United States)

    1986-01-01

    impairment of the synthesis of these cells, especially those in In addition to emesis. exposure to lower doses of ionizing bone marrow. However. since...pretreatment with fluoxetine in gustatory conditioning. 629-635. 1983. Pharmnat l Bioc/n-a 8,4,ui 17: 431-443. 1982. 100. Rabin. B. M. and J. S. Rabin

  2. A METHOD TO ESTIMATE TEMPORAL INTERACTION IN A CONDITIONAL RANDOM FIELD BASED APPROACH FOR CROP RECOGNITION

    Directory of Open Access Journals (Sweden)

    P. M. A. Diaz

    2016-06-01

    Full Text Available This paper presents a method to estimate the temporal interaction in a Conditional Random Field (CRF based approach for crop recognition from multitemporal remote sensing image sequences. This approach models the phenology of different crop types as a CRF. Interaction potentials are assumed to depend only on the class labels of an image site at two consecutive epochs. In the proposed method, the estimation of temporal interaction parameters is considered as an optimization problem, whose goal is to find the transition matrix that maximizes the CRF performance, upon a set of labelled data. The objective functions underlying the optimization procedure can be formulated in terms of different accuracy metrics, such as overall and average class accuracy per crop or phenological stages. To validate the proposed approach, experiments were carried out upon a dataset consisting of 12 co-registered LANDSAT images of a region in southeast of Brazil. Pattern Search was used as the optimization algorithm. The experimental results demonstrated that the proposed method was able to substantially outperform estimates related to joint or conditional class transition probabilities, which rely on training samples.

  3. Segmentation of Large Unstructured Point Clouds Using Octree-Based Region Growing and Conditional Random Fields

    Science.gov (United States)

    Bassier, M.; Bonduel, M.; Van Genechten, B.; Vergauwen, M.

    2017-11-01

    Point cloud segmentation is a crucial step in scene understanding and interpretation. The goal is to decompose the initial data into sets of workable clusters with similar properties. Additionally, it is a key aspect in the automated procedure from point cloud data to BIM. Current approaches typically only segment a single type of primitive such as planes or cylinders. Also, current algorithms suffer from oversegmenting the data and are often sensor or scene dependent. In this work, a method is presented to automatically segment large unstructured point clouds of buildings. More specifically, the segmentation is formulated as a graph optimisation problem. First, the data is oversegmented with a greedy octree-based region growing method. The growing is conditioned on the segmentation of planes as well as smooth surfaces. Next, the candidate clusters are represented by a Conditional Random Field after which the most likely configuration of candidate clusters is computed given a set of local and contextual features. The experiments prove that the used method is a fast and reliable framework for unstructured point cloud segmentation. Processing speeds up to 40,000 points per second are recorded for the region growing. Additionally, the recall and precision of the graph clustering is approximately 80%. Overall, nearly 22% of oversegmentation is reduced by clustering the data. These clusters will be classified and used as a basis for the reconstruction of BIM models.

  4. A Randomized Controlled Trial of Intensive Sleep Retraining (ISR): A Brief Conditioning Treatment for Chronic Insomnia

    Science.gov (United States)

    Harris, Jodie; Lack, Leon; Kemp, Kristyn; Wright, Helen; Bootzin, Richard

    2012-01-01

    Study Objective: To investigate the effectiveness of intensive sleep retraining in comparison and combination with traditional behavioral intervention for chronic primary insomnia. Participants: Seventy-nine volunteers with chronic sleep-onset insomnia (with or without sleep maintenance difficulties) were randomly assigned either to intensive sleep retraining (ISR), stimulus control therapy (SCT), ISR plus SCT, or the control (sleep hygiene) treatment condition. Intervention: ISR treatment consisted of 50 sleep onset trials over a 25-h sleep deprivation period. Measurements and Results: Treatment response was assessed with sleep diary, activity monitoring, and questionnaire measures. The active treatment groups (ISR, SCT, ISR+SCT) all resulted in significant improvements in sleep onset latency and sleep efficiency, with moderate to large effect sizes from pre- to post-treatment. Wake time after sleep onset decreased significantly in the SCT and ISR+SCT groups. Total sleep time increased significantly in the ISR and ISR+SCT treatment groups. Participants receiving ISR (ISR, ISR+SCT) experienced rapidly improved SOL and TST during treatment, suggesting an advantage of rapid improvements in sleep in response to ISR. Although there were few statistically significant differences between groups on individual variables, ISR+SCT resulted in consistently larger effect sizes of change than other treatments, including questionnaire measures of sleep quality, sleep self-efficacy, and daytime functioning. The combination treatment group (ISR+SCT) showed trends to outperform other active treatment groups with fewer treatment dropouts, and a greater proportion of treatment responders with 61% reaching “good sleeper” status. Treatment gains achieved at post-treatment in the active treatment groups were largely maintained throughout follow-up periods to 6 months. Conclusion: This 25-hour intensive conditioning treatment for chronic insomnia can produce rapid improvements in

  5. Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Buch SV

    2014-08-01

    Full Text Available Steen Vigh Buch,1 Frederik Philip Treschow,2 Jesper Brink Svendsen,3 Bjarne Skjødt Worm4 1Department of Vascular Surgery, Rigshospitalet, Copenhagen, Denmark; 2Department of Anesthesia and Intensive Care, Herlev Hospital, Copenhagen, Denmark; 3Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 4Department of Anesthesia and Intensive Care, Bispebjerg Hospital, Copenhagen, Denmark Background and aims: This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods: Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results: The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001 and in the follow-up test (P<0.01. Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04. Conclusion: Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills. Keywords: e-learning, video versus text, medicine, clinical skills

  6. Self-learning basic life support: A randomised controlled trial on learning conditions.

    Science.gov (United States)

    Pedersen, Tina Heidi; Kasper, Nina; Roman, Hari; Egloff, Mike; Marx, David; Abegglen, Sandra; Greif, Robert

    2018-05-01

    To investigate whether pure self-learning without instructor support, resulted in the same BLS-competencies as facilitator-led learning, when using the same commercially available video BLS teaching kit. First-year medical students were randomised to either BLS self-learning without supervision or facilitator-led BLS-teaching. Both groups used the MiniAnne kit (Laerdal Medical, Stavanger, Norway) in the students' local language. Directly after the teaching and three months later, all participants were tested on their BLS-competencies in a simulated scenario, using the Resusci Anne SkillReporter™ (Laerdal Medical, Stavanger, Norway). The primary outcome was percentage of correct cardiac compressions three months after the teaching. Secondary outcomes were all other BLS parameters recorded by the SkillReporter and parameters from a BLS-competence rating form. 240 students were assessed at baseline and 152 students participated in the 3-month follow-up. For our primary outcome, the percentage of correct compressions, we found a median of 48% (interquartile range (IQR) 10-83) for facilitator-led learning vs. 42% (IQR 14-81) for self-learning (p = 0.770) directly after the teaching. In the 3-month follow-up, the rate of correct compressions dropped to 28% (IQR 6-59) for facilitator-led learning (p = 0.043) and did not change significantly in the self-learning group (47% (IQR 12-78), p = 0.729). Self-learning is not inferior to facilitator-led learning in the short term. Self-learning resulted in a better retention of BLS-skills three months after training compared to facilitator-led training. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Genetic correlations between body condition scores and fertility in dairy cattle using bivariate random regression models.

    Science.gov (United States)

    De Haas, Y; Janss, L L G; Kadarmideen, H N

    2007-10-01

    Genetic correlations between body condition score (BCS) and fertility traits in dairy cattle were estimated using bivariate random regression models. BCS was recorded by the Swiss Holstein Association on 22,075 lactating heifers (primiparous cows) from 856 sires. Fertility data during first lactation were extracted for 40,736 cows. The fertility traits were days to first service (DFS), days between first and last insemination (DFLI), calving interval (CI), number of services per conception (NSPC) and conception rate to first insemination (CRFI). A bivariate model was used to estimate genetic correlations between BCS as a longitudinal trait by random regression components, and daughter's fertility at the sire level as a single lactation measurement. Heritability of BCS was 0.17, and heritabilities for fertility traits were low (0.01-0.08). Genetic correlations between BCS and fertility over the lactation varied from: -0.45 to -0.14 for DFS; -0.75 to 0.03 for DFLI; from -0.59 to -0.02 for CI; from -0.47 to 0.33 for NSPC and from 0.08 to 0.82 for CRFI. These results show (genetic) interactions between fat reserves and reproduction along the lactation trajectory of modern dairy cows, which can be useful in genetic selection as well as in management. Maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in mid lactation when the genetic variance for BCS is largest, and the genetic correlations between BCS and fertility is strongest.

  8. AUTOCLASSIFICATION OF THE VARIABLE 3XMM SOURCES USING THE RANDOM FOREST MACHINE LEARNING ALGORITHM

    International Nuclear Information System (INIS)

    Farrell, Sean A.; Murphy, Tara; Lo, Kitty K.

    2015-01-01

    In the current era of large surveys and massive data sets, autoclassification of astrophysical sources using intelligent algorithms is becoming increasingly important. In this paper we present the catalog of variable sources in the Third XMM-Newton Serendipitous Source catalog (3XMM) autoclassified using the Random Forest machine learning algorithm. We used a sample of manually classified variable sources from the second data release of the XMM-Newton catalogs (2XMMi-DR2) to train the classifier, obtaining an accuracy of ∼92%. We also evaluated the effectiveness of identifying spurious detections using a sample of spurious sources, achieving an accuracy of ∼95%. Manual investigation of a random sample of classified sources confirmed these accuracy levels and showed that the Random Forest machine learning algorithm is highly effective at automatically classifying 3XMM sources. Here we present the catalog of classified 3XMM variable sources. We also present three previously unidentified unusual sources that were flagged as outlier sources by the algorithm: a new candidate supergiant fast X-ray transient, a 400 s X-ray pulsar, and an eclipsing 5 hr binary system coincident with a known Cepheid.

  9. Mixed-handedness advantages in episodic memory obtained under conditions of intentional learning extend to incidental learning.

    Science.gov (United States)

    Christman, Stephen D; Butler, Michael

    2011-10-01

    The existence of handedness differences in the retrieval of episodic memories is well-documented, but virtually all have been obtained under conditions of intentional learning. Two experiments are reported that extend the presence of such handedness differences to memory retrieval under conditions of incidental learning. Experiment 1 used Craik and Tulving's (1975) classic levels-of-processing paradigm and obtained handedness differences under incidental and intentional conditions of deep processing, but not under conditions of shallow incidental processing. Experiment 2 looked at incidental memory for distracter items from a recognition memory task and again found a mixed-handed advantage. Results are discussed in terms of the relation between interhemispheric interaction, levels of processing, and episodic memory retrieval. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. Effects of errorless skill learning in people with mild-to-moderate or severe dementia: a randomized controlled pilot study.

    NARCIS (Netherlands)

    Kessels, R.P.C.; Hensken, L.M.

    2009-01-01

    This pilot study examines whether learning without errors is advantageous compared to trial-and-error learning in people with dementia using a procedural task and a randomized case-control design. A sample of 60 people was recruited, consisting of 20 patients with severe dementia, 20 patients with

  11. Effects of errorless skill learning in people with mild-to-moderate or severe dementia: A randomized controlled pilot study

    NARCIS (Netherlands)

    Kessels, R.P.C.; Olde Hensken, L.M.G.

    2009-01-01

    This pilot study examines whether learning without errors is advantageous compared to trial-and-error learning in people with dementia using a procedural task and a randomized case-control design. A sample of 60 people was recruited, consisting of 20 patients with severe dementia, 20 patients with

  12. Machine-learning techniques for family demography: an application of random forests to the analysis of divorce determinants in Germany

    OpenAIRE

    Arpino, Bruno; Le Moglie, Marco; Mencarini, Letizia

    2018-01-01

    Demographers often analyze the determinants of life-course events with parametric regression-type approaches. Here, we present a class of nonparametric approaches, broadly defined as machine learning (ML) techniques, and discuss advantages and disadvantages of a popular type known as random forest. We argue that random forests can be useful either as a substitute, or a complement, to more standard parametric regression modeling. Our discussion of random forests is intuitive and...

  13. Examining the Conditions of Using an On-Line Dictionary to Learn Words and Comprehend Texts

    Science.gov (United States)

    Dilenschneider, Robert Francis

    2018-01-01

    This study investigated three look-up conditions for language learners to learn unknown target words and comprehend a reading passage when their attention is transferred away to an on-line dictionary. The research questions focused on how each look-up condition impacted the recall and recognition of word forms, word meanings, and passage…

  14. The effect of encoding conditions on learning in the prototype distortion task.

    Science.gov (United States)

    Lee, Jessica C; Livesey, Evan J

    2017-06-01

    The prototype distortion task demonstrates that it is possible to learn about a category of physically similar stimuli through mere observation. However, there have been few attempts to test whether different encoding conditions affect learning in this task. This study compared prototypicality gradients produced under incidental learning conditions in which participants performed a visual search task, with those produced under intentional learning conditions in which participants were required to memorize the stimuli. Experiment 1 showed that similar prototypicality gradients could be obtained for category endorsement and familiarity ratings, but also found (weaker) prototypicality gradients in the absence of exposure. In Experiments 2 and 3, memorization was found to strengthen prototypicality gradients in familiarity ratings in comparison to visual search, but there were no group differences in participants' ability to discriminate between novel and presented exemplars. Although the Search groups in Experiments 2 and 3 produced prototypicality gradients, they were no different in magnitude to those produced in the absence of stimulus exposure in Experiment 1, suggesting that incidental learning during visual search was not conducive to producing prototypicality gradients. This study suggests that learning in the prototype distortion task is not implicit in the sense of resulting automatically from exposure, is affected by the nature of encoding, and should be considered in light of potential learning-at-test effects.

  15. Learning-dependent plasticity in human auditory cortex during appetitive operant conditioning.

    Science.gov (United States)

    Puschmann, Sebastian; Brechmann, André; Thiel, Christiane M

    2013-11-01

    Animal experiments provide evidence that learning to associate an auditory stimulus with a reward causes representational changes in auditory cortex. However, most studies did not investigate the temporal formation of learning-dependent plasticity during the task but rather compared auditory cortex receptive fields before and after conditioning. We here present a functional magnetic resonance imaging study on learning-related plasticity in the human auditory cortex during operant appetitive conditioning. Participants had to learn to associate a specific category of frequency-modulated tones with a reward. Only participants who learned this association developed learning-dependent plasticity in left auditory cortex over the course of the experiment. No differential responses to reward predicting and nonreward predicting tones were found in auditory cortex in nonlearners. In addition, learners showed similar learning-induced differential responses to reward-predicting and nonreward-predicting tones in the ventral tegmental area and the nucleus accumbens, two core regions of the dopaminergic neurotransmitter system. This may indicate a dopaminergic influence on the formation of learning-dependent plasticity in auditory cortex, as it has been suggested by previous animal studies. Copyright © 2012 Wiley Periodicals, Inc.

  16. Enhancement of Lutein Production in Chlorella sorokiniana (Chorophyta by Improvement of Culture Conditions and Random Mutagenesis

    Directory of Open Access Journals (Sweden)

    Maria Angeles Vargas

    2011-09-01

    Full Text Available Chlorella sorokiniana has been selected for lutein production, after a screening of thirteen species of microalgae, since it showed both a high content in this carotenoid and a high growth rate. The effects of several nutritional and environmental factors on cell growth and lutein accumulation have been studied. Maximal specific growth rate and lutein content were attained at 690 µmol photons m−2 s−1, 28 °C, 2 mM NaCl, 40 mM nitrate and under mixotrophic conditions. In general, optimal conditions for the growth of this strain also lead to maximal lutein productivity. High lutein yielding mutants of C. sorokiniana have been obtained by random mutagenesis, using N-methyl-N′-nitro-nitrosoguanidine (MNNG as a mutagen and selecting mutants by their resistance to the inhibitors of the carotenogenic pathway nicotine and norflurazon. Among the mutants resistant to the herbicides, those exhibiting both high content in lutein and high growth rate were chosen. Several mutants exhibited higher contents in this carotenoid than the wild type, showing, in addition, either a similar or higher growth rate than the latter strain. The mutant MR-16 exhibited a 2.0-fold higher volumetric lutein content than that of the wild type, attaining values of 42.0 mg L−1 and mutants DMR-5 and DMR-8 attained a lutein cellular content of 7.0 mg g−1 dry weight. The high lutein yield exhibited by C. sorokiniana makes this microalga an excellent candidate for the production of this commercially interesting pigment.

  17. Background fluorescence estimation and vesicle segmentation in live cell imaging with conditional random fields.

    Science.gov (United States)

    Pécot, Thierry; Bouthemy, Patrick; Boulanger, Jérôme; Chessel, Anatole; Bardin, Sabine; Salamero, Jean; Kervrann, Charles

    2015-02-01

    Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in space and time at the subcellular level. In fluorescence microscopy imaging, the moving tagged structures of interest, such as vesicles, appear as bright spots over a static or nonstatic background. In this paper, we consider the problem of vesicle segmentation and time-varying background estimation at the cellular scale. The main idea is to formulate the joint segmentation-estimation problem in the general conditional random field framework. Furthermore, segmentation of vesicles and background estimation are alternatively performed by energy minimization using a min cut-max flow algorithm. The proposed approach relies on a detection measure computed from intensity contrasts between neighboring blocks in fluorescence microscopy images. This approach permits analysis of either 2D + time or 3D + time data. We demonstrate the performance of the so-called C-CRAFT through an experimental comparison with the state-of-the-art methods in fluorescence video-microscopy. We also use this method to characterize the spatial and temporal distribution of Rab6 transport carriers at the cell periphery for two different specific adhesion geometries.

  18. Language Recognition Using Latent Dynamic Conditional Random Field Model with Phonological Features

    Directory of Open Access Journals (Sweden)

    Sirinoot Boonsuk

    2014-01-01

    Full Text Available Spoken language recognition (SLR has been of increasing interest in multilingual speech recognition for identifying the languages of speech utterances. Most existing SLR approaches apply statistical modeling techniques with acoustic and phonotactic features. Among the popular approaches, the acoustic approach has become of greater interest than others because it does not require any prior language-specific knowledge. Previous research on the acoustic approach has shown less interest in applying linguistic knowledge; it was only used as supplementary features, while the current state-of-the-art system assumes independency among features. This paper proposes an SLR system based on the latent-dynamic conditional random field (LDCRF model using phonological features (PFs. We use PFs to represent acoustic characteristics and linguistic knowledge. The LDCRF model was employed to capture the dynamics of the PFs sequences for language classification. Baseline systems were conducted to evaluate the features and methods including Gaussian mixture model (GMM based systems using PFs, GMM using cepstral features, and the CRF model using PFs. Evaluated on the NIST LRE 2007 corpus, the proposed method showed an improvement over the baseline systems. Additionally, it showed comparable result with the acoustic system based on i-vector. This research demonstrates that utilizing PFs can enhance the performance.

  19. A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking.

    Directory of Open Access Journals (Sweden)

    Mohammad Javad Shafiee

    Full Text Available In this work, we introduce a deep-structured conditional random field (DS-CRF model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering.

  20. A Coupled Hidden Conditional Random Field Model for Simultaneous Face Clustering and Naming in Videos

    KAUST Repository

    Zhang, Yifan

    2016-08-18

    For face naming in TV series or movies, a typical way is using subtitles/script alignment to get the time stamps of the names, and tagging them to the faces. We study the problem of face naming in videos when subtitles are not available. To this end, we divide the problem into two tasks: face clustering which groups the faces depicting a certain person into a cluster, and name assignment which associates a name to each face. Each task is formulated as a structured prediction problem and modeled by a hidden conditional random field (HCRF) model. We argue that the two tasks are correlated problems whose outputs can provide prior knowledge of the target prediction for each other. The two HCRFs are coupled in a unified graphical model called coupled HCRF where the joint dependence of the cluster labels and face name association is naturally embedded in the correlation between the two HCRFs. We provide an effective algorithm to optimize the two HCRFs iteratively and the performance of the two tasks on real-world data set can be both improved.

  1. Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts

    Science.gov (United States)

    Maldague, Xavier

    2018-01-01

    The use of fiber reinforced materials such as randomly-oriented strands has grown in recent years, especially for manufacturing of aerospace composite structures. This growth is mainly due to their advantageous properties: they are lighter and more resistant to corrosion when compared to metals and are more easily shaped than continuous fiber composites. The resistance and stiffness of these materials are directly related to their fiber orientation. Thus, efficient approaches to assess their fiber orientation are in demand. In this paper, a non-destructive evaluation method is applied to assess the fiber orientation on laminates reinforced with randomly-oriented strands. More specifically, a method called pulsed thermal ellipsometry combined with an artificial neural network, a machine learning technique, is used in order to estimate the fiber orientation on the surface of inspected parts. Results showed that the method can be potentially used to inspect large areas with good accuracy and speed. PMID:29351240

  2. Machine Learning and Infrared Thermography for Fiber Orientation Assessment on Randomly-Oriented Strands Parts.

    Science.gov (United States)

    Fernandes, Henrique; Zhang, Hai; Figueiredo, Alisson; Malheiros, Fernando; Ignacio, Luis Henrique; Sfarra, Stefano; Ibarra-Castanedo, Clemente; Guimaraes, Gilmar; Maldague, Xavier

    2018-01-19

    The use of fiber reinforced materials such as randomly-oriented strands has grown in recent years, especially for manufacturing of aerospace composite structures. This growth is mainly due to their advantageous properties: they are lighter and more resistant to corrosion when compared to metals and are more easily shaped than continuous fiber composites. The resistance and stiffness of these materials are directly related to their fiber orientation. Thus, efficient approaches to assess their fiber orientation are in demand. In this paper, a non-destructive evaluation method is applied to assess the fiber orientation on laminates reinforced with randomly-oriented strands. More specifically, a method called pulsed thermal ellipsometry combined with an artificial neural network, a machine learning technique, is used in order to estimate the fiber orientation on the surface of inspected parts. Results showed that the method can be potentially used to inspect large areas with good accuracy and speed.

  3. Mental Imagery as Facilitator to Lexical Learning-Blocked and Random Trials

    Directory of Open Access Journals (Sweden)

    Subhash Bhatnagar

    2014-04-01

    Full Text Available Developing an effective treatment plan that promotes learning-generalization beyond treated stimuli remains a challenging task in language rehabilitation. Many specific treatments have been used to document therapeutic gains in learned lexical behaviors and now learning generalizations beyond practiced stimuli are being forged (Boyle, 2004 and Kiran & Thompson, 2003.Accordingly, generalization beyond practiced structures still remains an exciting therapeutic strategy. As major elements of cognitive processing, the perceptual representations embedded within mental imagery (MI, have long been recognized for their healing potential (Thomas, 2008, and training mindfulness. MI is also known to modulate the brain’s neural-circuitry in new learning (Davidson, 2000. It also acts as a mean to access memories and passes undistorted through mental resistances (Singer 1974. Purpose We integrated blocked and random presentations of MI with our treatment of anomia with three goals in mind: (1 to evaluate whether activation of the neural circuitry through controlled MI facilitated word finding skills; (2 to determine if the blocked or random modes of MI presentation facilitate learning equally or not; and, (3 to evaluate if the effects of evoked MI generalize to untrained lexical items. Subject The participating subject was a three-year post-onset, right-handed, 68-year old University-educated male with chronic aphasia secondary to a MRI confirmed large left temporal-parietal infarct in addition to an earlier left frontal infarct. These strokes resulted in moderately impaired comprehension and verbal expression. He made gains in both aspects of language following two years of SLP treatment. However, he continued to exhibit moderate to severe word finding (Goodglass & Kaplan, 1983. Methods We incorporated MI with random and blocked presentations in ABA format to explore the learning and generalization of trained mental representations that comprised of both

  4. Effects of Flipped Learning Using Online Materials in a Surgical Nursing Practicum: A Pilot Stratified Group-Randomized Trial.

    Science.gov (United States)

    Lee, Myung Kyung; Park, Bu Kyung

    2018-01-01

    This study examined the effect of flipped learning in comparison to traditional learning in a surgical nursing practicum. The subjects of this study were 102 nursing students in their third year of university who were scheduled to complete a clinical nursing practicum in an operating room or surgical unit. Participants were randomly assigned to either a flipped learning group (n = 51) or a traditional learning group (n = 51) for the 1-week, 45-hour clinical nursing practicum. The flipped-learning group completed independent e-learning lessons on surgical nursing and received a brief orientation prior to the commencement of the practicum, while the traditional-learning group received a face-to-face orientation and on-site instruction. After the completion of the practicum, both groups completed a case study and a conference. The student's self-efficacy, self-leadership, and problem-solving skills in clinical practice were measured both before and after the one-week surgical nursing practicum. Participants' independent goal setting and evaluation of beliefs and assumptions for the subscales of self-leadership and problem-solving skills were compared for the flipped learning group and the traditional learning group. The results showed greater improvement on these indicators for the flipped learning group in comparison to the traditional learning group. The flipped learning method might offer more effective e-learning opportunities in terms of self-leadership and problem-solving than the traditional learning method in surgical nursing practicums.

  5. Effect of e-learning program on risk assessment and pressure ulcer classification - A randomized study.

    Science.gov (United States)

    Bredesen, Ida Marie; Bjøro, Karen; Gunningberg, Lena; Hofoss, Dag

    2016-05-01

    Pressure ulcers (PUs) are a problem in health care. Staff competency is paramount to PU prevention. Education is essential to increase skills in pressure ulcer classification and risk assessment. Currently, no pressure ulcer learning programs are available in Norwegian. Develop and test an e-learning program for assessment of pressure ulcer risk and pressure ulcer classification. Forty-four nurses working in acute care hospital wards or nursing homes participated and were assigned randomly into two groups: an e-learning program group (intervention) and a traditional classroom lecture group (control). Data was collected immediately before and after training, and again after three months. The study was conducted at one nursing home and two hospitals between May and December 2012. Accuracy of risk assessment (five patient cases) and pressure ulcer classification (40 photos [normal skin, pressure ulcer categories I-IV] split in two sets) were measured by comparing nurse evaluations in each of the two groups to a pre-established standard based on ratings by experts in pressure ulcer classification and risk assessment. Inter-rater reliability was measured by exact percent agreement and multi-rater Fleiss kappa. A Mann-Whitney U test was used for continuous sum score variables. An e-learning program did not improve Braden subscale scoring. For pressure ulcer classification, however, the intervention group scored significantly higher than the control group on several of the categories in post-test immediately after training. However, after three months there were no significant differences in classification skills between the groups. An e-learning program appears to have a greater effect on the accuracy of pressure ulcer classification than classroom teaching in the short term. For proficiency in Braden scoring, no significant effect of educational methods on learning results was detected. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Mobile-Based Video Learning Outcomes in Clinical Nursing Skill Education: A Randomized Controlled Trial.

    Science.gov (United States)

    Lee, Nam-Ju; Chae, Sun-Mi; Kim, Haejin; Lee, Ji-Hye; Min, Hyojin Jennifer; Park, Da-Eun

    2016-01-01

    Mobile devices are a regular part of daily life among the younger generations. Thus, now is the time to apply mobile device use to nursing education. The purpose of this study was to identify the effects of a mobile-based video clip on learning motivation, competence, and class satisfaction in nursing students using a randomized controlled trial with a pretest and posttest design. A total of 71 nursing students participated in this study: 36 in the intervention group and 35 in the control group. A video clip of how to perform a urinary catheterization was developed, and the intervention group was able to download it to their own mobile devices for unlimited viewing throughout 1 week. All of the students participated in a practice laboratory to learn urinary catheterization and were blindly tested for their performance skills after participation in the laboratory. The intervention group showed significantly higher levels of learning motivation and class satisfaction than did the control. Of the fundamental nursing competencies, the intervention group was more confident in practicing catheterization than their counterparts. Our findings suggest that video clips using mobile devices are useful tools that educate student nurses on relevant clinical skills and improve learning outcomes.

  7. Human tracking in thermal images using adaptive particle filters with online random forest learning

    Science.gov (United States)

    Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

    2013-11-01

    This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

  8. Learning of Multimodal Representations With Random Walks on the Click Graph.

    Science.gov (United States)

    Wu, Fei; Lu, Xinyan; Song, Jun; Yan, Shuicheng; Zhang, Zhongfei Mark; Rui, Yong; Zhuang, Yueting

    2016-02-01

    In multimedia information retrieval, most classic approaches tend to represent different modalities of media in the same feature space. With the click data collected from the users' searching behavior, existing approaches take either one-to-one paired data (text-image pairs) or ranking examples (text-query-image and/or image-query-text ranking lists) as training examples, which do not make full use of the click data, particularly the implicit connections among the data objects. In this paper, we treat the click data as a large click graph, in which vertices are images/text queries and edges indicate the clicks between an image and a query. We consider learning a multimodal representation from the perspective of encoding the explicit/implicit relevance relationship between the vertices in the click graph. By minimizing both the truncated random walk loss as well as the distance between the learned representation of vertices and their corresponding deep neural network output, the proposed model which is named multimodal random walk neural network (MRW-NN) can be applied to not only learn robust representation of the existing multimodal data in the click graph, but also deal with the unseen queries and images to support cross-modal retrieval. We evaluate the latent representation learned by MRW-NN on a public large-scale click log data set Clickture and further show that MRW-NN achieves much better cross-modal retrieval performance on the unseen queries/images than the other state-of-the-art methods.

  9. E-learning as a complement to presential teaching of blindness prevention: a randomized clinical trial

    Directory of Open Access Journals (Sweden)

    Rodrigo Pessoa Cavalcanti Lira

    2013-02-01

    Full Text Available OBJECTIVE: To investigate if E-learning material improves the basal student knowledge level before attending the presential class of blindness prevention (BP and if helps to fix this information one-month after the class. METHODS: Fourth-year medical students were randomly assigned to have a presential class of BP (Traditional group = TG or to have a presential class of BP plus an additional E-learning material (E-learning group = ELG. This material was e-mailed one week before the presential class. The students were submitted to a multiple-choice test (with three options each with seven questions immediately before the presential class, immediately after the class, and one-month later. The three tests had the same questions; however, the answers options were distributed in different sequences. The primary outcome was immediate pretest score. The secondary outcomes were immediate posttest score and one-month posttest score. RESULTS: Among the 120 fourth-year medical students, a random sample of 34 students was assigned to the TG and 34 students was assigned to the ELG. The two groups showed similar immediate posttest score (TG=6.8 and ELG=6.9; P<.754, but the differences at the immediate pretest score (TG=3.6 and ELG=4.7; P<.001, and at the one-month posttest score, were significant (TG=6.1 and ELG=6.8; P<.001. CONCLUSIONS: The pretest and the one-month posttest results suggested that the E-learning material acts as an effective complementary tool of the presential class of blindness prevention.

  10. Effects of Mobile Augmented Reality Learning Compared to Textbook Learning on Medical Students: Randomized Controlled Pilot Study

    Science.gov (United States)

    2013-01-01

    Background By adding new levels of experience, mobile Augmented Reality (mAR) can significantly increase the attractiveness of mobile learning applications in medical education. Objective To compare the impact of the heightened realism of a self-developed mAR blended learning environment (mARble) on learners to textbook material, especially for ethically sensitive subjects such as forensic medicine, while taking into account basic psychological aspects (usability and higher level of emotional involvement) as well as learning outcomes (increased learning efficiency). Methods A prestudy was conducted based on a convenience sample of 10 third-year medical students. The initial emotional status was captured using the “Profile of Mood States” questionnaire (POMS, German variation); previous knowledge about forensic medicine was determined using a 10-item single-choice (SC) test. During the 30-minute learning period, the students were randomized into two groups: the first group consisted of pairs of students, each equipped with one iPhone with a preinstalled copy of mARble, while the second group was provided with textbook material. Subsequently, both groups were asked to once again complete the POMS questionnaire and SC test to measure changes in emotional state and knowledge gain. Usability as well as pragmatic and hedonic qualities of the learning material was captured using AttrakDiff2 questionnaires. Data evaluation was conducted anonymously. Descriptive statistics for the score in total and the subgroups were calculated before and after the intervention. The scores of both groups were tested against each other using paired and unpaired signed-rank tests. An item analysis was performed for the SC test to objectify difficulty and selectivity. Results Statistically significant, the mARble group (6/10) showed greater knowledge gain than the control group (4/10) (Wilcoxon z=2.232, P=.03). The item analysis of the SC test showed a difficulty of P=0.768 (s=0.09) and a

  11. Effects of mobile augmented reality learning compared to textbook learning on medical students: randomized controlled pilot study.

    Science.gov (United States)

    Albrecht, Urs-Vito; Folta-Schoofs, Kristian; Behrends, Marianne; von Jan, Ute

    2013-08-20

    By adding new levels of experience, mobile Augmented Reality (mAR) can significantly increase the attractiveness of mobile learning applications in medical education. To compare the impact of the heightened realism of a self-developed mAR blended learning environment (mARble) on learners to textbook material, especially for ethically sensitive subjects such as forensic medicine, while taking into account basic psychological aspects (usability and higher level of emotional involvement) as well as learning outcomes (increased learning efficiency). A prestudy was conducted based on a convenience sample of 10 third-year medical students. The initial emotional status was captured using the "Profile of Mood States" questionnaire (POMS, German variation); previous knowledge about forensic medicine was determined using a 10-item single-choice (SC) test. During the 30-minute learning period, the students were randomized into two groups: the first group consisted of pairs of students, each equipped with one iPhone with a preinstalled copy of mARble, while the second group was provided with textbook material. Subsequently, both groups were asked to once again complete the POMS questionnaire and SC test to measure changes in emotional state and knowledge gain. Usability as well as pragmatic and hedonic qualities of the learning material was captured using AttrakDiff2 questionnaires. Data evaluation was conducted anonymously. Descriptive statistics for the score in total and the subgroups were calculated before and after the intervention. The scores of both groups were tested against each other using paired and unpaired signed-rank tests. An item analysis was performed for the SC test to objectify difficulty and selectivity. Statistically significant, the mARble group (6/10) showed greater knowledge gain than the control group (4/10) (Wilcoxon z=2.232, P=.03). The item analysis of the SC test showed a difficulty of P=0.768 (s=0.09) and a selectivity of RPB=0.2. For m

  12. Dissociation of learned helplessness and fear conditioning in mice: a mouse model of depression.

    Directory of Open Access Journals (Sweden)

    Dominic Landgraf

    Full Text Available The state of being helpless is regarded as a central aspect of depression, and therefore the learned helplessness paradigm in rodents is commonly used as an animal model of depression. The term 'learned helplessness' refers to a deficit in escaping from an aversive situation after an animal is exposed to uncontrollable stress specifically, with a control/comparison group having been exposed to an equivalent amount of controllable stress. A key feature of learned helplessness is the transferability of helplessness to different situations, a phenomenon called 'trans-situationality'. However, most studies in mice use learned helplessness protocols in which training and testing occur in the same environment and with the same type of stressor. Consequently, failures to escape may reflect conditioned fear of a particular environment, not a general change of the helpless state of an animal. For mice, there is no established learned helplessness protocol that includes the trans-situationality feature. Here we describe a simple and reliable learned helplessness protocol for mice, in which training and testing are carried out in different environments and with different types of stressors. We show that with our protocol approximately 50% of mice develop learned helplessness that is not attributable to fear conditioning.

  13. Dissociation of learned helplessness and fear conditioning in mice: a mouse model of depression.

    Science.gov (United States)

    Landgraf, Dominic; Long, Jaimie; Der-Avakian, Andre; Streets, Margo; Welsh, David K

    2015-01-01

    The state of being helpless is regarded as a central aspect of depression, and therefore the learned helplessness paradigm in rodents is commonly used as an animal model of depression. The term 'learned helplessness' refers to a deficit in escaping from an aversive situation after an animal is exposed to uncontrollable stress specifically, with a control/comparison group having been exposed to an equivalent amount of controllable stress. A key feature of learned helplessness is the transferability of helplessness to different situations, a phenomenon called 'trans-situationality'. However, most studies in mice use learned helplessness protocols in which training and testing occur in the same environment and with the same type of stressor. Consequently, failures to escape may reflect conditioned fear of a particular environment, not a general change of the helpless state of an animal. For mice, there is no established learned helplessness protocol that includes the trans-situationality feature. Here we describe a simple and reliable learned helplessness protocol for mice, in which training and testing are carried out in different environments and with different types of stressors. We show that with our protocol approximately 50% of mice develop learned helplessness that is not attributable to fear conditioning.

  14. Cue competition in evaluative conditioning as a function of the learning process.

    Science.gov (United States)

    Kattner, Florian; Green, C Shawn

    2015-11-01

    Evaluative conditioning (EC) is the change in the valence of a stimulus resulting from pairings with an affective (unconditioned) stimulus (US). With some exceptions, previous work has indicated that this form of conditioning might be insensitive to cue competition effects such as blocking and overshadowing. Here we assessed whether the extent of cue competition in EC depends upon the type of contingency learning during conditioning. Specifically, we contrasted a learning task that biased participants toward cognitive/inferential learning (i.e., predicting the US) with a learning task that prevented prolonged introspection (i.e., a rapid response made to the US). In all cases, standard EC effects were observed, with the subjective liking of stimuli changed in the direction of the valence of the US. More importantly, when inferential learning was likely, larger EC effects occurred for isolated stimuli than for compounds (indicating overshadowing). No blocking effects on explicit evaluations were observed for either learning task. Contingency judgments and implicit evaluations, however, were sensitive to blocking, indicating that the absence of a blocking effect on explicit evaluations might be due to inferences that occur during testing.

  15. Acceptance of technology-enhanced learning for a theoretical radiological science course: a randomized controlled trial.

    Science.gov (United States)

    Nkenke, Emeka; Vairaktaris, Elefterios; Bauersachs, Anne; Eitner, Stephan; Budach, Alexander; Knipfer, Christoph; Stelzle, Florian

    2012-03-30

    Technology-enhanced learning (TEL) gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation) questionnaire for the evaluation of courses given at universities. Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired. However, technology-enhanced learning cannot completely replace

  16. Acceptance of technology-enhanced learning for a theoretical radiological science course: a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Nkenke Emeka

    2012-03-01

    Full Text Available Abstract Background Technology-enhanced learning (TEL gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. Methods 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation questionnaire for the evaluation of courses given at universities. Results Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. Conclusions It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired

  17. Acceptance of technology-enhanced learning for a theoretical radiological science course: a randomized controlled trial

    Science.gov (United States)

    2012-01-01

    Background Technology-enhanced learning (TEL) gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. Methods 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation) questionnaire for the evaluation of courses given at universities. Results Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. Conclusions It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired. However, technology

  18. Collaborative testing for key-term definitions under representative conditions: Efficiency costs and no learning benefits.

    Science.gov (United States)

    Wissman, Kathryn T; Rawson, Katherine A

    2018-01-01

    Students are expected to learn key-term definitions across many different grade levels and academic disciplines. Thus, investigating ways to promote understanding of key-term definitions is of critical importance for applied purposes. A recent survey showed that learners report engaging in collaborative practice testing when learning key-term definitions, with outcomes also shedding light on the way in which learners report engaging in collaborative testing in real-world contexts (Wissman & Rawson, 2016, Memory, 24, 223-239). However, no research has directly explored the effectiveness of engaging in collaborative testing under representative conditions. Accordingly, the current research evaluates the costs (with respect to efficiency) and the benefits (with respect to learning) of collaborative testing for key-term definitions under representative conditions. In three experiments (ns = 94, 74, 95), learners individually studied key-term definitions and then completed retrieval practice, which occurred either individually or collaboratively (in dyads). Two days later, all learners completed a final individual test. Results from Experiments 1-2 showed a cost (with respect to efficiency) and no benefit (with respect to learning) of engaging in collaborative testing for key-term definitions. Experiment 3 evaluated a theoretical explanation for why collaborative benefits do not emerge under representative conditions. Collectively, outcomes indicate that collaborative testing versus individual testing is less effective and less efficient when learning key-term definitions under representative conditions.

  19. Randomized trial of two e-learning programs for oral health students on secondary prevention of eating disorders.

    Science.gov (United States)

    DeBate, Rita D; Severson, Herbert H; Cragun, Deborah; Bleck, Jennifer; Gau, Jeff; Merrell, Laura; Cantwell, Carley; Christiansen, Steve; Koerber, Anne; Tomar, Scott L; Brown, Kelli McCormack; Tedesco, Lisa A; Hendricson, William; Taris, Mark

    2014-01-01

    The purpose of this study was to test whether an interactive, web-based training program is more effective than an existing, flat-text, e-learning program at improving oral health students' knowledge, motivation, and self-efficacy to address signs of disordered eating behaviors with patients. Eighteen oral health classes of dental and dental hygiene students were randomized to either the Intervention (interactive program; n=259) or Alternative (existing program; n=58) conditions. Hierarchical linear modeling assessed for posttest differences between groups while controlling for baseline measures. Improvement among Intervention participants was superior to those who completed the Alternative program for three of the six outcomes: benefits/barriers, self-efficacy, and skills-based knowledge (effect sizes ranging from 0.43 to 0.87). This study thus suggests that interactive training programs may be better than flat-text e-learning programs for improving the skills-based knowledge and self-efficacy necessary for behavior change.

  20. E-Learning in Urology: Implementation of the Learning and Teaching Platform CASUS® - Do Virtual Patients Lead to Improved Learning Outcomes? A Randomized Study among Students.

    Science.gov (United States)

    Schneider, Anna-Teresa; Albers, Peter; Müller-Mattheis, Volker

    2015-01-01

    E-learning is playing an increasing role in medical education, supporting a problem-based and practical oriented education without putting patients at risk and compensating for the decrease in instructor-centered teaching. Not much research has been done concerning learning effects and reaction on behalf of the students. We created computer-based cases for four important diagnoses in urology using the authoring system CASUS®. Fourth-year medical school students were randomized into two groups: (1) the CASUS® group, using the online cases for preparation, and (2) the book group, using a textbook. A multiple-choice test referring to the prepared topic had to be completed at the beginning of each lecture and the results were analyzed. Evaluation of the students concerning the acceptance of the program was done at the end of the semester. Members of the CASUS® group scored significantly higher with an average of 20% better test results than students using textbooks for preparation. Evaluation regarding the program showed a highly positive rating. Limitations include the small study population and the possibly biased test performance of the students. Computerized patient cases facilitate practice-oriented teaching and result in an interesting and engaging learning model with improved learning outcomes. © 2015 S. Karger AG, Basel.

  1. Progressive learning in endoscopy simulation training improves clinical performance: a blinded randomized trial.

    Science.gov (United States)

    Grover, Samir C; Scaffidi, Michael A; Khan, Rishad; Garg, Ankit; Al-Mazroui, Ahmed; Alomani, Tareq; Yu, Jeffrey J; Plener, Ian S; Al-Awamy, Mohamed; Yong, Elaine L; Cino, Maria; Ravindran, Nikila C; Zasowski, Mark; Grantcharov, Teodor P; Walsh, Catharine M

    2017-11-01

    A structured comprehensive curriculum (SCC) that uses simulation-based training (SBT) can improve clinical colonoscopy performance. This curriculum may be enhanced through the application of progressive learning, a training strategy centered on incrementally challenging learners. We aimed to determine whether a progressive learning-based curriculum (PLC) would lead to superior clinical performance compared with an SCC. This was a single-blinded randomized controlled trial conducted at a single academic center. Thirty-seven novice endoscopists were recruited and randomized to either a PLC (n = 18) or to an SCC (n = 19). The PLC comprised 6 hours of SBT, which progressed in complexity and difficulty. The SCC included 6 hours of SBT, with cases of random order of difficulty. Both groups received expert feedback and 4 hours of didactic teaching. Participants were assessed at baseline, immediately after training, and 4 to 6 weeks after training. The primary outcome was participants' performance during their first 2 clinical colonoscopies, as assessed by using the Joint Advisory Group Direct Observation of Procedural Skills assessment tool (JAG DOPS). Secondary outcomes were differences in endoscopic knowledge, technical and communication skills, and global performance in the simulated setting. The PLC group outperformed the SCC group during first and second clinical colonoscopies, measured by JAG DOPS (P PLC group had superior technical and communication skills and global performance in the simulated setting (P  .05). Our findings demonstrate the superiority of a PLC for endoscopic simulation, compared with an SCC. Challenging trainees progressively is a simple, theory-based approach to simulation whereby the performance of clinical colonoscopies can be improved. (Clinical trial registration number: NCT02000180.). Copyright © 2017 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

  2. Genetic Parameters for Body condition score, Body weigth, Milk yield and Fertility estimated using random regression models

    NARCIS (Netherlands)

    Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

    2003-01-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields

  3. Robust Machine Learning Variable Importance Analyses of Medical Conditions for Health Care Spending.

    Science.gov (United States)

    Rose, Sherri

    2018-03-11

    To propose nonparametric double robust machine learning in variable importance analyses of medical conditions for health spending. 2011-2012 Truven MarketScan database. I evaluate how much more, on average, commercially insured enrollees with each of 26 of the most prevalent medical conditions cost per year after controlling for demographics and other medical conditions. This is accomplished within the nonparametric targeted learning framework, which incorporates ensemble machine learning. Previous literature studying the impact of medical conditions on health care spending has almost exclusively focused on parametric risk adjustment; thus, I compare my approach to parametric regression. My results demonstrate that multiple sclerosis, congestive heart failure, severe cancers, major depression and bipolar disorders, and chronic hepatitis are the most costly medical conditions on average per individual. These findings differed from those obtained using parametric regression. The literature may be underestimating the spending contributions of several medical conditions, which is a potentially critical oversight. If current methods are not capturing the true incremental effect of medical conditions, undesirable incentives related to care may remain. Further work is needed to directly study these issues in the context of federal formulas. © Health Research and Educational Trust.

  4. Emotional eating and Pavlovian learning: does negative mood facilitate appetitive conditioning?

    Science.gov (United States)

    Bongers, Peggy; van den Akker, Karolien; Havermans, Remco; Jansen, Anita

    2015-06-01

    Emotional eating has been suggested to be a learned behaviour; more specifically, classical conditioning processes might be involved in its development. In the present study we investigated whether a negative mood facilitates appetitive conditioning and whether trait impulsivity influences this process. After undergoing either a negative or neutral mood induction, participants were subjected to a differential classical conditioning procedure, using neutral stimuli and appetizing food. Two initially neutral distinctive vases with flowers were (CS+) or were not (CS-) paired with chocolate mousse intake. We measured participants' expectancy and desire to eat (4 CS+ and 4 CS- trials), salivation response, and actual food intake. The BIS-11 was administered to assess trait impulsivity. In both mood conditions, participants showed a classically conditioned appetite. Unexpectedly, there was no evidence of facilitated appetitive learning in a negative mood with regard to expectancy, desire, salivation, or intake. However, immediately before the taste test, participants in the negative mood condition reported a stronger desire to eat in the CS+ compared to the CS- condition, while no such effect occurred in the neutral group. An effect of impulsivity was found with regard to food intake in the neutral mood condition: high-impulsive participants consumed less food when presented with the CS+ compared to the CS-, and also less than low-impulsive participants. An alternative pathway to appetitive conditioning with regard to emotions is that it is not the neutral stimuli, but the emotions themselves that become conditioned stimuli and elicit appetitive responses. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2014-11-01

    Full Text Available Tool condition monitoring (TCM plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM, hidden Markov model (HMM and radius basis function (RBF are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

  6. Learning to predict and control harmful events: chronic pain and conditioning.

    Science.gov (United States)

    Vlaeyen, Johan W S

    2015-04-01

    Pain is a biologically relevant signal and response to bodily threat, associated with the urge to restore the integrity of the body. Immediate protective responses include increased arousal, selective attention, escape, and facial expressions, followed by recuperative avoidance and safety-seeking behaviors. To facilitate early and effective protection against future bodily threat or injury, learning takes place rapidly. Learning is the observable change in behavior due to events in the internal and external environmental and includes nonassociative (habituation and sensitization) and associative learning (Pavlovian and operant conditioning). Once acquired, these knowledge representations remain stored in memory and may generalize to perceptually or functionally similar events. Moreover, these processes are not just a consequence of pain; they may directly influence pain perception. In contrast to the rapid acquisition of learned responses, their extinction is slow, fragile, context dependent and only occurs through inhibitory processes. Here, we review features of associative forms of learning in humans that contribute to pain, pain-related distress, and disability and discuss promising future directions. Although conditioning has a long and honorable history, a conditioning perspective still might open new windows on novel treatment modalities that facilitate the well-being of individuals with chronic pain.

  7. Test-potentiated learning: three independent replications, a disconfirmed hypothesis, and an unexpected boundary condition.

    Science.gov (United States)

    Wissman, Kathryn T; Rawson, Katherine A

    2018-04-01

    Arnold and McDermott [(2013). Test-potentiated learning: Distinguishing between direct and indirect effects of testing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 940-945] isolated the indirect effects of testing and concluded that encoding is enhanced to a greater extent following more versus fewer practice tests, referred to as test-potentiated learning. The current research provided further evidence for test-potentiated learning and evaluated the covert retrieval hypothesis as an alternative explanation for the observed effect. Learners initially studied foreign language word pairs and then completed either one or five practice tests before restudy occurred. Results of greatest interest concern performance on test trials following restudy for items that were not correctly recalled on the test trials that preceded restudy. Results replicate Arnold and McDermott (2013) by demonstrating that more versus fewer tests potentiate learning when trial time is limited. Results also provide strong evidence against the covert retrieval hypothesis concerning why the effect occurs (i.e., it does not reflect differential covert retrieval during pre-restudy trials). In addition, outcomes indicate that the magnitude of the test-potentiated learning effect decreases as trial length increases, revealing an unexpected boundary condition to test-potentiated learning.

  8. Learning of conditioned reflexes of the Wistar rat under intermittent action of low CO concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Zorn, H.

    1972-04-01

    The influence of an intermittent long-time exposure to a concentration of 150 ppm carbon monoxide on the ability to learn conditioned reflexes was investigated with Wistar rats. Half the 80 rats employed and divided into intelligence groups were exposed to this concentration at night five times for 8 hr weekly. The carboxyhemoglobin level in the blood of these animals increased to 7-13 percent. After an adequate interval for CO elimination, the rats exposed and the control animals were trained to develop a conditioned flight reflex. At a later date, the results were ascertained. With regard to the progress in learning this action, the CO-exposed animals showed a significant reduction in performance (longer learning time, more frequent deficient behavior, and inclination for stupor and anxious denial).

  9. Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

    Science.gov (United States)

    Chen, Tianle; Zeng, Donglin

    2015-01-01

    Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

  10. Dissociable Hippocampal and Amygdalar D1-like receptor contribution to Discriminated Pavlovian conditioned approach learning

    Science.gov (United States)

    Andrzejewski, Matthew E; Ryals, Curtis

    2016-01-01

    Pavlovian conditioning is an elementary form of reward-related behavioral adaptation. The mesolimbic dopamine system is widely considered to mediate critical aspects of reward-related learning. For example, initial acquisition of positively-reinforced operant behavior requires dopamine (DA) D1 receptor (D1R) activation in the basolateral amygdala (BLA), central nucleus of the amygdala (CeA), and the ventral subiculum (vSUB). However, the role of D1R activation in these areas on appetitive, non-drug-related, Pavlovian learning is not currently known. In separate experiments, microinfusions of the D1-like receptor antagonist SCH-23390 (3.0 nmol/0.5 μL per side) into the amygdala and subiculum preceded discriminated Pavlovian conditioned approach (dPCA) training sessions. D1-like antagonism in all three structures impaired the acquisition of discriminated approach, but had no effect on performance after conditioning was asymptotic. Moreover, dissociable effects of D1-like antagonism in the three structures on components of discriminated responding were obtained. Lastly, the lack of latent inhibition in drug-treated groups may elucidate the role of D1-like in reward-related Pavlovian conditioning. The present data suggest a role for the D1 receptors in the amygdala and hippocampus in learning the significance of conditional stimuli, but not in the expression of conditional responses. PMID:26632336

  11. Computer Mathematics Games and Conditions for Enhancing Young Children's Learning of Number Sense

    Science.gov (United States)

    Kermani, Hengameh

    2017-01-01

    Purpose: The present study was designed to examine whether mathematics computer games improved young children's learning of number sense under three different conditions: when used individually, with a peer, and with teacher facilitation. Methodology: This study utilized a mixed methodology, collecting both quantitative and qualitative data. A…

  12. Naïve and Robust: Class-Conditional Independence in Human Classification Learning

    Science.gov (United States)

    Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D.

    2018-01-01

    Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…

  13. Simultaneous and Sequential Feature Negative Discriminations: Elemental Learning and Occasion Setting in Human Pavlovian Conditioning

    Science.gov (United States)

    Baeyens, Frank; Vervliet, Bram; Vansteenwegen, Debora; Beckers, Tom; Hermans, Dirk; Eelen, Paul

    2004-01-01

    Using a conditioned suppression task, we investigated simultaneous (XA-/A+) vs. sequential (X [right arrow] A-/A+) Feature Negative (FN) discrimination learning in humans. We expected the simultaneous discrimination to result in X (or alternatively the XA configuration) becoming an inhibitor acting directly on the US, and the sequential…

  14. Blockade of Dopamine Activity in the Nucleus Accumbens Impairs Learning Extinction of Conditioned Fear

    Science.gov (United States)

    Holtzman-Assif, Orit; Laurent, Vincent; Westbrook, R. Frederick

    2010-01-01

    Three experiments used rats to investigate the role of dopamine activity in learning to inhibit conditioned fear responses (freezing) in extinction. In Experiment 1, rats systemically injected with the D2 dopamine antagonist, haloperidol, froze more across multiple extinction sessions and on a drug-free retention test than control rats. In…

  15. Hyperresponsiveness of the Neural Fear Network During Fear Conditioning and Extinction Learning in Male Cocaine Users

    NARCIS (Netherlands)

    Kaag, A.M.; Levar, N.; Woutersen, K.; Homberg, J.R.; Brink, W. van den; Reneman, L.; Wingen, G. van

    2016-01-01

    OBJECTIVE: The authors investigated whether cocaine use disorder is associated with abnormalities in the neural underpinnings of aversive conditioning and extinction learning, as these processes may play an important role in the development and persistence of drug abuse. METHOD: Forty male regular

  16. Individual differences in discriminatory fear learning under conditions of ambiguity: a vulnerability factor for anxiety disorders?

    NARCIS (Netherlands)

    Arnaudova, I.; Krypotos, A.M.; Effting, M.; Boddez, Y.; Kindt, M.; Beckers, T.

    2013-01-01

    Complex fear learning procedures might be better suited than the common differential fear-conditioning paradigm for detecting individual differences related to vulnerability for anxiety disorders. Two such procedures are the blocking procedure and the protection-from-overshadowing procedure. Their

  17. Learning to Promote Health at an Emergency Care Department: Identifying Expansive and Restrictive Conditions

    Science.gov (United States)

    Gustavsson, Maria; Ekberg, Kerstin

    2015-01-01

    This article reports on the findings of a planned workplace health promotion intervention, and the aim is to identify conditions that facilitated or restricted the learning to promote health at an emergency care department in a Swedish hospital. The study had a longitudinal design, with interviews before and after the intervention and follow-up…

  18. Learning-based encoding with soft assignment for age estimation under unconstrained imaging conditions

    NARCIS (Netherlands)

    Alnajar, F.; Shan, C.; Gevers, T.; Geusebroek, J.M.

    2012-01-01

    In this paper we propose to adopt a learning-based encoding method for age estimation under unconstrained imaging conditions. A similar approach [Cao et al., 2010] is applied to face recognition in real-life face images. However, the feature vectors are encoded in hard manner i.e. each feature

  19. Conditions for Contingent Instructors Engaged in the Scholarship of Teaching and Learning

    Science.gov (United States)

    Vander Kloet, Marie; Frake-Mistak, Mandy; McGinn, Michelle K.; Caldecott, Marion; Aspenlieder, Erin D.; Beres, Jacqueline L.; Fukuzawa, Sherry; Cassidy, Alice; Gill, Apryl

    2017-01-01

    An increasingly large number of courses in Canadian postsecondary institutions are taught by contingent instructors who hold full- or part-time positions for contractually limited time periods. Despite strong commitments to advancing teaching and learning, the labour and employment conditions for contingent instructors affect the incentives and…

  20. Gamma/hadron segregation for a ground based imaging atmospheric Cherenkov telescope using machine learning methods: Random Forest leads

    International Nuclear Information System (INIS)

    Sharma Mradul; Koul Maharaj Krishna; Mitra Abhas; Nayak Jitadeepa; Bose Smarajit

    2014-01-01

    A detailed case study of γ-hadron segregation for a ground based atmospheric Cherenkov telescope is presented. We have evaluated and compared various supervised machine learning methods such as the Random Forest method, Artificial Neural Network, Linear Discriminant method, Naive Bayes Classifiers, Support Vector Machines as well as the conventional dynamic supercut method by simulating triggering events with the Monte Carlo method and applied the results to a Cherenkov telescope. It is demonstrated that the Random Forest method is the most sensitive machine learning method for γ-hadron segregation. (research papers)

  1. Virtual reality training versus blended learning of laparoscopic cholecystectomy:a randomized controlled trial with laparoscopic novices

    OpenAIRE

    Nickel, Felix; Brzoska, Julia Anja; Gondan, Matthias; Rangnick, Henriette Maria; Chu, Jackson; Kenngott, Hannes Götz; Linke, Georg Richard; Kadmon, Martina; Fischer, Lars; Müller-Stich, Beat Peter

    2015-01-01

    Objective: This study compared virtual reality (VR) training with low cost blended learning (BL) in a structured training program. Background: Training of laparoscopic skills outside the operating room is mandatory to reduce operative times and risks. Methods: Laparoscopy-naïve medical students were randomized in two groups stratified for gender. The BL group (n = 42) used E-learning for laparoscopic cholecystectomy (LC) and practiced basic skills with box trainers. The VR group (n = 42) trai...

  2. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

    Science.gov (United States)

    Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

    2017-11-01

    Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  3. Resting heart rate variability predicts safety learning and fear extinction in an interoceptive fear conditioning paradigm.

    Directory of Open Access Journals (Sweden)

    Meike Pappens

    Full Text Available This study aimed to investigate whether interindividual differences in autonomic inhibitory control predict safety learning and fear extinction in an interoceptive fear conditioning paradigm. Data from a previously reported study (N = 40 were extended (N = 17 and re-analyzed to test whether healthy participants' resting heart rate variability (HRV - a proxy of cardiac vagal tone - predicts learning performance. The conditioned stimulus (CS was a slight sensation of breathlessness induced by a flow resistor, the unconditioned stimulus (US was an aversive short-lasting suffocation experience induced by a complete occlusion of the breathing circuitry. During acquisition, the paired group received 6 paired CS-US presentations; the control group received 6 explicitly unpaired CS-US presentations. In the extinction phase, both groups were exposed to 6 CS-only presentations. Measures included startle blink EMG, skin conductance responses (SCR and US-expectancy ratings. Resting HRV significantly predicted the startle blink EMG learning curves both during acquisition and extinction. In the unpaired group, higher levels of HRV at rest predicted safety learning to the CS during acquisition. In the paired group, higher levels of HRV were associated with better extinction. Our findings suggest that the strength or integrity of prefrontal inhibitory mechanisms involved in safety- and extinction learning can be indexed by HRV at rest.

  4. Individual differences in discriminatory fear learning under conditions of ambiguity: A vulnerability factor for anxiety disorders?

    Directory of Open Access Journals (Sweden)

    Inna eArnaudova

    2013-05-01

    Full Text Available Complex fear learning procedures might be better suited than the common differential fear conditioning paradigm for detecting individual differences related to vulnerability for anxiety disorders. Two such procedures are the blocking procedure and the protection-from-overshadowing procedure. Their comparison allows for the examination of discriminatory fear learning under conditions of ambiguity. The present study examined the role of individual differences in such discriminatory fear learning. We hypothesized that heightened trait anxiety would be related to a deficit in discriminatory fear learning. Participants gave US-expectancy ratings as an index for the threat value of individual CSs following blocking and protection-from-overshadowing training. The difference in threat value at test between the protected-from-overshadowing CS and the blocked CS was negatively correlated with scores on a self-report tension-stress scale that approximates facets of generalized anxiety disorder (DASS-S, but not with other individual difference variables. In addition, a behavioral test showed that only participants scoring high on the DASS-S avoided the protected-from-overshadowing CS. This observed deficit in discriminatory fear learning for participants with high levels of tension-stress might be an underlying mechanism for fear overgeneralization in diffuse anxiety disorders such as generalized anxiety disorder.

  5. High fat diet intake during pre and periadolescence impairs learning of a conditioned place preference in adulthood

    Directory of Open Access Journals (Sweden)

    Sanabria Federico

    2011-06-01

    Full Text Available Abstract Background Brain regions that mediate learning of a conditioned place preference (CPP undergo significant development in pre and periadolescence. Consuming a high fat (HF diet during this developmental period and into adulthood can lead to learning impairments in rodents. The present study tested whether HF diet intake, consumed only in pre and periadolescence, would be sufficient to cause impairments using a CPP procedure. Methods Rats were randomly assigned to consume a HF or a low fat (LF diet during postnatal days (PD 21-40 and were then placed back on a standard lab chow diet. A 20-day CPP procedure, using HF Cheetos® as the unconditioned stimulus (US, began either the next day (PD 41 or 40 days later (PD 81. A separate group of adult rats were given the HF diet for 20 days beginning on PD 61, and then immediately underwent the 20-day CPP procedure beginning on PD 81. Results Pre and periadolescent exposure to a LF diet or adult exposure to a HF diet did not interfere with the development of a HF food-induced CPP, as these groups exhibited robust preferences for the HF Cheetos® food-paired compartment. However, pre and periadolescent exposure to the HF diet impaired the development of a HF food-induced CPP regardless of whether it was assessed immediately or 40 days after the exposure to the HF diet, and despite showing increased consumption of the HF Cheetos® in conditioning. Conclusions Intake of a HF diet, consumed only in pre and periadolescence, has long-lasting effects on learning that persist into adulthood.

  6. Multi-Range Conditional Random Field for Classifying Railway Electrification System Objects Using Mobile Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Jaewook Jung

    2016-12-01

    Full Text Available Railways have been used as one of the most crucial means of transportation in public mobility and economic development. For safe railway operation, the electrification system in the railway infrastructure, which supplies electric power to trains, is an essential facility for stable train operation. Due to its important role, the electrification system needs to be rigorously and regularly inspected and managed. This paper presents a supervised learning method to classify Mobile Laser Scanning (MLS data into ten target classes representing overhead wires, movable brackets and poles, which are key objects in the electrification system. In general, the layout of the railway electrification system shows strong spatial regularity relations among object classes. The proposed classifier is developed based on Conditional Random Field (CRF, which characterizes not only labeling homogeneity at short range, but also the layout compatibility between different object classes at long range in the probabilistic graphical model. This multi-range CRF model consists of a unary term and three pairwise contextual terms. In order to gain computational efficiency, MLS point clouds are converted into a set of line segments to which the labeling process is applied. Support Vector Machine (SVM is used as a local classifier considering only node features for producing the unary potentials of the CRF model. As the short-range pairwise contextual term, the Potts model is applied to enforce a local smoothness in the short-range graph; while long-range pairwise potentials are designed to enhance the spatial regularities of both horizontal and vertical layouts among railway objects. We formulate two long-range pairwise potentials as the log posterior probability obtained by the naive Bayes classifier. The directional layout compatibilities are characterized in probability look-up tables, which represent the co-occurrence rate of spatial relations in the horizontal and vertical

  7. Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

    Energy Technology Data Exchange (ETDEWEB)

    Baraldi, Piero, E-mail: piero.baraldi@polimi.i [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Razavi-Far, Roozbeh [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Zio, Enrico [Dipartimento di Energia - Sezione Ingegneria Nucleare, Politecnico di Milano, via Ponzio 34/3, 20133 Milano (Italy); Ecole Centrale Paris-Supelec, Paris (France)

    2011-04-15

    An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.

  8. Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions

    International Nuclear Information System (INIS)

    Baraldi, Piero; Razavi-Far, Roozbeh; Zio, Enrico

    2011-01-01

    An important requirement for the practical implementation of empirical diagnostic systems is the capability of classifying transients in all plant operational conditions. The present paper proposes an approach based on an ensemble of classifiers for incrementally learning transients under different operational conditions. New classifiers are added to the ensemble where transients occurring in new operational conditions are not satisfactorily classified. The construction of the ensemble is made by bagging; the base classifier is a supervised Fuzzy C Means (FCM) classifier whose outcomes are combined by majority voting. The incremental learning procedure is applied to the identification of simulated transients in the feedwater system of a Boiling Water Reactor (BWR) under different reactor power levels.

  9. Semi-parametric estimation of random effects in a logistic regression model using conditional inference

    DEFF Research Database (Denmark)

    Petersen, Jørgen Holm

    2016-01-01

    This paper describes a new approach to the estimation in a logistic regression model with two crossed random effects where special interest is in estimating the variance of one of the effects while not making distributional assumptions about the other effect. A composite likelihood is studied...

  10. Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

    Science.gov (United States)

    Boissoneault, Jeff; Sevel, Landrew; Letzen, Janelle; Robinson, Michael; Staud, Roland

    2017-01-01

    Chronic musculoskeletal pain condition often shows poor correlations between tissue abnormalities and clinical pain. Therefore, classification of pain conditions like chronic low back pain, osteoarthritis, and fibromyalgia depends mostly on self report and less on objective findings like X-ray or magnetic resonance imaging (MRI) changes. However, recent advances in structural and functional brain imaging have identified brain abnormalities in chronic pain conditions that can be used for illness classification. Because the analysis of complex and multivariate brain imaging data is challenging, machine learning techniques have been increasingly utilized for this purpose. The goal of machine learning is to train specific classifiers to best identify variables of interest on brain MRIs (i.e., biomarkers). This report describes classification techniques capable of separating MRI-based brain biomarkers of chronic pain patients from healthy controls with high accuracy (70-92%) using machine learning, as well as critical scientific, practical, and ethical considerations related to their potential clinical application. Although self-report remains the gold standard for pain assessment, machine learning may aid in the classification of chronic pain disorders like chronic back pain and fibromyalgia as well as provide mechanistic information regarding their neural correlates.

  11. Predicting memory performance under conditions of proactive interference: immediate and delayed judgments of learning.

    Science.gov (United States)

    Wahlheim, Christopher N

    2011-07-01

    Four experiments examined the monitoring accuracy of immediate and delayed judgments of learning (JOLs) under conditions of proactive interference (PI). PI was produced using paired-associate learning tasks that conformed to variations of classic A-B, A-D paradigms. Results revealed that the relative monitoring accuracy of interference items was better for delayed than for immediate JOLs. However, delayed JOLs were overconfident for interference items, but not for items devoid of interference. Intrusions retrieved prior to delayed JOLs produced inflated predictions of performance. These results show that delayed JOLs enhance monitoring accuracy in PI situations, except when intrusions are mistaken for target responses.

  12. Multi-Label Learning via Random Label Selection for Protein Subcellular Multi-Locations Prediction.

    Science.gov (United States)

    Wang, Xiao; Li, Guo-Zheng

    2013-03-12

    Prediction of protein subcellular localization is an important but challenging problem, particularly when proteins may simultaneously exist at, or move between, two or more different subcellular location sites. Most of the existing protein subcellular localization methods are only used to deal with the single-location proteins. In the past few years, only a few methods have been proposed to tackle proteins with multiple locations. However, they only adopt a simple strategy, that is, transforming the multi-location proteins to multiple proteins with single location, which doesn't take correlations among different subcellular locations into account. In this paper, a novel method named RALS (multi-label learning via RAndom Label Selection), is proposed to learn from multi-location proteins in an effective and efficient way. Through five-fold cross validation test on a benchmark dataset, we demonstrate our proposed method with consideration of label correlations obviously outperforms the baseline BR method without consideration of label correlations, indicating correlations among different subcellular locations really exist and contribute to improvement of prediction performance. Experimental results on two benchmark datasets also show that our proposed methods achieve significantly higher performance than some other state-of-the-art methods in predicting subcellular multi-locations of proteins. The prediction web server is available at http://levis.tongji.edu.cn:8080/bioinfo/MLPred-Euk/ for the public usage.

  13. Does competition work as a motivating factor in e-learning? A randomized controlled trial.

    Directory of Open Access Journals (Sweden)

    Bjarne Skjødt Worm

    Full Text Available BACKGROUND AND AIMS: Examinations today are often computerized and the primary motivation and curriculum is often based on the examinations. This study aims to test if competition widgets in e-learning quiz modules improve post-test and follow-up test results and self-evaluation. The secondary aim is to evaluate improvements during the training period comparing test-results and number of tests taken. METHODS: Two groups were randomly assigned to either a quiz-module with competition widgets or a module without. Pre-, post- and follow up test-results were recorded. Time used within the modules was measured and students reported time studying. Students were able to choose questions from former examinations in the quiz-module. RESULTS: Students from the competing group were significantly better at both post-and follow-up-test and had a significantly better overall learning efficiency than those from the non-competing group. They were also significantly better at guessing their post-test results. CONCLUSION: Quiz modules with competition widgets motivate students to become more active during the module and stimulate better total efficiency. They also generate improved self-awareness regarding post-test-results.

  14. Virtual reality training versus blended learning of laparoscopic cholecystectomy: a randomized controlled trial with laparoscopic novices.

    Science.gov (United States)

    Nickel, Felix; Brzoska, Julia A; Gondan, Matthias; Rangnick, Henriette M; Chu, Jackson; Kenngott, Hannes G; Linke, Georg R; Kadmon, Martina; Fischer, Lars; Müller-Stich, Beat P

    2015-05-01

    This study compared virtual reality (VR) training with low cost-blended learning (BL) in a structured training program.Training of laparoscopic skills outside the operating room is mandatory to reduce operative times and risks.Laparoscopy-naïve medical students were randomized in 2 groups stratified for sex. The BL group (n = 42) used E-learning for laparoscopic cholecystectomy (LC) and practiced basic skills with box trainers. The VR group (n = 42) trained basic skills and LC on the LAP Mentor II (Simbionix, Cleveland, OH). Each group trained 3 × 4 hours followed by a knowledge test concerning LC. Blinded raters assessed the operative performance of cadaveric porcine LC using the Objective Structured Assessment of Technical Skills (OSATS). The LC was discontinued when it was not completed within 80 min. Students evaluated their training modality with questionnaires.The VR group completed the LC significantly faster and more often within 80 min than BL (45% v 21%, P = .02). The BL group scored higher than the VR group in the knowledge test (13.3 ± 1.3 vs 11.0 ± 1.7, P advantages of both approaches.

  15. 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.

  16. Learning basic life support (BLS) with tablet PCs in reciprocal learning at school: are videos superior to pictures? A randomized controlled trial.

    Science.gov (United States)

    Iserbyt, Peter; Charlier, Nathalie; Mols, Liesbet

    2014-06-01

    It is often assumed that animations (i.e., videos) will lead to higher learning compared to static media (i.e., pictures) because they provide a more realistic demonstration of the learning task. To investigate whether learning basic life support (BLS) and cardiopulmonary resuscitation (CPR) from video produce higher learning outcomes compared to pictures in reciprocal learning. A randomized controlled trial. A total of 128 students (mean age: 17 years) constituting eight intact classes from a secondary school learned BLS in reciprocal roles of doer and helper with tablet PCs. Student pairs in each class were randomized over a Picture and a Video group. In the Picture group, students learned BLS by means of pictures combined with written instructions. In the Video group, BLS was learned through videos with on-screen instructions. Informational equivalence was assured since instructions in both groups comprised exactly the same words. BLS assessment occurred unannounced, three weeks following intervention. Analysis of variance demonstrated no significant differences in chest compression depths between the Picture group (M=42 mm, 95% CI=40-45) and the Video group (M=39 mm, 95% CI=36-42). In the Picture group significantly higher percentages of chest compressions with correct hand placement were achieved (M=67%, CI=58-77) compared to the Video group (M=53%, CI=43-63), P=.03, η(p)(2)=.03. No other significant differences were found. Results do not support the assumption that videos are superior to pictures for learning BLS and CPR in reciprocal learning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  17. Random Sampling of Correlated Parameters – a Consistent Solution for Unfavourable Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Žerovnik, G., E-mail: gasper.zerovnik@ijs.si [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Trkov, A. [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); International Atomic Energy Agency, PO Box 100, A-1400 Vienna (Austria); Kodeli, I.A. [Jožef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana (Slovenia); Capote, R. [International Atomic Energy Agency, PO Box 100, A-1400 Vienna (Austria); Smith, D.L. [Argonne National Laboratory, 1710 Avenida del Mundo, Coronado, CA 92118-3073 (United States)

    2015-01-15

    Two methods for random sampling according to a multivariate lognormal distribution – the correlated sampling method and the method of transformation of correlation coefficients – are briefly presented. The methods are mathematically exact and enable consistent sampling of correlated inherently positive parameters with given information on the first two distribution moments. Furthermore, a weighted sampling method to accelerate the convergence of parameters with extremely large relative uncertainties is described. However, the method is efficient only for a limited number of correlated parameters.

  18. Tai Chi for Chronic Pain Conditions: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

    Science.gov (United States)

    Kong, Ling Jun; Lauche, Romy; Klose, Petra; Bu, Jiang Hui; Yang, Xiao Cun; Guo, Chao Qing; Dobos, Gustav; Cheng, Ying Wu

    2016-04-29

    Several studies reported that Tai Chi showed potential effects for chronic pain, but its role remains controversial. This review assessed the evidence regarding the effects of Tai Chi for chronic pain conditions. 18 randomized controlled trials were included in our review. The aggregated results have indicated that Tai Chi showed positive evidence on immediate relief of chronic pain from osteoarthritis (standardized mean difference [SMD], -0.54; 95% confidence intervals [CI], -0.77 to -0.30; P chronic pain from low back pain (SMD, -0.81; 95% CI, -1.11 to -0.52; P complementary and alternative medicine for chronic pain conditions.

  19. Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

    Science.gov (United States)

    Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

    2015-03-01

    The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

  20. The experiences of patients with Duchenne muscular dystrophy in facing and learning about their clinical conditions.

    Science.gov (United States)

    Fujino, Haruo; Iwata, Yuko; Saito, Toshio; Matsumura, Tsuyoshi; Fujimura, Harutoshi; Imura, Osamu

    2016-01-01

    Patients experience extreme difficulty when facing an intractable genetic disease. Herein, we examine the experiences of patients with Duchenne muscular dystrophy in facing and learning about their disease. A total of seven patients with Duchenne muscular dystrophy (age range: 20-48) participated. We conducted in-depth interviews with them about how they learned of their disease and how their feelings regarding the disease changed over time. Transcribed data were analysed using thematic analysis. The following themes emerged from this analysis: "experiences before receiving the diagnosis," "experiences when they learned of their condition and progression of the disease," "supports," and "desired explanations." Anxiety and worry were most pronounced when they had to transition to using wheelchairs or respirators due to disease progression; indeed, such transitions affect the patients psychological adjustment. In such times, support from significant others in their lives helped patients adjust.

  1. Learning to Dislike Chocolate: Conditioning Negative Attitudes toward Chocolate and Its Effect on Chocolate Consumption

    Directory of Open Access Journals (Sweden)

    Yan Wang

    2017-08-01

    Full Text Available Evaluative conditioning (EC procedures can be used to form and change attitudes toward a wide variety of objects. The current study examined the effects of a negative EC procedure on attitudes toward chocolate, and whether it influenced chocolate evaluation and consumption. Participants were randomly assigned to the experimental condition in which chocolate images were paired with negative stimuli, or the control condition in which chocolate images were randomly paired with positive stimuli (50% and negative stimuli (50%. Explicit and implicit attitudes toward chocolate images were collected. During an ostensible taste test, chocolate evaluation and consumption were assessed. Results revealed that compared to participants in the control condition, participants in the experimental condition showed more negative explicit and implicit attitudes toward chocolate images and evaluated chocolate more negatively during the taste test. However, chocolate consumption did not differ between experimental and control conditions. These findings suggest that pairing chocolate with negative stimuli can influence attitudes toward chocolate, though behavioral effects are absent. Intervention applications of EC provide avenues for future research and practices.

  2. Learning to Dislike Chocolate: Conditioning Negative Attitudes toward Chocolate and Its Effect on Chocolate Consumption.

    Science.gov (United States)

    Wang, Yan; Wang, Guosen; Zhang, Dingyuan; Wang, Lei; Cui, Xianghua; Zhu, Jinglei; Fang, Yuan

    2017-01-01

    Evaluative conditioning (EC) procedures can be used to form and change attitudes toward a wide variety of objects. The current study examined the effects of a negative EC procedure on attitudes toward chocolate, and whether it influenced chocolate evaluation and consumption. Participants were randomly assigned to the experimental condition in which chocolate images were paired with negative stimuli, or the control condition in which chocolate images were randomly paired with positive stimuli (50%) and negative stimuli (50%). Explicit and implicit attitudes toward chocolate images were collected. During an ostensible taste test, chocolate evaluation and consumption were assessed. Results revealed that compared to participants in the control condition, participants in the experimental condition showed more negative explicit and implicit attitudes toward chocolate images and evaluated chocolate more negatively during the taste test. However, chocolate consumption did not differ between experimental and control conditions. These findings suggest that pairing chocolate with negative stimuli can influence attitudes toward chocolate, though behavioral effects are absent. Intervention applications of EC provide avenues for future research and practices.

  3. The Effects of Math Video Games on Learning: A Randomized Evaluation Study with Innovative Impact Estimation Techniques. CRESST Report 841

    Science.gov (United States)

    Chung, Gregory K. W. K.; Choi, Kilchan; Baker, Eva L.; Cai, Li

    2014-01-01

    A large-scale randomized controlled trial tested the effects of researcher-developed learning games on a transfer measure of fractions knowledge. The measure contained items similar to standardized assessments. Thirty treatment and 29 control classrooms (~1500 students, 9 districts, 26 schools) participated in the study. Students in treatment…

  4. A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment.

    Science.gov (United States)

    Jiang, Hui; Hanna, Eriny; Gatto, Cheryl L; Page, Terry L; Bhuva, Bharat; Broadie, Kendal

    2016-03-01

    Aversive olfactory classical conditioning has been the standard method to assess Drosophila learning and memory behavior for decades, yet training and testing are conducted manually under exceedingly labor-intensive conditions. To overcome this severe limitation, a fully automated, inexpensive system has been developed, which allows accurate and efficient Pavlovian associative learning/memory analyses for high-throughput pharmacological and genetic studies. The automated system employs a linear actuator coupled to an odorant T-maze with airflow-mediated transfer of animals between training and testing stages. Odorant, airflow and electrical shock delivery are automatically administered and monitored during training trials. Control software allows operator-input variables to define parameters of Drosophila learning, short-term memory and long-term memory assays. The approach allows accurate learning/memory determinations with operational fail-safes. Automated learning indices (immediately post-training) and memory indices (after 24h) are comparable to traditional manual experiments, while minimizing experimenter involvement. The automated system provides vast improvements over labor-intensive manual approaches with no experimenter involvement required during either training or testing phases. It provides quality control tracking of airflow rates, odorant delivery and electrical shock treatments, and an expanded platform for high-throughput studies of combinational drug tests and genetic screens. The design uses inexpensive hardware and software for a total cost of ∼$500US, making it affordable to a wide range of investigators. This study demonstrates the design, construction and testing of a fully automated Drosophila olfactory classical association apparatus to provide low-labor, high-fidelity, quality-monitored, high-throughput and inexpensive learning and memory behavioral assays. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Remote-online case-based learning: A comparison of remote-online and face-to-face, case-based learning - a randomized controlled trial.

    Science.gov (United States)

    Nicklen, Peter; Keating, Jenny L; Paynter, Sophie; Storr, Michael; Maloney, Stephen

    2016-01-01

    Case-based learning (CBL) is an educational approach where students work in small, collaborative groups to solve problems. Computer assisted learning (CAL) is the implementation of computer technology in education. The purpose of this study was to compare the effects of a remote-online CBL (RO-CBL) with traditional face-to-face CBL on learning the outcomes of undergraduate physiotherapy students. Participants were randomized to either the control (face-to-face CBL) or to the CAL intervention (RO-CBL). The entire 3rd year physiotherapy cohort (n = 41) at Monash University, Victoria, Australia, were invited to participate in the randomized controlled trial. Outcomes included a postintervention multiple-choice test evaluating the knowledge gained from the CBL, a self-assessment of learning based on examinable learning objectives and student satisfaction with the CBL. In addition, a focus group was conducted investigating perceptions and responses to the online format. Thirty-eight students (control n = 19, intervention n = 19) participated in two CBL sessions and completed the outcome assessments. CBL median scores for the postintervention multiple-choice test were comparable (Wilcoxon rank sum P = 0.61) (median/10 [range] intervention group: 9 [8-10] control group: 10 [7-10]). Of the 15 examinable learning objectives, eight were significantly in favor of the control group, suggesting a greater perceived depth of learning. Eighty-four percent of students (16/19) disagreed with the statement "I enjoyed the method of CBL delivery." Key themes identified from the focus group included risks associated with the implementation of, challenges of communicating in, and flexibility offered, by web-based programs. RO-CBL appears to provide students with a comparable learning experience to traditional CBL. Procedural and infrastructure factors need to be addressed in future studies to counter student dissatisfaction and decreased perceived depth of learning.

  6. Blended-Learning Pain Neuroscience Education for People With Chronic Spinal Pain: Randomized Controlled Multicenter Trial.

    Science.gov (United States)

    Malfliet, Anneleen; Kregel, Jeroen; Meeus, Mira; Roussel, Nathalie; Danneels, Lieven; Cagnie, Barbara; Dolphens, Mieke; Nijs, Jo

    2018-05-01

    Available evidence favors the use of pain neuroscience education (PNE) in patients with chronic pain. However, PNE trials are often limited to small sample sizes and, despite the current digital era, the effects of blended-learning PNE (ie, the combination of online digital media with traditional educational methods) have not yet been investigated. The study objective was to examine whether blended-learning PNE is able to improve disability, catastrophizing, kinesiophobia, and illness perceptions. This study was a 2-center, triple-blind randomized controlled trial (participants, statistician, and outcome assessor were masked). The study took place at university hospitals in Ghent and Brussels, Belgium. Participants were 120 people with nonspecific chronic spinal pain (ie, chronic neck pain and low back pain). The intervention was 3 sessions of PNE or biomedically focused back/neck school education (addressing spinal anatomy and physiology). Measurements were self-report questionnaires (Pain Disability Index, Pain Catastrophizing Scale, Tampa Scale for Kinesiophobia, Illness Perception Questionnaire, and Pain Vigilance and Awareness Questionnaire). None of the treatment groups showed a significant change in the perceived disability (Pain Disability Index) due to pain (mean group difference posteducation: 1.84; 95% CI = -2.80 to 6.47). Significant interaction effects were seen for kinesiophobia and several subscales of the Illness Perception Questionnaire, including negative consequences, cyclical time line, and acute/chronic time line. In-depth analysis revealed that only in the PNE group were these outcomes significantly improved (9% to 17% improvement; 0.37 ≤ Cohen d ≥ 0.86). Effect sizes are small to moderate, which might raise the concern of limited clinical utility; however, changes in kinesiophobia exceed the minimal detectable difference. PNE should not be used as the sole treatment modality but should be combined with other treatment strategies

  7. Portraying mental illness and drug addiction as treatable health conditions: effects of a randomized experiment on stigma and discrimination.

    Science.gov (United States)

    McGinty, Emma E; Goldman, Howard H; Pescosolido, Bernice; Barry, Colleen L

    2015-02-01

    Despite significant advances in treatment, stigma and discrimination toward persons with mental illness and drug addiction have remained constant in past decades. Prior work suggests that portraying other stigmatized health conditions (i.e., HIV/AIDS) as treatable can improve public attitudes toward those affected. Our study compared the effects of vignettes portraying persons with untreated and symptomatic versus successfully treated and asymptomatic mental illness and drug addiction on several dimensions of public attitudes about these conditions. We conducted a survey-embedded randomized experiment using a national sample (N = 3940) from an online panel. Respondents were randomly assigned to read one of ten vignettes. Vignette one was a control vignette, vignettes 2-5 portrayed individuals with untreated schizophrenia, depression, prescription pain medication addiction and heroin addiction, and vignettes 6-10 portrayed successfully treated individuals with the same conditions. After reading the randomly assigned vignette, respondents answered questions about their attitudes related to mental illness or drug addiction. Portrayals of untreated and symptomatic schizophrenia, depression, and heroin addiction heightened negative public attitudes toward persons with mental illness and drug addiction. In contrast, portrayals of successfully treated schizophrenia, prescription painkiller addiction, and heroin addiction led to less desire for social distance, greater belief in the effectiveness of treatment, and less willingness to discriminate against persons with these conditions. Portrayal of persons with successfully treated mental illness and drug addiction is a promising strategy for reducing stigma and discrimination toward persons with these conditions and improving public perceptions of treatment effectiveness. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  9. Pedunculopontine tegmental nucleus lesions impair stimulus--reward learning in autoshaping and conditioned reinforcement paradigms.

    Science.gov (United States)

    Inglis, W L; Olmstead, M C; Robbins, T W

    2000-04-01

    The role of the pedunculopontine tegmental nucleus (PPTg) in stimulus-reward learning was assessed by testing the effects of PPTg lesions on performance in visual autoshaping and conditioned reinforcement (CRf) paradigms. Rats with PPTg lesions were unable to learn an association between a conditioned stimulus (CS) and a primary reward in either paradigm. In the autoshaping experiment, PPTg-lesioned rats approached the CS+ and CS- with equal frequency, and the latencies to respond to the two stimuli did not differ. PPTg lesions also disrupted discriminated approaches to an appetitive CS in the CRf paradigm and completely abolished the acquisition of responding with CRf. These data are discussed in the context of a possible cognitive function of the PPTg, particularly in terms of lesion-induced disruptions of attentional processes that are mediated by the thalamus.

  10. [Cooperative learning for improving healthy housing conditions in Bogota: a case study].

    Science.gov (United States)

    Torres-Parra, Camilo A; García-Ubaque, Juan C; García-Ubaque, César A

    2014-01-01

    This was a community-based effort at constructing an educational proposal orientated towards self-empowerment aimed at improving the target population's sanitary, housing and living conditions through cooperative learning. A constructivist approach was adopted based on a programme called "Habitat community manger". The project involved working with fifteen families living in the Mochuelo Bajo barrio in Ciudad Bolívar in Bogotá, Colombia, for identifying the most relevant sanitary aspects for improving their homes and proposing a methodology and organisation for an educational proposal. Twenty-one poor housing-related epidemiological indicators were identified which formed the basis for defining specific problems and establishing a methodology for designing an educational proposal. The course which emerged from the cooperative learning experience was designed to promote the community's skills and education regarding health aimed at improving households' living conditions and ensuring a healthy environment which would allow them to develop an immediate habitat ensuring their own welfare and dignity.

  11. Lateralized implicit sequence learning in uni- and bi-manual conditions.

    Science.gov (United States)

    Schmitz, Rémy; Pasquali, Antoine; Cleeremans, Axel; Peigneux, Philippe

    2013-02-01

    It has been proposed that the right hemisphere (RH) is better suited to acquire novel material whereas the left hemisphere (LH) is more able to process well-routinized information. Here, we ask whether this potential dissociation also manifests itself in an implicit learning task. Using a lateralized version of the serial reaction time task (SRT), we tested whether participants trained in a divided visual field condition primarily stimulating the RH would learn the implicit regularities embedded in sequential material faster than participants in a condition favoring LH processing. In the first study, half of participants were presented sequences in the left (vs. right) visual field, and had to respond using their ipsilateral hand (unimanual condition), hence making visuo-motor processing possible within the same hemisphere. Results showed successful implicit sequence learning, as indicated by increased reaction time for a transfer sequence in both hemispheric conditions and lack of conscious knowledge in a generation task. There was, however, no evidence of interhemispheric differences. In the second study, we hypothesized that a bimanual response version of the lateralized SRT, which requires interhemispheric communication and increases computational and cognitive processing loads, would favor RH-dependent visuospatial/attentional processes. In this bimanual condition, our results revealed a much higher transfer effect in the RH than in the LH condition, suggesting higher RH sensitivity to the processing of novel sequential material. This LH/RH difference was interpreted within the framework of the Novelty-Routinization model [Goldberg, E., & Costa, L. D. (1981). Hemisphere differences in the acquisition and use of descriptive systems. Brain and Language, 14(1), 144-173] and interhemispheric interactions in attentional processing [Banich, M. T. (1998). The missing link: the role of interhemispheric interaction in attentional processing. Brain and Cognition, 36

  12. Cocaine induces state-dependent learning of sexual conditioning in male Japanese quail.

    Science.gov (United States)

    Gill, Karin E; Rice, Beth Ann; Akins, Chana K

    2015-01-01

    State dependent learning effects have been widely studied in a variety of drugs of abuse. However, they have yet to be studied in relation to sexual motivation. The current study investigated state-dependent learning effects of cocaine in male Japanese quail (Coturnix japonica) using a sexual conditioning paradigm. Cocaine-induced state-dependent learning effects were investigated using a 2×2 factorial design with training state as one factor and test state as the other factor. During a 14-day training phase, male quail were injected once daily with 10mg/kg cocaine or saline and then placed in a test chamber after 15min. In the test chamber, sexual conditioning trials consisted of presentation of a light conditioned stimulus (CS) followed by sexual reinforcement. During the state dependent test, half of the birds received a shift in drug state from training to testing (Coc→Sal or Sal→Coc) while the other half remained in the same drug state (Coc→Coc or Sal→Sal). Results showed that male quail that were trained and tested in the same state (Coc→Coc or Sal→Sal) showed greater sexual conditioning than male quail that were trained and tested in different states (Sal→Coc) except when cocaine was administered chronically prior to the test (Coc→Sal). For the latter condition, sexual conditioning persisted from cocaine training to the saline test. The findings suggest that state dependent effects may alter sexual motivation and that repeated exposure to cocaine during sexual activity may increase sexual motivation which, in turn, may lead to high risk sexual activities. An alternative explanation for the findings is also discussed. Copyright © 2014 Elsevier Inc. All rights reserved.

  13. A multi-tier higher order Conditional Random Field for land cover classification of multi-temporal multi-spectral Landsat imagery

    CSIR Research Space (South Africa)

    Salmon, BP

    2015-07-01

    Full Text Available In this paper the authors present a 2-tier higher order Conditional Random Field which is used for land cover classification. The Conditional Random Field is based on probabilistic messages being passed along a graph to compute efficiently...

  14. The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables

    OpenAIRE

    Ambrogioni, Luca; Güçlü, Umut; van Gerven, Marcel A. J.; Maris, Eric

    2017-01-01

    This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex conditional densities as linear combinations of a family of kernel functions centered at a subset of training points. The weights are determined by the outer layer of a deep neural network, trained by minimizing the negative log likelihood. This generalizes the popular quantized softmax approach, which can be seen ...

  15. Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory

    Directory of Open Access Journals (Sweden)

    Stephan Koenig

    2017-05-01

    Full Text Available We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L, partial (P, and high (H shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L < P < H and the uncertainty of their prediction (L < P > H. During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention.

  16. Attentional Bias for Uncertain Cues of Shock in Human Fear Conditioning: Evidence for Attentional Learning Theory

    Science.gov (United States)

    Koenig, Stephan; Uengoer, Metin; Lachnit, Harald

    2017-01-01

    We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention. PMID:28588466

  17. Effectiveness of adolescent suicide prevention e-learning modules that aim to improve knowledge and self-confidence of gatekeepers: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Ghoncheh, Rezvan; Kerkhof, Ad J F M; Koot, Hans M

    2014-02-08

    Providing e-learning modules can be an effective strategy for enhancing gatekeepers' knowledge, self-confidence and skills in adolescent suicide prevention. The aim of this study was to test the effectiveness of an online training program called Mental Health Online which consists of eight short e-learning modules, each capturing an important aspect of the process of recognition, guidance and referral of suicidal adolescents (12-20 years). The primary outcomes of this study are participant's ratings on perceived knowledge, perceived self-confidence, and actual knowledge regarding adolescent suicidality. A randomized controlled trial will be carried out among 154 gatekeepers. After completing the first assessment (pre-test), participants will be randomly assigned to either the experimental group or the waitlist control group. One week after completing the first assessment the experimental group will have access to the website Mental Health Online containing the eight e-learning modules and additional information on adolescent suicide prevention. Participants in both conditions will be assessed 4 weeks after completing the first assessment (post-test), and 12 weeks after completing the post-test (follow-up). At post-test, participants from the experimental group are asked to complete an evaluation questionnaire on the modules. The waitlist control group will have access to the modules and additional information on the website after completing the follow-up assessment. Gatekeepers can benefit from e-learning modules on adolescent suicide prevention. This approach allows them to learn about this sensitive subject at their own pace and from any given location, as long as they have access to the Internet. Given the flexible nature of the program, each participant can compose his/her own training creating an instant customized course with the required steps in adolescent suicide prevention. Netherlands Trial Register NTR3625.

  18. Efficacy of Adolescent Suicide Prevention E-Learning Modules for Gatekeepers: A Randomized Controlled Trial.

    Science.gov (United States)

    Ghoncheh, Rezvan; Gould, Madelyn S; Twisk, Jos Wr; Kerkhof, Ad Jfm; Koot, Hans M

    2016-01-29

    Face-to-face gatekeeper training can be an effective strategy in the enhancement of gatekeepers' knowledge and self-efficacy in adolescent suicide prevention. However, barriers related to access (eg, time, resources) may hamper participation in face-to-face training sessions. The transition to a Web-based setting could address obstacles associated with face-to-face gatekeeper training. Although Web-based suicide prevention training targeting adolescents exists, so far no randomized controlled trials (RCTs) have been conducted to investigate their efficacy. This RCT study investigated the efficacy of a Web-based adolescent suicide prevention program entitled Mental Health Online, which aimed to improve the knowledge and self-confidence of gatekeepers working with adolescents (12-20 years old). The program consisted of 8 short e-learning modules each capturing an important aspect of the process of early recognition, guidance, and referral of suicidal adolescents, alongside additional information on the topic of (adolescent) suicide prevention. A total of 190 gatekeepers (ages 21 to 62 years) participated in this study and were randomized to either the experimental group or waitlist control group. The intervention was not masked. Participants from both groups completed 3 Web-based assessments (pretest, posttest, and 3-month follow-up). The outcome measures of this study were actual knowledge, and participants' ratings of perceived knowledge and perceived self-confidence using questionnaires developed specifically for this study. The actual knowledge, perceived knowledge, and perceived self-confidence of gatekeepers in the experimental group improved significantly compared to those in the waitlist control group at posttest, and the effects remained significant at 3-month follow-up. The overall effect sizes were 0.76, 1.20, and 1.02, respectively, across assessments. The findings of this study indicate that Web-based suicide prevention e-learning modules can be an

  19. Using Learning Decomposition and Bootstrapping with Randomization to Compare the Impact of Different Educational Interventions on Learning

    Science.gov (United States)

    Feng, Mingyu; Beck, Joseph E.; Heffernan, Neil T.

    2009-01-01

    A basic question of instructional interventions is how effective it is in promoting student learning. This paper presents a study to determine the relative efficacy of different instructional strategies by applying an educational data mining technique, learning decomposition. We use logistic regression to determine how much learning is caused by…

  20. Social media to supplement point-of-care ultrasound courses: the "sandwich e-learning" approach. A randomized trial.

    Science.gov (United States)

    Hempel, Dorothea; Haunhorst, Stephanie; Sinnathurai, Sivajini; Seibel, Armin; Recker, Florian; Heringer, Frank; Michels, Guido; Breitkreutz, Raoul

    2016-12-01

    Point-of-care ultrasound (POC-US) is gaining importance in almost all specialties. E-learning has been used to teach theoretical knowledge and pattern recognition. As social media are universally available, they can be utilized for educational purposes. We wanted to evaluate the utility of the sandwich e-learning approach defined as a pre-course e-learning and a post-course learning activity using Facebook after a one-day point-of-care ultrasound (POC-US) course and its effect on the retention of knowledge. A total of 62 medial students were recruited for this study and randomly assigned to one of four groups. All groups received an identical hands-on training and performed several tests during the study period. The hands-on training was performed in groups of five students per instructor with the students scanning each other. Group 1 had access to pre-course e-learning, but not to post-course e-learning. Instead of a pre-course e-learning, group 2 listened to presentations at the day of the course (classroom teaching) and had access to the post-course learning activity using Facebook. Group 3 had access to both pre- and post-course e-learning (sandwich e-learning) activities, while group 4 listened classroom presentations only (classroom teaching only). Therefore only groups 2 and 3 had access to post-course learning via Facebook by joining a secured group. Posts containing ultrasound pictures and videos were published to this group. The students were asked to "like" the posts to monitor attendance. Knowledge retention was assessed 6 weeks after the course. After 6 weeks, group 3 achieved comparable results when compared to group 2 (82.2 % + -8.2 vs. 84.3 + -8.02) (p = 0.3). Students who participated in the post-course activity were more satisfied with the overall course than students without post-course learning (5.5 vs. 5.3 on a range from 1 to 6). In this study, the sandwich e-learning approach led to equal rates of knowledge retention compared to

  1. A Correction of Random Incidence Absorption Coefficients for the Angular Distribution of Acoustic Energy under Measurement Conditions

    DEFF Research Database (Denmark)

    Jeong, Cheol-Ho

    2009-01-01

    Most acoustic measurements are based on an assumption of ideal conditions. One such ideal condition is a diffuse and reverberant field. In practice, a perfectly diffuse sound field cannot be achieved in a reverberation chamber. Uneven incident energy density under measurement conditions can cause...... discrepancies between the measured value and the theoretical random incidence absorption coefficient. Therefore the angular distribution of the incident acoustic energy onto an absorber sample should be taken into account. The angular distribution of the incident energy density was simulated using the beam...... tracing method for various room shapes and source positions. The averaged angular distribution is found to be similar to a Gaussian distribution. As a result, an angle-weighted absorption coefficient was proposed by considering the angular energy distribution to improve the agreement between...

  2. The design of instructional tools affects secondary school students' learning of cardiopulmonary resuscitation (CPR) in reciprocal peer learning: a randomized controlled trial.

    Science.gov (United States)

    Iserbyt, Peter; Byra, Mark

    2013-11-01

    Research investigating design effects of instructional tools for learning Basic Life Support (BLS) is almost non-existent. To demonstrate the design of instructional tools matter. The effect of spatial contiguity, a design principle stating that people learn more deeply when words and corresponding pictures are placed close (i.e., integrated) rather than far from each other on a page was investigated on task cards for learning Cardiopulmonary Resuscitation (CPR) during reciprocal peer learning. A randomized controlled trial. A total of 111 students (mean age: 13 years) constituting six intact classes learned BLS through reciprocal learning with task cards. Task cards combine a picture of the skill with written instructions about how to perform it. In each class, students were randomly assigned to the experimental group or the control. In the control, written instructions were placed under the picture on the task cards. In the experimental group, written instructions were placed close to the corresponding part of the picture on the task cards reflecting application of the spatial contiguity principle. One-way analysis of variance found significantly better performances in the experimental group for ventilation volumes (P=.03, ηp2=.10) and flow rates (P=.02, ηp2=.10). For chest compression depth, compression frequency, compressions with correct hand placement, and duty cycles no significant differences were found. This study shows that the design of instructional tools (i.e., task cards) affects student learning. Research-based design of learning tools can enhance BLS and CPR education. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  3. Game-based e-learning is more effective than a conventional instructional method: a randomized controlled trial with third-year medical students.

    Science.gov (United States)

    Boeker, Martin; Andel, Peter; Vach, Werner; Frankenschmidt, Alexander

    2013-01-01

    When compared with more traditional instructional methods, Game-based e-learning (GbEl) promises a higher motivation of learners by presenting contents in an interactive, rule-based and competitive way. Most recent systematic reviews and meta-analysis of studies on Game-based learning and GbEl in the medical professions have shown limited effects of these instructional methods. To compare the effectiveness on the learning outcome of a Game-based e-learning (GbEl) instruction with a conventional script-based instruction in the teaching of phase contrast microscopy urinalysis under routine training conditions of undergraduate medical students. A randomized controlled trial was conducted with 145 medical students in their third year of training in the Department of Urology at the University Medical Center Freiburg, Germany. 82 subjects where allocated for training with an educational adventure-game (GbEl group) and 69 subjects for conventional training with a written script-based approach (script group). Learning outcome was measured with a 34 item single choice test. Students' attitudes were collected by a questionnaire regarding fun with the training, motivation to continue the training and self-assessment of acquired knowledge. The students in the GbEl group achieved significantly better results in the cognitive knowledge test than the students in the script group: the mean score was 28.6 for the GbEl group and 26.0 for the script group of a total of 34.0 points with a Cohen's d effect size of 0.71 (ITT analysis). Attitudes towards the recent learning experience were significantly more positive with GbEl. Students reported to have more fun while learning with the game when compared to the script-based approach. Game-based e-learning is more effective than a script-based approach for the training of urinalysis in regard to cognitive learning outcome and has a high positive motivational impact on learning. Game-based e-learning can be used as an effective teaching

  4. Game-based e-learning is more effective than a conventional instructional method: a randomized controlled trial with third-year medical students.

    Directory of Open Access Journals (Sweden)

    Martin Boeker

    Full Text Available BACKGROUND: When compared with more traditional instructional methods, Game-based e-learning (GbEl promises a higher motivation of learners by presenting contents in an interactive, rule-based and competitive way. Most recent systematic reviews and meta-analysis of studies on Game-based learning and GbEl in the medical professions have shown limited effects of these instructional methods. OBJECTIVES: To compare the effectiveness on the learning outcome of a Game-based e-learning (GbEl instruction with a conventional script-based instruction in the teaching of phase contrast microscopy urinalysis under routine training conditions of undergraduate medical students. METHODS: A randomized controlled trial was conducted with 145 medical students in their third year of training in the Department of Urology at the University Medical Center Freiburg, Germany. 82 subjects where allocated for training with an educational adventure-game (GbEl group and 69 subjects for conventional training with a written script-based approach (script group. Learning outcome was measured with a 34 item single choice test. Students' attitudes were collected by a questionnaire regarding fun with the training, motivation to continue the training and self-assessment of acquired knowledge. RESULTS: The students in the GbEl group achieved significantly better results in the cognitive knowledge test than the students in the script group: the mean score was 28.6 for the GbEl group and 26.0 for the script group of a total of 34.0 points with a Cohen's d effect size of 0.71 (ITT analysis. Attitudes towards the recent learning experience were significantly more positive with GbEl. Students reported to have more fun while learning with the game when compared to the script-based approach. CONCLUSIONS: Game-based e-learning is more effective than a script-based approach for the training of urinalysis in regard to cognitive learning outcome and has a high positive motivational impact on

  5. Conditional Cooperativity in Toxin-Antitoxin Regulation Prevents Random Toxin Activation and Promotes Fast Translational Recovery

    DEFF Research Database (Denmark)

    Cataudella, Ilaria; Trusina, Ala; Sneppen, Kim

    2012-01-01

    system, relBE of Escherichia coli. We show that the model with the in vivo and in vitro established parameters reproduces experimentally observed response to nutritional stress. We further demonstrate that conditional cooperativity stabilizes the level of antitoxin in rapidly growing cells...

  6. Associative learning in humans--conditioning of sensory-evoked brain activity.

    Science.gov (United States)

    Skrandies, W; Jedynak, A

    2000-01-01

    A classical conditioning paradigm was employed in two experiments performed on 35 human volunteers. In nine subjects, the presentation of Landolt rings (conditioned stimuli, CS + ) was paired with an electric stimulus (unconditioned stimuli, UCS) applied to the left median nerve. Neutral visual control stimuli were full circles (CS -) that were not paired with the UCS. The skin conductance response (SCR) was determined in a time interval of 5 s after onset of the visual stimuli, and it was measured in the acquisition and test phase. Associative learning was reflected by a SCR occurring selectively with CS +. The same experiment was repeated with another group of 26 adults while electroencephalogram (EEG) was recorded from 30 electrodes. For each subject, mean evoked potentials were computed. In 13 of the subjects, a conditioning paradigm was followed while the other subjects served as the control group (non-contingent stimulation). There were somatosensory and visual brain activity evoked by the stimuli. Conditioned components were identified by computing cross-correlation between evoked somatosensory components and the averaged EEG. In the visual evoked brain activity, three components with mean latencies of 105.4, 183.2, and 360.3 ms were analyzed. Somatosensory stimuli were followed by major components that occurred at mean latencies of 48.8, 132.5, 219.7, 294.8, and 374.2 ms latency after the shock. All components were analyzed in terms of latency, field strength, and topographic characteristics, and were compared between groups and experimental conditions. Both visual and somatosensory brain activity was significantly affected by classical conditioning. Our data illustrate how associative learning affects the topography of brain electrical activity elicited by presentation of conditioned visual stimuli.

  7. Effects of OEF/OIF-Related Physical and Emotional Co-Morbidities on Associative Learning: Concurrent Delay and Trace Eyeblink Classical Conditioning

    Directory of Open Access Journals (Sweden)

    Regina E. McGlinchey

    2014-03-01

    Full Text Available This study examined the performance of veterans and active duty personnel who served in Operation Enduring Freedom and/or Operation Iraqi Freedom (OEF/OIF on a basic associative learning task. Eighty-eight individuals participated in this study. All received a comprehensive clinical evaluation to determine the presence and severity of posttraumatic stress disorder (PTSD and traumatic brain injury (TBI. The eyeblink conditioning task was composed of randomly intermixed delay and trace conditioned stimulus (CS and unconditioned stimulus (US pairs (acquisition followed by a series of CS only trials (extinction. Results revealed that those with a clinical diagnosis of PTSD or a diagnosis of PTSD with comorbid mTBI acquired delay and trace conditioned responses (CRs to levels and at rates similar to a deployed control group, thus suggesting intact basic associative learning. Differential extinction impairment was observed in the two clinical groups. Acquisition of CRs for both delay and trace conditioning, as well as extinction of trace CRs, was associated with alcoholic behavior across all participants. These findings help characterize the learning and memory function of individuals with PTSD and mTBI from OEF/OIF and raise the alarming possibility that the use of alcohol in this group may lead to more significant cognitive dysfunction.

  8. Food approach conditioning and discrimination learning using sound cues in benthic sharks.

    Science.gov (United States)

    Vila Pouca, Catarina; Brown, Culum

    2018-07-01

    The marine environment is filled with biotic and abiotic sounds. Some of these sounds predict important events that influence fitness while others are unimportant. Individuals can learn specific sound cues and 'soundscapes' and use them for vital activities such as foraging, predator avoidance, communication and orientation. Most research with sounds in elasmobranchs has focused on hearing thresholds and attractiveness to sound sources, but very little is known about their abilities to learn about sounds, especially in benthic species. Here we investigated if juvenile Port Jackson sharks could learn to associate a musical stimulus with a food reward, discriminate between two distinct musical stimuli, and whether individual personality traits were linked to cognitive performance. Five out of eight sharks were successfully conditioned to associate a jazz song with a food reward delivered in a specific corner of the tank. We observed repeatable individual differences in activity and boldness in all eight sharks, but these personality traits were not linked to the learning performance assays we examined. These sharks were later trained in a discrimination task, where they had to distinguish between the same jazz and a novel classical music song, and swim to opposite corners of the tank according to the stimulus played. The sharks' performance to the jazz stimulus declined to chance levels in the discrimination task. Interestingly, some sharks developed a strong side bias to the right, which in some cases was not the correct side for the jazz stimulus.

  9. Cluster-randomized trial demonstrating impact on academic achievement of elementary social-emotional learning.

    Science.gov (United States)

    Schonfeld, David J; Adams, Ryan E; Fredstrom, Bridget K; Weissberg, Roger P; Gilman, Richard; Voyce, Charlene; Tomlin, Ricarda; Speese-Linehan, Dee

    2015-09-01

    This study evaluated the results of a social and emotional learning (SEL) program on academic achievement among students attending a large, urban, high-risk school district. Using a cluster-randomized design, 24 elementary schools were assigned to receive either the intervention curriculum (Promoting Alternative Thinking Strategies, or PATHS) or a curriculum that delivered few if any SEL topics (i.e., the control group). In addition to state mastery test scores, demographic data, school attendance, and dosage information were obtained from 705 students who remained in the same group from the 3rd to the 6th grade. Analyses of odds ratios revealed that students enrolled in the intervention schools demonstrated higher levels of basic proficiency in reading, writing, and math at some grade levels. Although these between-groups differences held for race/ethnicity, gender, and socioeconomic status, significant within-group differences also were noted across these variables. Collectively, these findings indicated that social development instruction may be a promising approach to promote acquisition of academic proficiency, especially among youth attending high-risk school settings. Implications of these findings with respect to SEL programs conclude the article. (c) 2015 APA, all rights reserved).

  10. Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

    Science.gov (United States)

    Parsa, Maryam; Panda, Priyadarshini; Sen, Shreyas; Roy, Kaushik

    2017-07-01

    Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for analysis of the large pool of data generated by the wearable devices. Deep learning is among the promising methods for analyzing such data for healthcare applications and disease diagnosis. However, the conventional deep neural networks are computationally intensive and it is impractical to use them in real-time diagnosis with low-powered on-body devices. We propose Staged Inference using Conditional Deep Learning (SICDL), as an energy efficient approach for creating healthcare monitoring systems. For smart diagnostics, we observe that all diagnoses are not equally challenging. The proposed approach thus decomposes the diagnoses into preliminary analysis (such as healthy vs unhealthy) and detailed analysis (such as identifying the specific type of cardio disease). The preliminary diagnosis is conducted real-time with a low complexity neural network realized on the resource-constrained on-body device. The detailed diagnosis requires a larger network that is implemented remotely in cloud and is conditionally activated only for detailed diagnosis (unhealthy individuals). We evaluated the proposed approach using available physiological sensor data from Physionet databases, and achieved 38% energy reduction in comparison to the conventional deep learning approach.

  11. Peer-Led Self-Management of General Medical Conditions for Patients With Serious Mental Illnesses: A Randomized Trial.

    Science.gov (United States)

    Druss, Benjamin G; Singh, Manasvini; von Esenwein, Silke A; Glick, Gretl E; Tapscott, Stephanie; Tucker, Sherry Jenkins; Lally, Cathy A; Sterling, Evelina W

    2018-02-01

    Individuals with serious mental illnesses have high rates of general medical comorbidity and challenges in managing these conditions. A growing workforce of certified peer specialists is available to help these individuals more effectively manage their health and health care. However, few studies have examined the effectiveness of peer-led programs for self-management of general medical conditions for this population. This randomized study enrolled 400 participants with a serious mental illness and one or more chronic general medical conditions across three community mental health clinics. Participants were randomly assigned to the Health and Recovery Peer (HARP) program, a self-management program for general medical conditions led by certified peer specialists (N=198), or to usual care (N=202). Assessments were conducted at baseline and three and six months. At six months, participants in the intervention group demonstrated a significant differential improvement in the primary study outcome, health-related quality of life. Specifically, compared with the usual care group, intervention participants had greater improvement in the Short-Form Health Survey physical component summary (an increase of 2.7 versus 1.4 points, p=.046) and mental component summary (4.6 versus 2.5 points, p=.039). Significantly greater six-month improvements in mental health recovery were seen for the intervention group (p=.02), but no other between-group differences in secondary outcome measures were significant. The HARP program was associated with improved physical health- and mental health-related quality of life among individuals with serious mental illness and comorbid general medical conditions, suggesting the potential benefits of more widespread dissemination of peer-led disease self-management in this population.

  12. Learning an operant conditioning task differentially induces gliogenesis in the medial prefrontal cortex and neurogenesis in the hippocampus.

    Directory of Open Access Journals (Sweden)

    Maximiliano Rapanelli

    Full Text Available Circuit modification associated with learning and memory involves multiple events, including the addition and remotion of newborn cells trough adulthood. Adult neurogenesis and gliogenesis were mainly described in models of voluntary exercise, enriched environments, spatial learning and memory task; nevertheless, it is unknown whether it is a common mechanism among different learning paradigms, like reward dependent tasks. Therefore, we evaluated cell proliferation, neurogenesis, astrogliogenesis, survival and neuronal maturation in the medial prefrontal cortex (mPFC and the hippocampus (HIPP during learning an operant conditioning task. This was performed by using endogenous markers of cell proliferation, and a bromodeoxiuridine (BrdU injection schedule in two different phases of learning. Learning an operant conditioning is divided in two phases: a first phase when animals were considered incompletely trained (IT, animals that were learning the task when they performed between 50% and 65% of the responses, and a second phase when animals were considered trained (Tr, animals that completely learned the task when they reached 100% of the responses with a latency time lower than 5 seconds. We found that learning an operant conditioning task promoted cell proliferation in both phases of learning in the mPFC and HIPP. Additionally, the results presented showed that astrogliogenesis was induced in the medial prefrontal cortex (mPFC in both phases, however, the first phase promoted survival of these new born astrocytes. On the other hand, an increased number of new born immature neurons was observed in the HIPP only in the first phase of learning, whereas, decreased values were observed in the second phase. Finally, we found that neuronal maturation was induced only during the first phase. This study shows for the first time that learning a reward-dependent task, like the operant conditioning, promotes neurogenesis, astrogliogenesis, survival and

  13. Cupping therapy versus acupuncture for pain-related conditions: a systematic review of randomized controlled trials and trial sequential analysis.

    Science.gov (United States)

    Zhang, Ya-Jing; Cao, Hui-Juan; Li, Xin-Lin; Yang, Xiao-Ying; Lai, Bao-Yong; Yang, Guo-Yang; Liu, Jian-Ping

    2017-01-01

    Both cupping therapy and acupuncture have been used in China for a long time, and their target indications are pain-related conditions. There is no systematic review comparing the effectiveness of these two therapies. To compare the beneficial effectiveness and safety between cupping therapy and acupuncture for pain-related conditions to provide evidence for clinical practice. Protocol of this review was registered in PROSPERO (CRD42016050986). We conducted literature search from six electronic databases until 31st March 2017. We included randomized trials comparing cupping therapy with acupuncture on pain-related conditions. Methodological quality of the included studies was evaluated by risk of bias tool. Mean difference, risk ratio, risk difference and their 95% confidence interval were used to report the estimate effect of the pooled results through meta-analysis or the results from each individual study. Trial sequential analysis (TSA) was applied to adjust random errors and calculate the sample size. Twenty-three randomized trials with 2845 participants were included covering 12 pain-related conditions. All included studies were of poor methodological quality. Three meta-analyses were conducted, which showed similar clinical beneficial effects of cupping therapy and acupuncture for the rate of symptom improvement in cervical spondylosis (RR 1.13, 95% CI 1.01 to 1.26; n = 646), lateral femoral cutaneous neuritis (RR 1.10, 95% CI 1.00 to 1.22; n = 102) and scapulohumeral periarthritis (RR 1.31, 95% CI 1.15 to 1.51; n = 208). Results from other outcomes (such as visual analogue and numerical rating scale) in each study also showed no statistical significant difference between these two therapies for all included pain-related conditions. The results of TSA for cervical spondylosis demonstrated that the current available data have not reached a powerful conclusion. No serious adverse events related to cupping therapy or acupuncture was found in included

  14. Evaluation and visualization of multiaxial fatigue behavior under random non-proportional loading condition

    Directory of Open Access Journals (Sweden)

    Takahiro Morishita

    2017-07-01

    Full Text Available In cyclic multiaxial stress/strain condition under nonproportional loading in which principal direction of stress/strain are changed in a cycle, it becomes difficult to analyze stress/strain ranges because of complexity of multiaxial stress/strain states depending on time in cycles. In order to evaluate stress/strain simply and suitably under non-proportional loading, Itoh and Sakane have proposed a method called as IS-method and a strain parameter for life evaluation under non-proportional loading NP. In the method, 6-components of stress/strain are converted to an equivalent stress/strain indicating the amplitude and the direction of principal stress/strain as a function of time as well as an intensity of loading nonproportionality fNP. Based on IS-method, the authors also have developed a tool which enables to analyze multiaxial stress/strain condition with the nonproportionality of loading history and evaluate failure life under nonproportional multiaxial loading. The tool indicates the analyzed results on monitor and users can understand visually not only variation of the stress/strain conditions but also non-proportionality during the cycle, which helps the design of material strength.

  15. Visual perceptual learning by operant conditioning training follows rules of contingency

    Science.gov (United States)

    Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo

    2015-01-01

    Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning. PMID:26028984

  16. Visual perceptual learning by operant conditioning training follows rules of contingency.

    Science.gov (United States)

    Kim, Dongho; Seitz, Aaron R; Watanabe, Takeo

    2015-01-01

    Visual perceptual learning (VPL) can occur as a result of a repetitive stimulus-reward pairing in the absence of any task. This suggests that rules that guide Conditioning, such as stimulus-reward contingency (e.g. that stimulus predicts the likelihood of reward), may also guide the formation of VPL. To address this question, we trained subjects with an operant conditioning task in which there were contingencies between the response to one of three orientations and the presence of reward. Results showed that VPL only occurred for positive contingencies, but not for neutral or negative contingencies. These results suggest that the formation of VPL is influenced by similar rules that guide the process of Conditioning.

  17. Effects of mobile phone-based app learning compared to computer-based web learning on nursing students: pilot randomized controlled trial.

    Science.gov (United States)

    Lee, Myung Kyung

    2015-04-01

    This study aimed to determine the effect of mobile-based discussion versus computer-based discussion on self-directed learning readiness, academic motivation, learner-interface interaction, and flow state. This randomized controlled trial was conducted at one university. Eighty-six nursing students who were able to use a computer, had home Internet access, and used a mobile phone were recruited. Participants were randomly assigned to either the mobile phone app-based discussion group (n = 45) or a computer web-based discussion group (n = 41). The effect was measured at before and after an online discussion via self-reported surveys that addressed academic motivation, self-directed learning readiness, time distortion, learner-learner interaction, learner-interface interaction, and flow state. The change in extrinsic motivation on identified regulation in the academic motivation (p = 0.011) as well as independence and ability to use basic study (p = 0.047) and positive orientation to the future in self-directed learning readiness (p = 0.021) from pre-intervention to post-intervention was significantly more positive in the mobile phone app-based group compared to the computer web-based discussion group. Interaction between learner and interface (p = 0.002), having clear goals (p = 0.012), and giving and receiving unambiguous feedback (p = 0.049) in flow state was significantly higher in the mobile phone app-based discussion group than it was in the computer web-based discussion group at post-test. The mobile phone might offer more valuable learning opportunities for discussion teaching and learning methods in terms of self-directed learning readiness, academic motivation, learner-interface interaction, and the flow state of the learning process compared to the computer.

  18. A new system to reduce formaldehyde levels improves safety conditions during gross veterinary anatomy learning.

    Science.gov (United States)

    Nacher, Víctor; Llombart, Cristina; Carretero, Ana; Navarro, Marc; Ysern, Pere; Calero, Sebastián; Fígols, Enric; Ruberte, Jesús

    2007-01-01

    Dissection is a very useful method of learning veterinary anatomy. However, formaldehyde, which is widely used to preserve cadavers, is an irritant, and it has recently been classified as a carcinogen. In 1997, the Instituto Nacional de Seguridad e Higiene en el Trabajo [National Institute of Workplace Security and Hygiene] found that the levels of formaldehyde in our dissection room were above the threshold limit values. Unfortunately, no optimal substitute for formaldehyde is currently available. Therefore, we designed a new ventilation system that combines slow propulsion of fresh air from above the dissection table and rapid aspiration of polluted air from the perimeter. Formaldehyde measurements performed in 2004, after the introduction of this new system into our dissection laboratory, showed a dramatic reduction (about tenfold, or 0.03 ppm). A suitable propelling/aspirating air system successfully reduces the concentration of formaldehyde in the dissection room, significantly improving safety conditions for students, instructors, and technical staff during gross anatomy learning.

  19. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew

    2017-12-06

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  20. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew; McCabe, Matthew

    2017-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  1. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2018-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

  2. Mental skills training effectively minimizes operative performance deterioration under stressful conditions: Results of a randomized controlled study.

    Science.gov (United States)

    Anton, N E; Beane, J; Yurco, A M; Howley, L D; Bean, E; Myers, E M; Stefanidis, D

    2018-02-01

    Stress can negatively impact surgical performance, but mental skills may help. We hypothesized that a comprehensive mental skills curriculum (MSC) would minimize resident performance deterioration under stress. Twenty-four residents were stratified then randomized to receive mental skills and FLS training (MSC group), or only FLS training (control group). Laparoscopic suturing skill was assessed on a live porcine model with and without external stressors. Outcomes were compared with t-tests. Twenty-three residents completed the study. The groups were similar at baseline. There were no differences in suturing at posttest or transfer test under normal conditions. Both groups experienced significantly decreased performance when stress was applied, but the MSC group significantly outperformed controls under stress. This MSC enabled residents to perform significantly better than controls in the simulated OR under unexpected stressful conditions. These findings support the use of psychological skills as an integral part of a surgical resident training. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. eLearning course may shorten the duration of mechanical restraint among psychiatric inpatients: a cluster-randomized trial.

    Science.gov (United States)

    Kontio, Raija; Pitkänen, Anneli; Joffe, Grigori; Katajisto, Jouko; Välimäki, Maritta

    2014-10-01

    The management of psychiatric inpatients exhibiting severely disturbed and aggressive behaviour is an important educational topic. Well structured, IT-based educational programmes (eLearning) often ensure quality and may make training more affordable and accessible. The aim of this study was to explore the impact of an eLearning course for personnel on the rates and duration of seclusion and mechanical restraint among psychiatric inpatients. In a cluster-randomized intervention trial, the nursing personnel on 10 wards were randomly assigned to eLearning (intervention) or training-as-usual (control) groups. The eLearning course comprised six modules with specific topics (legal and ethical issues, behaviour-related factors, therapeutic relationship and self-awareness, teamwork and integrating knowledge with practice) and specific learning methods. The rates (incidents per 1000 occupied bed days) and durations of the coercion incidents were examined before and after the course. A total of 1283 coercion incidents (1143 seclusions [89%] and 140 incidents involving the use of mechanical restraints [11%]) were recorded on the study wards during the data collection period. On the intervention wards, there were no statistically significant changes in the rates of seclusion and mechanical restraint. However, the duration of incidents involving mechanical restraints shortened from 36.0 to 4.0 h (median) (P eLearning course, the duration of incidents involving the use of mechanical restraints decreased. However, more studies are needed to ensure that the content of the course focuses on the most important factors associated with the seclusion-related elements. The eLearning course deserves further development and further studies. The duration of coercion incidents merits attention in future research.

  4. Statistical Learning Framework with Adaptive Retraining for Condition-Based Maintenance

    International Nuclear Information System (INIS)

    An, Sang Ha; Chang, Soon Heung; Heo, Gyun Young; Seo, Ho Joon; Kim, Su Young

    2009-01-01

    As systems become more complex and more critical in our daily lives, the need for the maintenance based on the reliable monitoring and diagnosis has become more apparent. However, in reality, the general opinion has been that 'maintenance is a necessary evil' or 'nothing can be done to improve maintenance costs'. Perhaps these were true statements twenty years ago when many of the diagnostic technologies were not fully developed. The developments of microprocessor or computer based instrumentation that can be used to monitor the operating condition of plant equipment, machinery and systems have provided the means to manage the maintenance operation. They have provided the means to reduce or eliminate unnecessary repairs, prevent catastrophic machine failures and reduce the negative impact of the maintenance operation on the profitability of manufacturing and production plants. Condition-based maintenance (CBM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. Most of the statistical learning techniques are only valid as long as the physics of a system does not change. If any significant change such as the replacement of a component or equipment occurs in the system, the statistical learning model should be re-trained or re-developed to adapt the new system. In this research, authors will propose a statistical learning framework which can be applicable for various CBMs, and the concept of the adaptive retraining technique will be described to support the execution of the framework so that the monitoring system does not need to be re-developed or re-trained even though there are any significant changes in the system or component

  5. A Randomized Controlled Trial Determining Variances in Ostomy Skin Conditions and the Economic Impact (ADVOCATE Trial).

    Science.gov (United States)

    Colwell, Janice C; Pittman, Joyce; Raizman, Rose; Salvadalena, Ginger

    To compare ostomy-related costs and incidence of peristomal skin complications (PSCs) for ceramide-infused ostomy skin barriers and control skin barriers. The ADVOCATE trial is a multi-centered randomized controlled trial, and double-blinded international study with an adaptive design. The sample comprised 153 adults from 25 sites from the United States, Canada, and Europe. Participants were seen in hospital and outpatient care settings. Data were collected by investigators at each site during face-to-face visits and during telephone check-in calls between visits. Cost of care data were collected using a questionnaire developed specifically for the study. The peristomal skin was assessed using the Ostomy Skin Tool. Health-related quality of life was measured using the SF-12v2. Patient-reported outcomes were collected using a patient-centered study-specific questionnaire. Cost of care was analyzed via analysis of covariance comparing total cost of care for 12 weeks between the 2 groups. The incidence of PSC was analyzed via Barnard's exact test comparing the incidence of PSCs between the control and treatment groups. Tertiary outcomes were exploratory in nature and not statistically powered. Use of the ceramide-infused barrier significantly reduced stoma-related cost of care over a 12-week period, resulting in a $36.46 decrease in cost (14% relative decrease). The adjusted average costs were $223.73 in the treatment group and $260.19 in the control group (P = .017). The overall incidence of PSCs in the study was 47.7%; PSC incidence was 40.5% for the treatment group versus 55.4% for controls (P = .069, 95% confidence interval of the difference: -1.2 to 30.4). Significantly more participants using the ceramide-infused skin barrier were "very satisfied" with barrier performance (75% vs 55%; P = .033), prevention of leakage (63% vs 38%; P < .01), and prevention of itching (53% vs 31%; P = .016). General postoperative improvement in health-related quality of life was

  6. Incorrect modeling of the failure process of minimally repaired systems under random conditions: The effect on the maintenance costs

    International Nuclear Information System (INIS)

    Pulcini, Gianpaolo

    2015-01-01

    This note investigates the effect of the incorrect modeling of the failure process of minimally repaired systems that operates under random environmental conditions on the costs of a periodic replacement maintenance. The motivation of this paper is given by a recently published paper, where a wrong formulation of the expected cost for unit time under a periodic replacement policy is obtained. This wrong formulation is due to the incorrect assumption that the intensity function of minimally repaired systems that operate under random conditions has the same functional form as the failure rate of the first failure time. This produced an incorrect optimization of the replacement maintenance. Thus, in this note the conceptual differences between the intensity function and the failure rate of the first failure time are first highlighted. Then, the correct expressions of the expected cost and of the optimal replacement period are provided. Finally, a real application is used to measure how severe can be the economical consequences caused by the incorrect modeling of the failure process.

  7. From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

    Science.gov (United States)

    Grossberg, Stephen

    2015-09-24

    This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

  8. Dutch care innovation units in elderly care: A qualitative study into students' perspectives and workplace conditions for learning.

    Science.gov (United States)

    Snoeren, Miranda; Volbeda, Patricia; Niessen, Theo J H; Abma, Tineke A

    2016-03-01

    To promote workplace learning for staff as well as students, a partnership was formed between a residential care organisation for older people and several nursing faculties in the Netherlands. This partnership took the form of two care innovation units; wards where qualified staff, students and nurse teachers collaborate to integrate care, education, innovation and research. In this article, the care innovation units as learning environments are studied from a student perspective to deepen understandings concerning the conditions that facilitate learning. A secondary analysis of focus groups, held with 216 nursing students over a period of five years, revealed that students are satisfied about the units' learning potential, which is formed by various inter-related and self-reinforcing affordances: co-constructive learning and working, challenging situations and activities, being given responsibility and independence, and supportive and recognisable learning structures. Time constraints had a negative impact on the units' learning potential. It is concluded that the learning potential of the care innovation units was enhanced by realising certain conditions, like learning structures and activities. The learning potential was also influenced, however, by the non-controllable and dynamic interaction of various elements within the context. Suggestions for practice and further research are offered. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. A randomized trial of heart failure disease management in skilled nursing facilities (SNF Connect): Lessons learned.

    Science.gov (United States)

    Daddato, Andrea; Wald, Heidi L; Horney, Carolyn; Fairclough, Diane L; Leister, Erin C; Coors, Marilyn; Capell, Warren H; Boxer, Rebecca S

    2017-06-01

    Conducting clinical trials in skilled nursing facilities is particularly challenging. This manuscript describes facility and patient recruitment challenges and solutions for clinical research in skilled nursing facilities. Lessons learned from the SNF Connect Trial, a randomized trial of a heart failure disease management versus usual care for patients with heart failure receiving post-acute care in skilled nursing facilities, are discussed. Description of the trial design and barriers to facility and patient recruitment along with regulatory issues are presented. The recruitment of Denver-metro skilled nursing facilities was facilitated by key stakeholders of the skilled nursing facilities community. However, there were still a number of barriers to facility recruitment including leadership turnover, varying policies regarding research, fear of litigation and of an increased workload. Engagement of facilities was facilitated by their strong interest in reducing hospital readmissions, marketing potential to hospitals, and heart failure management education for their staff. Recruitment of patients proved difficult and there were few facilitators. Identified patient recruitment challenges included patients being unaware of their heart failure diagnosis, patients overwhelmed with their illness and care, and frequently there was no available proxy for cognitively impaired patients. Flexibility in changing the recruitment approach and targeting skilled nursing facilities with higher rates of admissions helped to overcome some barriers. Recruitment of skilled nursing facilities and patients in skilled nursing facilities for clinical trials is challenging. Strategies to attract both facilities and patients are warranted. These include aligning study goals with facility incentives and flexible recruitment protocols to work with patients in "transition crisis."

  10. The influence of a learning object with virtual simulation for dentistry: A randomized controlled trial.

    Science.gov (United States)

    Tubelo, Rodrigo Alves; Branco, Vicente Leitune Castelo; Dahmer, Alessandra; Samuel, Susana Maria Werner; Collares, Fabrício Mezzomo

    2016-01-01

    The study aimed to evaluate the influence of virtual learning object (VLO) in the theoretical knowledge and skill practice of undergraduate dentistry students as it relates to zinc phosphate cement (ZPC). Only students enrolled in the dentistry course the course were included in the trial. Forty-six students received a live class regarding ZPC and were randomized by electronic sorting into the following 4 groups: VLO Immediate (GIVLOn=9), VLO longitudinal (GLVLOn=15) and two control groups without VLO (GICn=9 and GLCn=13). The immediate groups had access to VLO or a book for 20 min before the ability assessment, whereas the longitudinal groups had access to VLO or a book for 15 days. A pre- and posttest on theoretical knowledge and two laboratory skill tests, evaluated by blinded examiners, were performed regarding zinc phosphate cement manipulation in all groups. The students who used the VLO obtained better results in all the tests performed than the control students. The theoretical posttest showed a significant difference between the longitudinal groups, GLC (6.0 ± 1.15) and GLVLO (7.33 ± 1.43). The lower film thickness presented with a significant difference in the VLO groups: (GIC 25 ± 9.3) and GIVLO (16.24 ± 5.17); GLC (50 ± 27.08) and GLVLO (22.5±9.65). The higher setting time occurred in the VLO groups, and the immediate group showed a significant difference (GIC 896 ± 218.90) and GIVLO (1138.5 ± 177.95). The ZPC manipulated by the students who used the VLO had better mechanical properties in the laboratory tests. Therefore, the groups that used the VLO had clinical handling skills superior to its controls and greater retention of knowledge after 15 days. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  11. Clinical Inertia in a Randomized Trial of Telemedicine-Based Chronic Disease Management: Lessons Learned.

    Science.gov (United States)

    Barton, Anna Beth; Okorodudu, Daniel E; Bosworth, Hayden B; Crowley, Matthew J

    2018-01-17

    Treatment nonadherence and clinical inertia perpetuate poor cardiovascular disease (CVD) risk factor control. Telemedicine interventions may counter both treatment nonadherence and clinical inertia. We explored why a telemedicine intervention designed to reduce treatment nonadherence and clinical inertia did not improve CVD risk factor control, despite enhancing treatment adherence versus usual care. In this analysis of a randomized trial, we studied recipients of the 12-month telemedicine intervention. This intervention comprised two nurse-administered components: (1) monthly self-management education targeting improved treatment adherence; and (2) quarterly medication management facilitation designed to support treatment intensification by primary care (thereby reducing clinical inertia). For each medication management facilitation encounter, we ascertained whether patients met treatment goals, and if not, whether primary care recommended treatment intensification following the encounter. We assessed disease control associated with encounters, where intensification was/was not recommended. We examined 455 encounters across 182 intervention recipients (100% African Americans with type 2 diabetes). Even after accounting for valid reasons for deferring intensification (e.g., treatment nonadherence), intensification was not recommended in 67.5% of encounters in which hemoglobin A1c was above goal, 72.5% in which systolic blood pressure was above goal, and 73.9% in which low-density lipoprotein cholesterol was above goal. In each disease state, treatment intensification was more likely with poorer control. Despite enhancing treatment adherence, this intervention was unsuccessful in countering clinical inertia, likely explaining its lack of effect on CVD risk factors. We identify several lessons learned that may benefit investigators and healthcare systems.

  12. Structural Conditions for Collaboration and Learning in Innovation Networks: Using an Innovation System Performance Lens to Analyse Agricultural Knowledge Systems

    NARCIS (Netherlands)

    Hermans, F.; Klerkx, L.W.A.; Roep, D.

    2015-01-01

    Purpose: We investigate how the structural conditions of eight different European agricultural innovation systems can facilitate or hinder collaboration and social learning in multidisciplinary innovation networks. Methodology: We have adapted the Innovation System Failure Matrix to investigate the

  13. The role of conditioning, learning and dopamine in sexual behavior: a narrative review of animal and human studies

    NARCIS (Netherlands)

    Brom, Mirte; Both, Stephanie; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip

    2014-01-01

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of

  14. The role of conditioning, learning and dopamine in sexual behavior : A narrative review of animal and human studies

    NARCIS (Netherlands)

    Brom, M.; Both, S.; Laan, E.; Everaerd, W.; Spinhoven, P.

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of

  15. Learning-induced Dependence of Neuronal Activity in Primary Motor Cortex on Motor Task Condition.

    Science.gov (United States)

    Cai, X; Shimansky, Y; He, Jiping

    2005-01-01

    A brain-computer interface (BCI) system such as a cortically controlled robotic arm must have a capacity of adjusting its function to a specific environmental condition. We studied this capacity in non-human primates based on chronic multi-electrode recording from the primary motor cortex of a monkey during the animal's performance of a center-out 3D reaching task and adaptation to external force perturbations. The main condition-related feature of motor cortical activity observed before the onset of force perturbation was a phasic raise of activity immediately before the perturbation onset. This feature was observed during a series of perturbation trials, but were absent under no perturbations. After adaptation has been completed, it usually was taking the subject only one trial to recognize a change in the condition to switch the neuronal activity accordingly. These condition-dependent features of neuronal activity can be used by a BCI for recognizing a change in the environmental condition and making corresponding adjustments, which requires that the BCI-based control system possess such advanced properties of the neural motor control system as capacity to learn and adapt.

  16. Social makes smart: rearing conditions affect learning and social behaviour in jumping spiders.

    Science.gov (United States)

    Liedtke, J; Schneider, J M

    2017-11-01

    There is a long-standing debate as to whether social or physical environmental aspects drive the evolution and development of cognitive abilities. Surprisingly few studies make use of developmental plasticity to compare the effects of these two domains during development on behaviour later in life. Here, we present rearing effects on the development of learning abilities and social behaviour in the jumping spider Marpissa muscosa. These spiders are ideally suited for this purpose because they possess the ability to learn and can be reared in groups but also in isolation without added stress. This is a critical but rarely met requirement for experimentally varying the social environment to test its impact on cognition. We split broods of spiders and reared them either in a physically or in a socially enriched environment. A third group kept under completely deprived conditions served as a 'no-enrichment' control. We tested the spiders' learning abilities by using a modified T-maze. Social behaviour was investigated by confronting spiders with their own mirror image. Results show that spiders reared in groups outperform their conspecifics from the control, i.e. 'no-enrichment', group in both tasks. Physical enrichment did not lead to such an increased performance. We therefore tentatively suggest that growing up in contact with conspecifics induces the development of cognitive abilities in this species.

  17. Effectiveness of applying flipped learning to clinical nursing practicums for nursing students in Korea: A randomized controlled trial.

    Science.gov (United States)

    Kim, Hyun Sook; Kim, Mi Young; Cho, Mi-Kyoung; Jang, Sun Joo

    2017-10-01

    The purpose of this study was to develop flipped learning models for clinical practicums and compare their effectiveness regarding learner motivation toward learning, satisfaction, and confidence in performing core nursing skills among undergraduate nursing students in Korea. This study was a randomized clinical trial designed to compare the effectiveness of 2 flipped learning models. Data were collected for 3 days from October 21 to 23, 2015 before the clinical practicum was implemented and for 2 weeks from October 26 to December 18, 2015 during the practicum period. The confidence of the students in performing core nursing skills was likely to increase after they engaged in the clinical practicum in both study groups. However, while learner confidence and motivation were not affected by the type of flipped learning, learner satisfaction did differ between the 2 groups. The findings indicate that applying flipped learning allows students to conduct individualized learning with a diversity of clinical cases at their own level of understanding and at their own pace before they participate in real-world practicums. © 2017 John Wiley & Sons Australia, Ltd.

  18. Open-closed-loop iterative learning control for a class of nonlinear systems with random data dropouts

    Science.gov (United States)

    Cheng, X. Y.; Wang, H. B.; Jia, Y. L.; Dong, YH

    2018-05-01

    In this paper, an open-closed-loop iterative learning control (ILC) algorithm is constructed for a class of nonlinear systems subjecting to random data dropouts. The ILC algorithm is implemented by a networked control system (NCS), where only the off-line data is transmitted by network while the real-time data is delivered in the point-to-point way. Thus, there are two controllers rather than one in the control system, which makes better use of the saved and current information and thereby improves the performance achieved by open-loop control alone. During the transfer of off-line data between the nonlinear plant and the remote controller data dropout occurs randomly and the data dropout rate is modeled as a binary Bernoulli random variable. Both measurement and control data dropouts are taken into consideration simultaneously. The convergence criterion is derived based on rigorous analysis. Finally, the simulation results verify the effectiveness of the proposed method.

  19. Using Random Parameter Logit in Open and Distance Learning (ODL) Institutions in Malaysia

    Science.gov (United States)

    Chiam, Chooi Chea; Loo, SzeWei

    2015-01-01

    Attention has been drawn to Open Distance Learning (ODL) as a mode for teaching and learning with the advancement in communication via the Internet. Education today has expanded the role of ICT in learning and knowledge generation, leveraging on Internet technology to transmit education across the country. Due to the advancement of technology and…

  20. The impact of blended teaching on knowledge, satisfaction, and self-directed learning in nursing undergraduates: a randomized, controlled trial.

    Science.gov (United States)

    Gagnon, Marie-Pierre; Gagnon, Johanne; Desmartis, Marie; Njoya, Merlin

    2013-01-01

    This study aimed to assess the effectiveness of a blended-teaching intervention using Internet-based tutorials coupled with traditional lectures in an introduction to research undergraduate nursing course. Effects of the intervention were compared with conventional, face-to-face classroom teaching on three outcomes: knowledge, satisfaction, and self-learning readiness. A two-group, randomized, controlled design was used, involving 112 participants. Descriptive statistics and analysis of covariance (ANCOVA) were performed. The teaching method was found to have no direct impact on knowledge acquisition, satisfaction, and self-learning readiness. However, motivation and teaching method had an interaction effect on knowledge acquisition by students. Among less motivated students, those in the intervention group performed better than those who received traditional training. These findings suggest that this blended-teaching method could better suit some students, depending on their degree of motivation and level of self-directed learning readiness.

  1. Physiotherapy students' perspectives of online e-learning for interdisciplinary management of chronic health conditions: a qualitative study.

    Science.gov (United States)

    Gardner, Peter; Slater, Helen; Jordan, Joanne E; Fary, Robyn E; Chua, Jason; Briggs, Andrew M

    2016-02-16

    To qualitatively explore physiotherapy students' perceptions of online e-learning for chronic disease management using a previously developed, innovative and interactive, evidence-based, e-learning package: Rheumatoid Arthritis for Physiotherapists e-Learning (RAP-eL). Physiotherapy students participated in three focus groups in Perth, Western Australia. Purposive sampling was employed to ensure maximum heterogeneity across age, gender and educational background. To explore students' perspectives on the advantages and disadvantages of online e-learning, ways to enhance e-learning, and information/learning gaps in relation to interdisciplinary management of chronic health conditions, a semi-structured interview schedule was developed. Verbatim transcripts were analysed using inductive methods within a grounded theory approach to derive key themes. Twenty-three students (78 % female; 39 % with previous tertiary qualification) of mean (SD) age 23 (3.6) years participated. Students expressed a preference for a combination of both online e-learning and lecture-style learning formats for chronic disease management, citing flexibility to work at one's own pace and time, and access to comprehensive information as advantages of e-learning learning. Personal interaction and ability to clarify information immediately were considered advantages of lecture-style formats. Perceived knowledge gaps included practical application of interdisciplinary approaches to chronic disease management and developing and implementing physiotherapy management plans for people with chronic health conditions. Physiotherapy students preferred multi-modal and blended formats for learning about chronic disease management. This study highlights the need for further development of practically-oriented knowledge and skills related to interdisciplinary care for people with chronic conditions among physiotherapy students. While RAP-eL focuses on rheumatoid arthritis, the principles of learning apply to

  2. Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

    Science.gov (United States)

    Zdravevski, Eftim; Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

    2017-01-01

    Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from

  3. Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

    Directory of Open Access Journals (Sweden)

    Eftim Zdravevski

    Full Text Available Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position.The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers.The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be

  4. Influence of depth of neuromuscular blockade on surgical conditions during low-pressure pneumoperitoneum laparoscopic cholecystectomy: A randomized blinded study.

    Science.gov (United States)

    Barrio, Javier; Errando, Carlos L; García-Ramón, Jaime; Sellés, Rafael; San Miguel, Guillermo; Gallego, Juan

    2017-11-01

    To evaluate the influence of neuromuscular blockade (NMB) on surgical conditions during low-pressure pneumoperitoneum (8mmHg) laparoscopic cholecystectomy (LC), while comparing moderate and deep NMB. Secondary objective was to evaluate if surgical conditions during low-pressure pneumoperitoneum LC performed with deep NMB could be comparable to those provided during standard-pressure pneumoperitoneum (12mmHg) LC. Prospective, randomized, blinded clinical trial. Operating room. Ninety ASA 1-2 patients scheduled for elective LC. Patients were allocated into 3 groups: Group 1: low-pressure pneumoperitoneum with moderate-NMB (1-3 TOF), Group 2: low-pressure pneumoperitoneum with deep-NMB (1-5 PTC) and Group 3: standard pneumoperitoneum (12mmHg). Rocuronium was used to induce NMB and acceleromiography was used for NMB monitoring (TOF-Watch-SX). Three experienced surgeons evaluated surgical conditions using a four-step scale at three time-points: surgical field exposure, dissection of the gallbladder and extraction/closure. Low-pressure pneumoperitoneum (Group 1 vs. 2): good conditions: 96.7 vs. 96.7%, 90 vs. 80% and 89.6 vs. 92.3%, respectively for the time-points, p>0.05. No differences in optimal surgical conditions were observed between the groups. Surgery completion at 8mmHg pneumoperitoneum: 96.7 vs. 86.7%, p=0.353. Standard-pressure pneumoperitoneum vs. low-pressure pneumoperitoneum with deep NMB (Group 3 vs. 2): good conditions: 100% in Group 3 for the three time-points (p=0.024 vs. Group 2 at dissection of the gallbladder). Significantly greater percentage of optimal conditions during standard-pressure pneumoperitoneum LC at the three time points of evaluation. The depth of NMB was found not to be decisive neither in the improvement of surgical conditions nor in the completion of low-pressure pneumoperitoneum LC performed by experienced surgeons. Surgical conditions were considered better with a standard-pressure pneumoperitoneum, regardless of the depth of NMB

  5. Cervical Joint Position Sense in Hypobaric Conditions: A Randomized Double-Blind Controlled Trial.

    Science.gov (United States)

    Bagaianu, Diana; Van Tiggelen, Damien; Duvigneaud, N; Stevens, Veerle; Schroyen, Danny; Vissenaeken, Dirk; D'Hondt, Gino; Pitance, Laurent

    2017-09-01

    head repositioning accuracy in healthy subjects. Discussion/impact/recommendations: Postural control mechanisms are very sensitive to acute mild hypoxia and have been recently investigated. Acute hypobaric hypoxia at moderate and high altitudes has a negative effect on postural control. However, which part of the postural system is affected has not yet been determined and proprioception has been little investigated. The results from this study highlighted that in healthy subjects with good cervical spine proprioception at baseline, artificial hypoxia induced by the simulation of moderate altitude does not increase head repositioning error. Further studies should investigate cervical joint position sense in real aircraft, at different altitudes and in a group of experienced helicopter pilots, to evaluate the impact of moderate altitude on cervical joint position sense in a different population. Conducting the same experiments in a population of pilots and in real flight conditions should be considered, since various factors such as the level of proprioception, head posture, type of movement, head load, muscle fatigue, flight altitude, and the length of flight time might influence the kinesthetic sensitivity. Reprint & Copyright © 2017 Association of Military Surgeons of the U.S.

  6. Parents' learning needs and preferences when sharing management of their child's long-term/chronic condition: A systematic review.

    Science.gov (United States)

    Nightingale, Ruth; Friedl, Simone; Swallow, Veronica

    2015-11-01

    This review aimed to (1) identify parents' learning needs and preferences when sharing the management of their child's long-term/chronic (long-term) condition and (2) inform healthcare professional support provided to parents across the trajectory. We conducted a literature search in seven health databases from 1990 to 2013. The quality of included studies was assessed using a critical appraisal tool developed for reviewing the strengths and weaknesses of qualitative, quantitative and mixed methods studies. Twenty-three studies met our criteria and were included in the review. Three themes emerged from synthesis of the included studies: (1) parents' learning needs and preferences (2) facilitators to parents' learning, and (3) barriers to parents' learning. Asking parents directly about their learning needs and preferences may be the most reliable way for healthcare professionals to ascertain how to support and promote individual parents' learning when sharing management of their child's long-term condition. With the current emphasis on parent-healthcare professional shared management of childhood long-term conditions, it is recommended that professionals base their assessment of parents' learning needs and preferences on identified barriers and facilitators to parental learning. This should optimise delivery of home-based care, thereby contributing to improved clinical outcomes for the child. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. Experience and Lessons Learned from Conditioning of Spent Sealed Sources in Singapore - 13107

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Dae-Seok; Kang, Il-Sik; Jang, Kyung-Duk; Jang, Won-Hyuk [Korea Atomic Energy Research Institute, 1045 Daedeokdaero, Yuseong, Daejeon (Korea, Republic of); Hoo, Wee-Teck [National Environment Agency, 40 Scotts Road 228231 (Singapore)

    2013-07-01

    In 2010, IAEA requested KAERI (Korea Atomic Energy Research Institute) to support Singapore for conditioning spent sealed sources. Those that had been used for a lightning conductor, check source, or smoke detector, various sealed sources had been collected and stored by the NEA (National Environment Agency) in Singapore. Based on experiences for the conditioning of Ra-226 sources in some Asian countries since 2000, KAERI sent an expert team to Singapore for the safe management of spent sealed sources in 2011. As a result of the conditioning, about 575.21 mCi of Am-241, Ra-226, Co-60, and Sr-90 were safely conditioned in 3 concrete lining drums with the cooperation of the KAERI expert team, the IAEA supervisor, the NEA staff and local laborers in Singapore. Some lessons were learned during the operation: (1) preparations by a local authority are very helpful for an efficient operation, (2) a preliminary inspection by an expert team is helpful for the operation, (3) brief reports before and after daily operation are useful for communication, and (4) a training opportunity is required for the sustainability of the expert team. (authors)

  8. Role of exponential type random invexities for asymptotically sufficient efficiency conditions in semi-infinite multi-objective fractional programming.

    Science.gov (United States)

    Verma, Ram U; Seol, Youngsoo

    2016-01-01

    First a new notion of the random exponential Hanson-Antczak type [Formula: see text]-V-invexity is introduced, which generalizes most of the existing notions in the literature, second a random function [Formula: see text] of the second order is defined, and finally a class of asymptotically sufficient efficiency conditions in semi-infinite multi-objective fractional programming is established. Furthermore, several sets of asymptotic sufficiency results in which various generalized exponential type [Formula: see text]-V-invexity assumptions are imposed on certain vector functions whose components are the individual as well as some combinations of the problem functions are examined and proved. To the best of our knowledge, all the established results on the semi-infinite aspects of the multi-objective fractional programming are new, which is a significantly new emerging field of the interdisciplinary research in nature. We also observed that the investigated results can be modified and applied to several special classes of nonlinear programming problems.

  9. Genetic parameters for body condition score, body weight, milk yield, and fertility estimated using random regression models.

    Science.gov (United States)

    Berry, D P; Buckley, F; Dillon, P; Evans, R D; Rath, M; Veerkamp, R F

    2003-11-01

    Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation.

  10. Why do organizations not learn from incidents? Bottlenecks, causes and conditions for a failure to effectively learn

    DEFF Research Database (Denmark)

    Drupsteen, Linda; Hasle, Peter

    2014-01-01

    be studied.Difficulties were identified in multiple steps of the learning process, but most difficulties became visiblewhen planning actions, which is the phase that bridges the gap from incident investigation to actions forimprovement. The main causes for learning difficulties, which were identified...... learn. In sevenorganizations focus groups were held to discuss factors that according to employees contributed to thefailure to learn. By use of a model of the learning from incidents process, the steps, where difficulties forlearning arose, became visible, and the causes for these difficulties could...

  11. A cluster randomized control trial to assess the impact of active learning on child activity, attention control, and academic outcomes: The Texas I-CAN trial.

    Science.gov (United States)

    Bartholomew, John B; Jowers, Esbelle M; Errisuriz, Vanessa L; Vaughn, Sharon; Roberts, Gregory

    2017-10-01

    Active learning is designed to pair physical activity with the teaching of academic content. This has been shown to be a successful strategy to increase physical activity and improve academic performance. The existing designs have confounded academic lessons with physical activity. As a result, it is impossible to determine if the subsequent improvement in academic performance is due to: (1) physical activity, (2) the academic content of the active learning, or (3) the combination of academic material taught through physical activity. The Texas I-CAN project is a 3-arm, cluster randomized control trial in which 28 elementary schools were assigned to either control, math intervention, or spelling intervention. As a result, each intervention condition serves as an unrelated content control for the other arm of the trial, allowing the impact of physical activity to be separated from the content. That is, schools that perform only active math lessons provide a content control for the spelling schools on spelling outcomes. This also calculated direct observations of attention and behavior control following periods of active learning. This design is unique in its ability to separate the impact of physical activity, in general, from the combination of physical activity and specific academic content. This, in combination with the ability to examine both proximal and distal outcomes along with measures of time on task will do much to guide the design of future, school-based interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews.

    Science.gov (United States)

    Tutubalina, Elena; Nikolenko, Sergey

    2017-01-01

    Adverse drug reactions (ADRs) are an essential part of the analysis of drug use, measuring drug use benefits, and making policy decisions. Traditional channels for identifying ADRs are reliable but very slow and only produce a small amount of data. Text reviews, either on specialized web sites or in general-purpose social networks, may lead to a data source of unprecedented size, but identifying ADRs in free-form text is a challenging natural language processing problem. In this work, we propose a novel model for this problem, uniting recurrent neural architectures and conditional random fields. We evaluate our model with a comprehensive experimental study, showing improvements over state-of-the-art methods of ADR extraction.

  13. Combination of Deep Recurrent Neural Networks and Conditional Random Fields for Extracting Adverse Drug Reactions from User Reviews

    Directory of Open Access Journals (Sweden)

    Elena Tutubalina

    2017-01-01

    Full Text Available Adverse drug reactions (ADRs are an essential part of the analysis of drug use, measuring drug use benefits, and making policy decisions. Traditional channels for identifying ADRs are reliable but very slow and only produce a small amount of data. Text reviews, either on specialized web sites or in general-purpose social networks, may lead to a data source of unprecedented size, but identifying ADRs in free-form text is a challenging natural language processing problem. In this work, we propose a novel model for this problem, uniting recurrent neural architectures and conditional random fields. We evaluate our model with a comprehensive experimental study, showing improvements over state-of-the-art methods of ADR extraction.

  14. MDMA enhances hippocampal-dependent learning and memory under restrictive conditions, and modifies hippocampal spine density.

    Science.gov (United States)

    Abad, Sònia; Fole, Alberto; del Olmo, Nuria; Pubill, David; Pallàs, Mercè; Junyent, Fèlix; Camarasa, Jorge; Camins, Antonio; Escubedo, Elena

    2014-03-01

    Addictive drugs produce forms of structural plasticity in the nucleus accumbens and prefrontal cortex. The aim of this study was to investigate the impact of chronic MDMA exposure on pyramidal neurons in the CA1 region of hippocampus and drug-related spatial learning and memory changes. Adolescent rats were exposed to saline or MDMA in a regime that mimicked chronic administration. One week later, when acquisition or reference memory was evaluated in a standard Morris water maze (MWM), no differences were obtained between groups. However, MDMA-exposed animals performed better when the MWM was implemented under more difficult conditions. Animals of MDMA group were less anxious and were more prepared to take risks, as in the open field test they ventured more frequently into the central area. We have demonstrated that MDMA caused an increase in brain-derived neurotrophic factor (BDNF) expression. When spine density was evaluated, MDMA-treated rats presented a reduced density when compared with saline, but overall, training increased the total number of spines, concluding that in MDMA-group, training prevented a reduction in spine density or induced its recovery. This study provides support for the conclusion that binge administration of MDMA, known to be associated to neurotoxic damage of hippocampal serotonergic terminals, increases BDNF expression and stimulates synaptic plasticity when associated with training. In these conditions, adolescent rats perform better in a more difficult water maze task under restricted conditions of learning and memory. The effect on this task could be modulated by other behavioural changes provoked by MDMA.

  15. Using Random Parameter Logit In Open And Distance Learning (ODL) Institutions In Malaysia

    OpenAIRE

    Chooi Chea Chiam; SzeWei Loo

    2015-01-01

    Attention has been drawn to Open Distance Learning (ODL) as a mode for teaching and learning with the advancement in communication via the Internet. Education today has expanded the role of ICT in learning and knowledge generation, leveraging on Internet technology to transmit education across the country. Technology advancement and the introduction of ODL in educationhas created heated competition among these private higher education providers in Malaysia. ODL mode offers a flexible form of ...

  16. Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of net...

  17. Learning Historical Thinking with Oral History Interviews: A Cluster Randomized Controlled Intervention Study of Oral History Interviews in History Lessons

    Science.gov (United States)

    Bertram, Christiane; Wagner, Wolfgang; Trautwein, Ulrich

    2017-01-01

    The present study examined the effectiveness of the oral history approach with respect to students' historical competence. A total of 35 ninth-grade classes (N = 900) in Germany were randomly assigned to one of four conditions--live, video, text, or a (nontreated) control group--in a pretest, posttest, and follow-up design. Comparing the three…

  18. Comparison of error-based and errorless learning for people with severe traumatic brain injury: study protocol for a randomized control trial.

    Science.gov (United States)

    Ownsworth, Tamara; Fleming, Jennifer; Tate, Robyn; Shum, David H K; Griffin, Janelle; Schmidt, Julia; Lane-Brown, Amanda; Kendall, Melissa; Chevignard, Mathilde

    2013-11-05

    Poor skills generalization poses a major barrier to successful outcomes of rehabilitation after traumatic brain injury (TBI). Error-based learning (EBL) is a relatively new intervention approach that aims to promote skills generalization by teaching people internal self-regulation skills, or how to anticipate, monitor and correct their own errors. This paper describes the protocol of a study that aims to compare the efficacy of EBL and errorless learning (ELL) for improving error self-regulation, behavioral competency, awareness of deficits and long-term outcomes after TBI. This randomized, controlled trial (RCT) has two arms (EBL and ELL); each arm entails 8 × 2 h training sessions conducted within the participants' homes. The first four sessions involve a meal preparation activity, and the final four sessions incorporate a multitasking errand activity. Based on a sample size estimate, 135 participants with severe TBI will be randomized into either the EBL or ELL condition. The primary outcome measure assesses error self-regulation skills on a task related to but distinct from training. Secondary outcomes include measures of self-monitoring and self-regulation, behavioral competency, awareness of deficits, role participation and supportive care needs. Assessments will be conducted at pre-intervention, post-intervention, and at 6-months post-intervention. This study seeks to determine the efficacy and long-term impact of EBL for training internal self-regulation strategies following severe TBI. In doing so, the study will advance theoretical understanding of the role of errors in task learning and skills generalization. EBL has the potential to reduce the length and costs of rehabilitation and lifestyle support because the techniques could enhance generalization success and lifelong application of strategies after TBI. ACTRN12613000585729.

  19. Effect of Play-based Therapy on Meta-cognitive and Behavioral Aspects of Executive Function: A Randomized, Controlled, Clinical Trial on the Students With Learning Disabilities.

    Science.gov (United States)

    Karamali Esmaili, Samaneh; Shafaroodi, Narges; Hassani Mehraban, Afsoon; Parand, Akram; Zarei, Masoume; Akbari-Zardkhaneh, Saeed

    2017-01-01

    Although the effect of educational methods on executive function (EF) is well known, training this function by a playful method is debatable. The current study aimed at investigating if a play-based intervention is effective on metacognitive and behavioral skills of EF in students with specific learning disabilities. In the current randomized, clinical trial, 49 subjects within the age range of 7 to 11 years with specific learning disabilities were randomly assigned into the intervention (25 subjects; mean age 8.5±1.33 years) and control (24 subjects; mean age 8.7±1.03 years) groups. Subjects in the intervention group received EF group training based on playing activities; subjects in the control group received no intervention. The behavior rating inventory of executive function (BRIEF) was administered to evaluate the behavioral and cognitive aspects of EF. The duration of the intervention was 6 hours per week for 9 weeks. Multivariate analysis of covariance was used to compare mean changes (before and after) in the BRIEF scores between the groups. The assumptions of multivariate analysis of covariance were examined. After controlling pre-test conditions, the intervention and control groups scored significantly differently on both the metacognition (P=0.002; effect size=0.20) and behavior regulation indices (P=0.01; effect size=0.12) of BRIEF. Play-based therapy is effective on the metacognitive and behavioral aspects of EF in students with specific learning disabilities. Professionals can use play-based therapy rather than educational approaches in clinical practice to enhance EF skills.

  20. Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.

    Science.gov (United States)

    Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio

    2018-02-01

    Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially important as these systems are pervasively being introduced to critical domains, such as the medical field. Representation Learning techniques are general methods for automatic feature computation. Nevertheless, these techniques are regarded as uninterpretable "black boxes". In this paper, we propose a methodology to enhance the interpretability of automatically extracted machine learning features. The proposed system is composed of a Restricted Boltzmann Machine for unsupervised feature learning, and a Random Forest classifier, which are combined to jointly consider existing correlations between imaging data, features, and target variables. We define two levels of interpretation: global and local. The former is devoted to understanding if the system learned the relevant relations in the data correctly, while the later is focused on predictions performed on a voxel- and patient-level. In addition, we propose a novel feature importance strategy that considers both imaging data and target variables, and we demonstrate the ability of the approach to leverage the interpretability of the obtained representation for the task at hand. We evaluated the proposed methodology in brain tumor segmentation and penumbra estimation in ischemic stroke lesions. We show the ability of the proposed methodology to unveil information regarding relationships between imaging modalities and extracted features and their usefulness for the task at hand. In both clinical scenarios, we demonstrate that the proposed methodology enhances the interpretability of automatically learned features, highlighting specific learning patterns that resemble how an expert extracts relevant data from medical images. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. The Role of Nucleus Accumbens Shell in Learning about Neutral versus Excitatory Stimuli during Pavlovian Fear Conditioning

    Science.gov (United States)

    Bradfield, Laura A.; McNally, Gavan P.

    2010-01-01

    We studied the role of nucleus accumbens shell (AcbSh) in Pavlovian fear conditioning. Rats were trained to fear conditioned stimulus A (CSA) in Stage I, which was then presented in compound with a neutral stimulus and paired with shock in Stage II. AcbSh lesions had no effect on fear-learning to CSA in Stage I, but selectively prevented learning…

  2. Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test.

    Science.gov (United States)

    Souillard-Mandar, William; Davis, Randall; Rudin, Cynthia; Au, Rhoda; Libon, David J; Swenson, Rodney; Price, Catherine C; Lamar, Melissa; Penney, Dana L

    2016-03-01

    The Clock Drawing Test - a simple pencil and paper test - has been used for more than 50 years as a screening tool to differentiate normal individuals from those with cognitive impairment, and has proven useful in helping to diagnose cognitive dysfunction associated with neurological disorders such as Alzheimer's disease, Parkinson's disease, and other dementias and conditions. We have been administering the test using a digitizing ballpoint pen that reports its position with considerable spatial and temporal precision, making available far more detailed data about the subject's performance. Using pen stroke data from these drawings categorized by our software, we designed and computed a large collection of features, then explored the tradeoffs in performance and interpretability in classifiers built using a number of different subsets of these features and a variety of different machine learning techniques. We used traditional machine learning methods to build prediction models that achieve high accuracy. We operationalized widely used manual scoring systems so that we could use them as benchmarks for our models. We worked with clinicians to define guidelines for model interpretability, and constructed sparse linear models and rule lists designed to be as easy to use as scoring systems currently used by clinicians, but more accurate. While our models will require additional testing for validation, they offer the possibility of substantial improvement in detecting cognitive impairment earlier than currently possible, a development with considerable potential impact in practice.

  3. Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

    Science.gov (United States)

    Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

    2016-10-05

    Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

  4. A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

    Science.gov (United States)

    Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

    2018-01-01

    Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that

  5. Social Learning Theory Parenting Intervention Promotes Attachment-Based Caregiving in Young Children: Randomized Clinical Trial

    Science.gov (United States)

    O'Connor, Thomas G.; Matias, Carla; Futh, Annabel; Tantam, Grace; Scott, Stephen

    2013-01-01

    Parenting programs for school-aged children are typically based on behavioral principles as applied in social learning theory. It is not yet clear if the benefits of these interventions extend beyond aspects of the parent-child relationship quality conceptualized by social learning theory. The current study examined the extent to which a social…

  6. Teaching Parents about Responsive Feeding through a Vicarious Learning Video: A Pilot Randomized Controlled Trial

    Science.gov (United States)

    Ledoux, Tracey; Robinson, Jessica; Baranowski, Tom; O'Connor, Daniel P.

    2018-01-01

    The American Academy of Pediatrics and World Health Organization recommend responsive feeding (RF) to promote healthy eating behaviors in early childhood. This project developed and tested a vicarious learning video to teach parents RF practices. A RF vicarious learning video was developed using community-based participatory research methods.…

  7. Teaching parents about responsive feeding through a vicarious learning video: A pilot randomized controlled trial

    Science.gov (United States)

    The American Academy of Pediatrics and World Health Organization recommend responsive feeding (RF) to promote healthy eating behaviors in early childhood. This project developed and tested a vicarious learning video to teach parents RF practices. A RF vicarious learning video was developed using com...

  8. Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions

    Directory of Open Access Journals (Sweden)

    Hussain Shareef

    2017-01-01

    Full Text Available Many maximum power point tracking (MPPT algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland–Altman test, with more than 95 percent acceptability.

  9. Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

    Science.gov (United States)

    Chan, Jennifer S K

    2016-05-01

    Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions.

    Science.gov (United States)

    Shareef, Hussain; Mutlag, Ammar Hussein; Mohamed, Azah

    2017-01-01

    Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland-Altman test, with more than 95 percent acceptability.

  11. Active learning for clinical text classification: is it better than random sampling?

    Science.gov (United States)

    Figueroa, Rosa L; Ngo, Long H; Goryachev, Sergey; Wiechmann, Eduardo P

    2012-01-01

    Objective This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks. Design Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to classify text from five datasets. The performance of these algorithms was compared to that of passive learning on the five datasets. We then conducted a novel investigation of the interaction between dataset characteristics and the performance results. Measurements Classification accuracy and area under receiver operating characteristics (ROC) curves for each algorithm at different sample sizes were generated. The performance of active learning algorithms was compared with that of passive learning using a weighted mean of paired differences. To determine why the performance varies on different datasets, we measured the diversity and uncertainty of each dataset using relative entropy and correlated the results with the performance differences. Results The DIST and CMB algorithms performed better than passive learning. With a statistical significance level set at 0.05, DIST outperformed passive learning in all five datasets, while CMB was found to be better than passive learning in four datasets. We found strong correlations between the dataset diversity and the DIV performance, as well as the dataset uncertainty and the performance of the DIST algorithm. Conclusion For medical text classification, appropriate active learning algorithms can yield performance comparable to that of passive learning with considerably smaller training sets. In particular, our results suggest that DIV performs better on data with higher diversity and DIST on data with lower uncertainty. PMID:22707743

  12. Adaptive learning can result in a failure to profit from good conditions: implications for understanding depression.

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    Trimmer, Pete C; Higginson, Andrew D; Fawcett, Tim W; McNamara, John M; Houston, Alasdair I

    2015-04-26

    Depression is a major medical problem diagnosed in an increasing proportion of people and for which commonly prescribed psychoactive drugs are frequently ineffective. Development of treatment options may be facilitated by an evolutionary perspective; several adaptive reasons for proneness to depression have been proposed. A common feature of many explanations is that depressive behaviour is a way to avoid costly effort where benefits are small and/or unlikely. However, this viewpoint fails to explain why low mood persists when the situation improves. We investigate whether a behavioural rule that is adapted to a stochastically changing world can cause inactivity which appears similar to the effect of depression, in that it persists after the situation has improved. We develop an adaptive learning model in which an individual has repeated choices of whether to invest costly effort that may result in a net benefit. Investing effort also provides information about the current conditions and rates of change of the conditions. An individual following the optimal behavioural strategy may sometimes remain inactive when conditions are favourable (i.e. when it would be better to invest effort) when it is poorly informed about the current environmental state. Initially benign conditions can predispose an individual to inactivity after a relatively brief period of negative experiences. Our approach suggests that the antecedent factors causing depressed behaviour could go much further back in an individual s history than is currently appreciated. The insights from our approach have implications for the ongoing debate about best treatment options for patients with depressive symptoms. © The Author(s) 2015. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.

  13. Overlapping neurobiology of learned helplessness and conditioned defeat: implications for PTSD and mood disorders.

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    Hammack, Sayamwong E; Cooper, Matthew A; Lezak, Kimberly R

    2012-02-01

    Exposure to traumatic events can increase the risk for major depressive disorder (MDD) as well as posttraumatic stress disorder (PTSD), and pharmacological treatments for these disorders often involve the modulation of serotonergic (5-HT) systems. Several behavioral paradigms in rodents produce changes in behavior that resemble symptoms of MDD and these behavioral changes are sensitive to antidepressant treatments. Here we review two animal models in which MDD-like behavioral changes are elicited by exposure to an acute traumatic event during adulthood, learned helplessness (LH) and conditioned defeat. In LH, exposure of rats to inescapable, but not escapable, tailshock produces a constellation of behavioral changes that include deficits in fight/flight responding and enhanced anxiety-like behavior. In conditioned defeat, exposure of Syrian hamsters to a social defeat by a more aggressive animal leads to a loss of territorial aggression and an increase in submissive and defensive behaviors in subsequent encounters with non-aggressive conspecifics. Investigations into the neural substrates that control LH and conditioned defeat revealed that increased 5-HT activity in the dorsal raphe nucleus (DRN) is critical for both models. Other key brain regions that regulate the acquisition and/or expression of behavior in these two paradigms include the basolateral amygdala (BLA), central nucleus of the amygdala (CeA) and bed nucleus of the stria terminalis (BNST). In this review, we compare and contrast the role of each of these neural structures in mediating LH and conditioned defeat, and discuss the relevance of these data in developing a better understanding of the mechanisms underlying trauma-related depression. This article is part of a Special Issue entitled 'Post-Traumatic Stress Disorder'. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Comparing Patient Satisfaction and Intubating Conditions Using Succinylcholine or Low-Dose Rocuronium for Rigid Bronchoscopy: A Randomized Study.

    Science.gov (United States)

    Ghezel-Ahmadi, Verena; Ghezel-Ahmadi, David; Mangen, Jacques; Bolukbas, Servet; Welker, Andreas; Kuerschner, Veit Christian; Fischer, Andreas; Schirren, Joachim; Beck, Grietje

    2015-09-01

    Despite its serious side effects, succinylcholine is commonly used for neuromuscular relaxation in short procedures, such as rigid bronchoscopy and tracheobronchial interventions. The application of low-dose rocuronium reversed by low-dose sugammadex might be a modern alternative. The aim of this study was to compare patient satisfaction, incidence of postoperative myalgia (POM) as well as intubating conditions of these two muscle relaxants for rigid bronchoscopy. A single-center, prospective-randomized, blinded study of 95 patients, scheduled for rigid bronchoscopy and tracheobronchial intervention was conducted. The patients were anesthetized with propofol, remifentanil and either low-dose succinylcholine (S) (0.5 mg/kg) or low-dose rocuronium (0.25 mg/kg) with sugammadex (RS) (0.5 mg/kg). All patients were evaluated on the first and second postinterventional day for their satisfaction with the treatment (rigid bronchoscopy) using a Numeric Analog Rating Scale (NAS 0-10) and the presence and severity of POM (NAS 1-4). Intubating conditions were assessed as excellent, good, or poor on the basis of position of vocal cords and reaction to insertion of the rigid bronchoscope. Patients in the S group were less satisfied with the treatment than patients in RS group (72.7 vs. 93.7%, p = 0.007). The incidence of POM on the first day after intervention was significantly higher in the S group then in the RS group (56.9% vs. 4.3%, p rocuronium in 75% of patients. The anesthetic drug costs were significantly higher in the RS group then in the S group (p rocuronium provided better patient satisfaction and less POM. But with the use of low-dose succinylcholine, the intubating conditions are more comfortable, and it is less expensive than rocuronium/sugammadex. Georg Thieme Verlag KG Stuttgart · New York.

  15. Implementation of Treat-to-Target in Rheumatoid Arthritis Through a Learning Collaborative: Results of a Randomized Controlled Trial.

    Science.gov (United States)

    Solomon, Daniel H; Losina, Elena; Lu, Bing; Zak, Agnes; Corrigan, Cassandra; Lee, Sara B; Agosti, Jenifer; Bitton, Asaf; Harrold, Leslie R; Pincus, Theodore; Radner, Helga; Yu, Zhi; Smolen, Josef S; Fraenkel, Liana; Katz, Jeffrey N

    2017-07-01

    Treat-to-target (TTT) is an accepted paradigm for the management of rheumatoid arthritis (RA), but some evidence suggests poor adherence. The purpose of this study was to test the effects of a group-based multisite improvement learning collaborative on adherence to TTT. We conducted a cluster-randomized quality-improvement trial with waitlist control across 11 rheumatology sites in the US. The intervention entailed a 9-month group-based learning collaborative that incorporated rapid-cycle improvement methods. A composite TTT implementation score was calculated as the percentage of 4 required items documented in the visit notes for each patient at 2 time points, as evaluated by trained staff. The mean change in the implementation score for TTT across all patients for the intervention sites was compared with that for the control sites after accounting for intracluster correlation using linear mixed models. Five sites with a total of 23 participating rheumatology providers were randomized to intervention and 6 sites with 23 participating rheumatology providers were randomized to the waitlist control. The intervention included 320 patients, and the control included 321 patients. At baseline, the mean TTT implementation score was 11% in both arms; after the 9-month intervention, the mean TTT implementation score was 57% in the intervention group and 25% in the control group (change in score of 46% for intervention and 14% for control; P = 0.004). We did not observe excessive use of resources or excessive occurrence of adverse events in the intervention arm. A learning collaborative resulted in substantial improvements in adherence to TTT for the management of RA. This study supports the use of an educational collaborative to improve quality. © 2017, American College of Rheumatology.

  16. Immersive and interactive virtual reality to improve learning and retention of neuroanatomy in medical students: a randomized controlled study.

    Science.gov (United States)

    Ekstrand, Chelsea; Jamal, Ali; Nguyen, Ron; Kudryk, Annalise; Mann, Jennifer; Mendez, Ivar

    2018-02-23

    Spatial 3-dimensional understanding of the brain is essential to learning neuroanatomy, and 3-dimensional learning techniques have been proposed as tools to enhance neuroanatomy training. The aim of this study was to examine the impact of immersive virtual-reality neuroanatomy training and compare it to traditional paper-based methods. In this randomized controlled study, participants consisted of first- or second-year medical students from the University of Saskatchewan recruited via email and posters displayed throughout the medical school. Participants were randomly assigned to the virtual-reality group or the paper-based group and studied the spatial relations between neural structures for 12 minutes after performing a neuroanatomy baseline test, with both test and control questions. A postintervention test was administered immediately after the study period and 5-9 days later. Satisfaction measures were obtained. Of the 66 participants randomly assigned to the study groups, 64 were included in the final analysis, 31 in the virtual-reality group and 33 in the paper-based group. The 2 groups performed comparably on the baseline questions and showed significant performance improvement on the test questions following study. There were no significant differences between groups for the control questions, the postintervention test questions or the 7-day postintervention test questions. Satisfaction survey results indicated that neurophobia was decreased. Results from this study provide evidence that training in neuroanatomy in an immersive and interactive virtual-reality environment may be an effective neuroanatomy learning tool that warrants further study. They also suggest that integration of virtual-reality into neuroanatomy training may improve knowledge retention, increase study motivation and decrease neurophobia. Copyright 2018, Joule Inc. or its licensors.

  17. Effect of Low-dose Atracurium on Laryngeal Mask Airway Insertion Conditions: A Randomized Double-blind Clinical Trial

    Directory of Open Access Journals (Sweden)

    Karim Nasseri

    2017-01-01

    Full Text Available Background: The amount of sedation and muscle relaxation of the jaw may have an impact on complications caused by laryngeal mask airway (LMA. The aim of this study is to evaluate the effect of low-dose Atracurium on conditions of insertion, complications, and hemodynamic responses to LMA insertion following induction of anesthesia with propofol, in patients undergoing cataract surgery. Patients and Methods: In this double-blind randomized clinical trial study, 60 patients were randomly divided into two groups. Initially, the patients in the study group received 0.15 mg/kg intravenous injection of atracurium, and the patients in the control group received 2 ml of intravenous injection of normal saline, after which anesthesia in both groups were induced with midazolam, fentanyl, lidocaine, and propofol. The amount of jaw relaxation, ease of insertion, and the time needed for insertion, hemodynamic responses and complications of LMA insertion were evaluated. Results: Jaw relaxation and ease of LMA insertion in the study group was significantly better than that of the control group (P = 0.02. Average time needed for LMA placement in the study group (5/06 ± 0.52 second was significantly lower than the control group (5/76 ± 0.67 second (P = 0.001. Hemodynamic response to LMA insertion was similar in both groups. Sore throat at recovery and 24 h after surgery in the control group was significantly higher than that of the study group (3/30 vs. 10/30 (P = 0.01. Conclusions: Using low doses of atracurium decreases the time needed for LMA insertion and sore throat after the operation. Atracurium also increases jaw relaxation and facilitates the placement of LMA.

  18. Imitation learning of car driving skills with decision trees and random forests

    Directory of Open Access Journals (Sweden)

    Cichosz Paweł

    2014-09-01

    Full Text Available Machine learning is an appealing and useful approach to creating vehicle control algorithms, both for simulated and real vehicles. One common learning scenario that is often possible to apply is learning by imitation, in which the behavior of an exemplary driver provides training instances for a supervised learning algorithm. This article follows this approach in the domain of simulated car racing, using the TORCS simulator. In contrast to most prior work on imitation learning, a symbolic decision tree knowledge representation is adopted, which combines potentially high accuracy with human readability, an advantage that can be important in many applications. Decision trees are demonstrated to be capable of representing high quality control models, reaching the performance level of sophisticated pre-designed algorithms. This is achieved by enhancing the basic imitation learning scenario to include active retraining, automatically triggered on control failures. It is also demonstrated how better stability and generalization can be achieved by sacrificing human-readability and using decision tree model ensembles. The methodology for learning control models contributed by this article can be hopefully applied to solve real-world control tasks, as well as to develop video game bots

  19. Learning cardiopulmonary resuscitation theory with face-to-face versus audiovisual instruction for secondary school students: a randomized controlled trial.

    Science.gov (United States)

    Cerezo Espinosa, Cristina; Nieto Caballero, Sergio; Juguera Rodríguez, Laura; Castejón-Mochón, José Francisco; Segura Melgarejo, Francisca; Sánchez Martínez, Carmen María; López López, Carmen Amalia; Pardo Ríos, Manuel

    2018-02-01

    To compare secondary students' learning of basic life support (BLS) theory and the use of an automatic external defibrillator (AED) through face-to-face classroom instruction versus educational video instruction. A total of 2225 secondary students from 15 schools were randomly assigned to one of the following 5 instructional groups: 1) face-to-face instruction with no audiovisual support, 2) face-to-face instruction with audiovisual support, 3) audiovisual instruction without face-to-face instruction, 4) audiovisual instruction with face-to-face instruction, and 5) a control group that received no instruction. The students took a test of BLS and AED theory before instruction, immediately after instruction, and 2 months later. The median (interquartile range) scores overall were 2.33 (2.17) at baseline, 5.33 (4.66) immediately after instruction (Paudiovisual instruction for learning BLS and AED theory were found in secondary school students either immediately after instruction or 2 months later.

  20. Evaluation of an e-learning system for diagnosis of gastric lesions using magnifying narrow-band imaging: a multicenter randomized controlled study.

    Science.gov (United States)

    Nakanishi, Hiroyoshi; Doyama, Hisashi; Ishikawa, Hideki; Uedo, Noriya; Gotoda, Takuji; Kato, Mototsugu; Nagao, Shigeaki; Nagami, Yasuaki; Aoyagi, Hiroyuki; Imagawa, Atsushi; Kodaira, Junichi; Mitsui, Shinya; Kobayashi, Nozomu; Muto, Manabu; Takatori, Hajime; Abe, Takashi; Tsujii, Masahiko; Watari, Jiro; Ishiyama, Shuhei; Oda, Ichiro; Ono, Hiroyuki; Kaneko, Kazuhiro; Yokoi, Chizu; Ueo, Tetsuya; Uchita, Kunihisa; Matsumoto, Kenshi; Kanesaka, Takashi; Morita, Yoshinori; Katsuki, Shinichi; Nishikawa, Jun; Inamura, Katsuhisa; Kinjo, Tetsu; Yamamoto, Katsumi; Yoshimura, Daisuke; Araki, Hiroshi; Kashida, Hiroshi; Hosokawa, Ayumu; Mori, Hirohito; Yamashita, Haruhiro; Motohashi, Osamu; Kobayashi, Kazuhiko; Hirayama, Michiaki; Kobayashi, Hiroyuki; Endo, Masaki; Yamano, Hiroo; Murakami, Kazunari; Koike, Tomoyuki; Hirasawa, Kingo; Miyaoka, Youichi; Hamamoto, Hidetaka; Hikichi, Takuto; Hanabata, Norihiro; Shimoda, Ryo; Hori, Shinichiro; Sato, Tadashi; Kodashima, Shinya; Okada, Hiroyuki; Mannami, Tomohiko; Yamamoto, Shojiro; Niwa, Yasumasa; Yashima, Kazuo; Tanabe, Satoshi; Satoh, Hiro; Sasaki, Fumisato; Yamazato, Tetsuro; Ikeda, Yoshiou; Nishisaki, Hogara; Nakagawa, Masahiro; Matsuda, Akio; Tamura, Fumio; Nishiyama, Hitoshi; Arita, Keiko; Kawasaki, Keisuke; Hoppo, Kazushige; Oka, Masashi; Ishihara, Shinichi; Mukasa, Michita; Minamino, Hiroaki; Yao, Kenshi

    2017-10-01

    Background and study aim  Magnifying narrow-band imaging (M-NBI) is useful for the accurate diagnosis of early gastric cancer (EGC). However, acquiring skill at M-NBI diagnosis takes substantial effort. An Internet-based e-learning system to teach endoscopic diagnosis of EGC using M-NBI has been developed. This study evaluated its effectiveness. Participants and methods  This study was designed as a multicenter randomized controlled trial. We recruited endoscopists as participants from all over Japan. After completing Test 1, which consisted of M-NBI images of 40 gastric lesions, participants were randomly assigned to the e-learning or non-e-learning groups. Only the e-learning group was allowed to access the e-learning system. After the e-learning period, both groups received Test 2. The analysis set was participants who scored e-learning group and 197 in the non-e-learning group). After the e-learning period, all 395 completed Test 2. The analysis sets were e-learning group: n = 184; and non-e-learning group: n = 184. The mean Test 1 score was 59.9 % for the e-learning group and 61.7 % for the non-e-learning group. The change in accuracy in Test 2 was significantly higher in the e-learning group than in the non-e-learning group (7.4 points vs. 0.14 points, respectively; P  e-learning system in improving practitioners' capabilities to diagnose EGC using M-NBI.Trial registered at University Hospital Medical Information Network Clinical Trials Registry (UMIN000008569). © Georg Thieme Verlag KG Stuttgart · New York.

  1. Random forest learning of ultrasonic statistical physics and object spaces for lesion detection in 2D sonomammography

    Science.gov (United States)

    Sheet, Debdoot; Karamalis, Athanasios; Kraft, Silvan; Noël, Peter B.; Vag, Tibor; Sadhu, Anup; Katouzian, Amin; Navab, Nassir; Chatterjee, Jyotirmoy; Ray, Ajoy K.

    2013-03-01

    Breast cancer is the most common form of cancer in women. Early diagnosis can significantly improve lifeexpectancy and allow different treatment options. Clinicians favor 2D ultrasonography for breast tissue abnormality screening due to high sensitivity and specificity compared to competing technologies. However, inter- and intra-observer variability in visual assessment and reporting of lesions often handicaps its performance. Existing Computer Assisted Diagnosis (CAD) systems though being able to detect solid lesions are often restricted in performance. These restrictions are inability to (1) detect lesion of multiple sizes and shapes, and (2) differentiate between hypo-echoic lesions from their posterior acoustic shadowing. In this work we present a completely automatic system for detection and segmentation of breast lesions in 2D ultrasound images. We employ random forests for learning of tissue specific primal to discriminate breast lesions from surrounding normal tissues. This enables it to detect lesions of multiple shapes and sizes, as well as discriminate between hypo-echoic lesion from associated posterior acoustic shadowing. The primal comprises of (i) multiscale estimated ultrasonic statistical physics and (ii) scale-space characteristics. The random forest learns lesion vs. background primal from a database of 2D ultrasound images with labeled lesions. For segmentation, the posterior probabilities of lesion pixels estimated by the learnt random forest are hard thresholded to provide a random walks segmentation stage with starting seeds. Our method achieves detection with 99.19% accuracy and segmentation with mean contour-to-contour error < 3 pixels on a set of 40 images with 49 lesions.

  2. Three-dimensional printing model improves morphological understanding in acetabular fracture learning: A multicenter, randomized, controlled study.

    Directory of Open Access Journals (Sweden)

    Zhenfei Huang

    Full Text Available Conventional education results in unsatisfactory morphological understanding of acetabular fractures due to lack of three-dimensional (3D details and tactile feedback of real fractures. Virtual reality (VR and 3D printing (3DP techniques are widely applied in teaching. The purpose of this study was to identify the effect of physical model (PM, VR and 3DP models in education of morphological understanding of acetabular fractures. 141 students were invited to participate in this study. Participants were equally and randomly assigned to the PM, VR and 3DP learning groups. Three-level objective tests were conducted to evaluate learning, including identifying anatomical landmarks, describing fracture lines, identifying classification, and inferring fracture mechanism. Four subjective questions were asked to evaluate the usability and value of instructional materials. Generally, the 3DP group showed a clear advantage over the PM and VR groups in objective tests, while there was no significant difference between the PM and VR groups. 3DP was considered to be the most valuable learning tool for understanding acetabular fractures. The findings demonstrate that 3DP modelling of real fractures is an effective learning instrument that can be used to understand the morphology of acetabular fractures and promote subjective interest.

  3. The application of online transcranial random noise stimulation and perceptual learning in the improvement of visual functions in mild myopia.

    Science.gov (United States)

    Camilleri, Rebecca; Pavan, Andrea; Campana, Gianluca

    2016-08-01

    It has recently been demonstrated how perceptual learning, that is an improvement in a sensory/perceptual task upon practice, can be boosted by concurrent high-frequency transcranial random noise stimulation (tRNS). It has also been shown that perceptual learning can generalize and produce an improvement of visual functions in participants with mild refractive defects. By using three different groups of participants (single-blind study), we tested the efficacy of a short training (8 sessions) using a single Gabor contrast-detection task with concurrent hf-tRNS in comparison with the same training with sham stimulation or hf-tRNS with no concurrent training, in improving visual acuity (VA) and contrast sensitivity (CS) of individuals with uncorrected mild myopia. A short training with a contrast detection task is able to improve VA and CS only if coupled with hf-tRNS, whereas no effect on VA and marginal effects on CS are seen with the sole administration of hf-tRNS. Our results support the idea that, by boosting the rate of perceptual learning via the modulation of neuronal plasticity, hf-tRNS can be successfully used to reduce the duration of the perceptual training and/or to increase its efficacy in producing perceptual learning and generalization to improved VA and CS in individuals with uncorrected mild myopia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  4. Improving Pediatric Basic Life Support Performance Through Blended Learning With Web-Based Virtual Patients: Randomized Controlled Trial.

    Science.gov (United States)

    Lehmann, Ronny; Thiessen, Christiane; Frick, Barbara; Bosse, Hans Martin; Nikendei, Christoph; Hoffmann, Georg Friedrich; Tönshoff, Burkhard; Huwendiek, Sören

    2015-07-02

    E-learning and blended learning approaches gain more and more popularity in emergency medicine curricula. So far, little data is available on the impact of such approaches on procedural learning and skill acquisition and their comparison with traditional approaches. This study investigated the impact of a blended learning approach, including Web-based virtual patients (VPs) and standard pediatric basic life support (PBLS) training, on procedural knowledge, objective performance, and self-assessment. A total of 57 medical students were randomly assigned to an intervention group (n=30) and a control group (n=27). Both groups received paper handouts in preparation of simulation-based PBLS training. The intervention group additionally completed two Web-based VPs with embedded video clips. Measurements were taken at randomization (t0), after the preparation period (t1), and after hands-on training (t2). Clinical decision-making skills and procedural knowledge were assessed at t0 and t1. PBLS performance was scored regarding adherence to the correct algorithm, conformance to temporal demands, and the quality of procedural steps at t1 and t2. Participants' self-assessments were recorded in all three measurements. Procedural knowledge of the intervention group was significantly superior to that of the control group at t1. At t2, the intervention group showed significantly better adherence to the algorithm and temporal demands, and better procedural quality of PBLS in objective measures than did the control group. These aspects differed between the groups even at t1 (after VPs, prior to practical training). Self-assessments differed significantly only at t1 in favor of the intervention group. Training with VPs combined with hands-on training improves PBLS performance as judged by objective measures.

  5. Kinematics and dynamics of green water on a fixed platform in a large wave basin in focusing wave and random wave conditions

    Science.gov (United States)

    Chuang, Wei-Liang; Chang, Kuang-An; Mercier, Richard

    2018-06-01

    Green water kinematics and dynamics due to wave impingements on a simplified geometry, fixed platform were experimentally investigated in a large, deep-water wave basin. Both plane focusing waves and random waves were employed in the generation of green water. The focusing wave condition was designed to create two consecutive plunging breaking waves with one impinging on the frontal vertical wall of the fixed platform, referred as wall impingement, and the other directly impinging on the deck surface, referred as deck impingement. The random wave condition was generated using the JONSWAP spectrum with a significant wave height approximately equal to the freeboard. A total of 179 green water events were collected in the random wave condition. By examining the green water events in random waves, three different flow types are categorized: collapse of overtopping wave, fall of bulk water, and breaking wave crest. The aerated flow velocity was measured using bubble image velocimetry, while the void fraction was measured using fiber optic reflectometry. For the plane focusing wave condition, measurements of impact pressure were synchronized with the flow velocity and void fraction measurements. The relationship between the peak pressures and the pressure rise times is examined. For the high-intensity impact in the deck impingement events, the peak pressures are observed to be proportional to the aeration levels. The maximum horizontal velocities in the green water events in random waves are well represented by the lognormal distribution. Ritter's solution is shown to quantitatively describe the green water velocity distributions under both the focusing wave condition and the random wave condition. A prediction equation for green water velocity distribution under random waves is proposed.

  6. Declarative virtual water maze learning and emotional fear conditioning in primary insomnia.

    Science.gov (United States)

    Kuhn, Marion; Hertenstein, Elisabeth; Feige, Bernd; Landmann, Nina; Spiegelhalder, Kai; Baglioni, Chiara; Hemmerling, Johanna; Durand, Diana; Frase, Lukas; Klöppel, Stefan; Riemann, Dieter; Nissen, Christoph

    2018-05-02

    Healthy sleep restores the brain's ability to adapt to novel input through memory formation based on activity-dependent refinements of the strength of neural transmission across synapses (synaptic plasticity). In line with this framework, patients with primary insomnia often report subjective memory impairment. However, investigations of memory performance did not produce conclusive results. The aim of this study was to further investigate memory performance in patients with primary insomnia in comparison to healthy controls, using two well-characterized learning tasks, a declarative virtual water maze task and emotional fear conditioning. Twenty patients with primary insomnia according to DSM-IV criteria (17 females, three males, 43.5 ± 13.0 years) and 20 good sleeper controls (17 females, three males, 41.7 ± 12.8 years) were investigated in a parallel-group study. All participants completed a hippocampus-dependent virtual Morris water maze task and amygdala-dependent classical fear conditioning. Patients with insomnia showed significantly delayed memory acquisition in the virtual water maze task, but no significant difference in fear acquisition compared with controls. These findings are consistent with the notion that memory processes that emerge from synaptic refinements in a hippocampal-neocortical network are particularly sensitive to chronic disruptions of sleep, while those in a basic emotional amygdala-dependent network may be more resilient. © 2018 European Sleep Research Society.

  7. Autologous Conditioned Plasma Versus Placebo Injection Therapy in Lateral Epicondylitis of the Elbow: A Double Blind, Randomized Study.

    Science.gov (United States)

    Schöffl, Volker; Willauschus, Wolfgang; Sauer, Felix; Küpper, Thomas; Schöffl, Isabelle; Lutter, Christoph; Gelse, Kolja; Dickschas, Jörg

    2017-01-01

    Introduction  There are various therapeutic approaches to the treatment of lateral epicondylitis, a highly prevalent musculoskeletal disorder. Recently, injection therapy with autologous conditioned plasma (ACP) has shown promise as a new approach. Methods  Set up as a prospective, double-blind, randomized controlled clinical trial, this study involved 50 patients with lateral epicondylitis. Following external randomization, 25 patients received one round of injection therapy with ACP (platelet rich plasma, PRP), while the remaining 25 patients received a placebo of 0.9 % NaCl. All patients were re-evaluated with respect to lateral epicondylitis of the elbow at four-weeks and six-months post-injection. Results  Out of 50 patients, 36 qualified for reevaluation, 18 patients from the ACP therapy group and 18 from the placebo group. The initial Disability of the Arm, Shoulder and Hand (DASH) score for all reevaluated patients was 36.4 in the ACP group, and 41.0 in the placebo group; both groups exhibited decreased DASH scores at the four-week and six-month post-injection follow-up (6 months: ACP 30.1, placebo 25.8). The decrease of the DASH score after 4 weeks was greater and qualified as statistically significant in the placebo group (p = 0.041), compared to the DASH score decrease in the ACP treatment group, which was statistically non-significant. Additionally, the difference between the DASH scores of the treatment and placebo groups was statistically non-significant four weeks and six months after treatment. Discussion  The results of this study suggest a therapeutic effect in both the ACP and placebo groups, with no evidence for a therapeutically significant difference between ACP and placebo treatments. It is hypothesized that, in accordance with the study protocols, injection with a local anaesthetic prior to ACP therapy may have an influence on the therapeutic effect of ACP. Future studies have to confirm recent findings that demonstrated a

  8. A Randomized Controlled Trial on the Effect of Tapentadol and Morphine on Conditioned Pain Modulation in Healthy Volunteers.

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    Chris Martini

    Full Text Available Modulatory descending pathways, originating at supraspinal sites that converge at dorsal horn neurons, influence pain perception in humans. Defects in descending pain control are linked to chronic pain states and its restoration may be a valuable analgesic tool. Conditioned pain modulation (CPM is a surrogate marker of descending inhibition that reduces the perception of pain from a primary test stimulus during application of a conditioning stimulus. Here the effects of the analgesics tapentadol, a combined mu-opioid receptor agonist and noradrenaline reuptake inhibitor, and morphine, a strong mu-opioid receptor agonist, were tested on CPM in a randomized, double-blind, placebo-controlled crossover trial in 12 healthy pain-free volunteers, to understand possible differences in mechanism of action between these opioids.On three occasions CPM responses were obtained 60-90 and 120-150 min following intake of tapentadol (100 mg immediate release tablet, morphine (40 mg immediate release tablet or placebo. At both time points, CPM was detectable after treatment with placebo and tapentadol (peak pain ratings reduced by 20-30% after application of the conditioning stimulus but not after morphine. Compared to placebo morphine displayed significantly less CPM: mean treatment difference 18.2% (95% CI 3.4 to 32.9% at 60-90 min after drug intake and 19.5% (95% CI 5.7 to 33.2% at 120-150 min after drug intake (p = 0.001. No difference in CPM between placebo and tapentadol was detected: mean treatment difference 1.5% (95% CI -11.6 to 14.6% at 60-90 min after drug intake and 1.5% (95% CI -16.0 to 18.9% at 120-150 min after drug intake (p = 0.60.Our data show that in volunteers morphine affects CPM, while tapentadol was without effect despite identical experimental conditions. These data confirm that tapentadol's main mechanism of action is distinct from that of morphine and likely related to the effect of adrenergic stimulation on descending controls

  9. Conditions for the quality of primary education teachers’ collective learning at individual and group level

    NARCIS (Netherlands)

    Doppenberg, J.J.; Brok, den P.J.; Bergen, T.C.M.

    2009-01-01

    Collective teacher learning plays an important role in teachers' professional development and schools' innovative capacity. Despite this importance, collective learning in schools has been weakly conceptualised and little empirical evidence exists with respect to the contributions of collective

  10. Bidirectional Long Short-Term Memory Network with a Conditional Random Field Layer for Uyghur Part-Of-Speech Tagging

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    Maihemuti Maimaiti

    2017-11-01

    Full Text Available Uyghur is an agglutinative and a morphologically rich language; natural language processing tasks in Uyghur can be a challenge. Word morphology is important in Uyghur part-of-speech (POS tagging. However, POS tagging performance suffers from error propagation of morphological analyzers. To address this problem, we propose a few models for POS tagging: conditional random fields (CRF, long short-term memory (LSTM, bidirectional LSTM networks (BI-LSTM, LSTM networks with a CRF layer, and BI-LSTM networks with a CRF layer. These models do not depend on stemming and word disambiguation for Uyghur and combine hand-crafted features with neural network models. State-of-the-art performance on Uyghur POS tagging is achieved on test data sets using the proposed approach: 98.41% accuracy on 15 labels and 95.74% accuracy on 64 labels, which are 2.71% and 4% improvements, respectively, over the CRF model results. Using engineered features, our model achieves further improvements of 0.2% (15 labels and 0.48% (64 labels. The results indicate that the proposed method could be an effective approach for POS tagging in other morphologically rich languages.

  11. Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields

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    Teerapong Panboonyuen

    2017-07-01

    Full Text Available Object segmentation of remotely-sensed aerial (or very-high resolution, VHS images and satellite (or high-resolution, HR images, has been applied to many application domains, especially in road extraction in which the segmented objects are served as a mandatory layer in geospatial databases. Several attempts at applying the deep convolutional neural network (DCNN to extract roads from remote sensing images have been made; however, the accuracy is still limited. In this paper, we present an enhanced DCNN framework specifically tailored for road extraction of remote sensing images by applying landscape metrics (LMs and conditional random fields (CRFs. To improve the DCNN, a modern activation function called the exponential linear unit (ELU, is employed in our network, resulting in a higher number of, and yet more accurate, extracted roads. To further reduce falsely classified road objects, a solution based on an adoption of LMs is proposed. Finally, to sharpen the extracted roads, a CRF method is added to our framework. The experiments were conducted on Massachusetts road aerial imagery as well as the Thailand Earth Observation System (THEOS satellite imagery data sets. The results showed that our proposed framework outperformed Segnet, a state-of-the-art object segmentation technique, on any kinds of remote sensing imagery, in most of the cases in terms of precision, recall, and F 1 .

  12. Recognition and Evaluation of Clinical Section Headings in Clinical Documents Using Token-Based Formulation with Conditional Random Fields

    Directory of Open Access Journals (Sweden)

    Hong-Jie Dai

    2015-01-01

    Full Text Available Electronic health record (EHR is a digital data format that collects electronic health information about an individual patient or population. To enhance the meaningful use of EHRs, information extraction techniques have been developed to recognize clinical concepts mentioned in EHRs. Nevertheless, the clinical judgment of an EHR cannot be known solely based on the recognized concepts without considering its contextual information. In order to improve the readability and accessibility of EHRs, this work developed a section heading recognition system for clinical documents. In contrast to formulating the section heading recognition task as a sentence classification problem, this work proposed a token-based formulation with the conditional random field (CRF model. A standard section heading recognition corpus was compiled by annotators with clinical experience to evaluate the performance and compare it with sentence classification and dictionary-based approaches. The results of the experiments showed that the proposed method achieved a satisfactory F-score of 0.942, which outperformed the sentence-based approach and the best dictionary-based system by 0.087 and 0.096, respectively. One important advantage of our formulation over the sentence-based approach is that it presented an integrated solution without the need to develop additional heuristics rules for isolating the headings from the surrounding section contents.

  13. The Ghost Condition: Imitation Versus Emulation in Young Children's Observational Learning.

    Science.gov (United States)

    Thompson, Doreen E.; Russell, James

    2004-01-01

    Although observational learning by children may occur through imitating a modeler's actions, it can also occur through learning about an object's dynamic affordances- a process that M. Tomasello (1996) calls "emulation." The relative contributions of imitation and emulation within observational learning were examined in a study with 14- to…

  14. Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning

    Science.gov (United States)

    Rau, Martina A.

    2017-01-01

    Visual representations play a critical role in enhancing science, technology, engineering, and mathematics (STEM) learning. Educational psychology research shows that adding visual representations to text can enhance students' learning of content knowledge, compared to text-only. But should students learn with a single type of visual…

  15. Quality of the Home Learning Environment during Preschool Age--Domains and Contextual Conditions

    Science.gov (United States)

    Kluczniok, Katharina; Lehrl, Simone; Kuger, Susanne; Rossbach, Hans-Guenther

    2013-01-01

    The quality of the home learning environment has been proven to be of major importance for child development, but little is known about the role of domain specificity in promoting early childhood learning at home and its dependence on family background. This article presents a framework of the home learning environment in early childhood that…

  16. Development of an E-learning System for the Endoscopic Diagnosis of Early Gastric Cancer: An International Multicenter Randomized Controlled Trial.

    Science.gov (United States)

    Yao, K; Uedo, N; Muto, M; Ishikawa, H; Cardona, H J; Filho, E C Castro; Pittayanon, R; Olano, C; Yao, F; Parra-Blanco, A; Ho, S H; Avendano, A G; Piscoya, A; Fedorov, E; Bialek, A P; Mitrakov, A; Caro, L; Gonen, C; Dolwani, S; Farca, A; Cuaresma, L F; Bonilla, J J; Kasetsermwiriya, W; Ragunath, K; Kim, S E; Marini, M; Li, H; Cimmino, D G; Piskorz, M M; Iacopini, F; So, J B; Yamazaki, K; Kim, G H; Ang, T L; Milhomem-Cardoso, D M; Waldbaum, C A; Carvajal, W A Piedra; Hayward, C M; Singh, R; Banerjee, R; Anagnostopoulos, G K; Takahashi, Y

    2016-07-01

    In many countries, gastric cancer is not diagnosed until an advanced stage. An Internet-based e-learning system to improve the ability of endoscopists to diagnose gastric cancer at an early stage was developed and was evaluated for its effectiveness. The study was designed as a randomized controlled trial. After receiving a pre-test, participants were randomly allocated to either an e-learning or non-e-learning group. Only those in the e-learning group gained access to the e-learning system. Two months after the pre-test, both groups received a post-test. The primary endpoint was the difference between the two groups regarding the rate of improvement of their test results. 515 endoscopists from 35 countries were assessed for eligibility, and 332 were enrolled in the study, with 166 allocated to each group. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group were included in the analysis. The mean improvement rate (standard deviation) in the e-learning and non-e-learning groups was 1·24 (0·26) and 1·00 (0·16), respectively (Pe-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039). Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  17. Random practice - one of the factors of the motor learning process

    Directory of Open Access Journals (Sweden)

    Petr Valach

    2012-01-01

    Full Text Available BACKGROUND: An important concept of acquiring motor skills is the random practice (contextual interference - CI. The explanation of the effect of contextual interference is that the memory has to work more intensively, and therefore it provides higher effect of motor skills retention than the block practice. Only active remembering of a motor skill assigns the practical value for appropriate using in the future. OBJECTIVE: The aim of this research was to determine the difference in how the motor skills in sport gymnastics are acquired and retained using the two different teaching methods - blocked and random practice. METHODS: The blocked and random practice on the three selected gymnastics tasks were applied in the two groups students of physical education (blocked practice - the group BP, random practice - the group RP during two months, in one session a week (totally 80 trials. At the end of the experiment and 6 months after (retention tests the groups were tested on the selected gymnastics skills. RESULTS: No significant differences in a level of the gymnastics skills were found between BP group and RP group at the end of the experiment. However, the retention tests showed significantly higher level of the gymnastics skills in the RP group in comparison with the BP group. CONCLUSION: The results confirmed that a retention of the gymnastics skills using the teaching method of the random practice was significantly higher than with use of the blocked practice.

  18. Implementing blended learning in emergency airway management training: a randomized controlled trial.

    Science.gov (United States)

    Kho, Madeleine Huei Tze; Chew, Keng Sheng; Azhar, Muhaimin Noor; Hamzah, Mohd Lotfi; Chuah, Kee Man; Bustam, Aida; Chan, Hiang Chuan

    2018-01-15

    While emergency airway management training is conventionally conducted via face-to-face learning (F2FL) workshops, there are inherent cost, time, place and manpower limitations in running such workshops. Blended learning (BL) refers to the systematic integration of online and face-to-face learning aimed to facilitate complex thinking skills and flexible participation at a reduced financial, time and manpower cost. This study was conducted to evaluate its effectiveness in emergency airway management training. A single-center prospective randomised controlled trial involving 30 doctors from Sarawak General Hospital, Malaysia was conducted from September 2016 to February 2017 to compare the effectiveness of BL versus F2FL for emergency airway management training. Participants in the BL arm were given a period of 12 days to go through the online materials in a learning management system while those in the F2FL arm attended a-day of face-to-face lectures (8 h). Participants from both arms then attended a day of hands-on session consisting of simulation skills training with airway manikins. Pre- and post-tests in knowledge and practical skills were administered. E-learning experience and the perception towards BL among participants in the BL arm were also assessed. Significant improvements in post-test scores as compared to pre-test scores were noted for participants in both BL and F2FL arms for knowledge, practical, and total scores. The degree of increment between the BL group and the F2FL arms for all categories were not significantly different (total scores: 35 marks, inter-quartile range (IQR) 15.0 - 41.0 vs. 31 marks, IQR 24.0 - 41.0, p = 0.690; theory scores: 18 marks, IQR 9 - 24 vs. 19 marks, IQR 15 - 20, p = 0.992; practical scores: 11 marks, IQR 5 -18 vs. 10 marks, IQR 9 - 20, p = 0.461 respectively). The overall perception towards BL was positive. Blended learning is as effective as face-to-face learning for emergency airway management training

  19. Using Random Parameter Logit In Open And Distance Learning (ODL Institutions In Malaysia

    Directory of Open Access Journals (Sweden)

    Chooi Chea Chiam

    2015-10-01

    Full Text Available Attention has been drawn to Open Distance Learning (ODL as a mode for teaching and learning with the advancement in communication via the Internet. Education today has expanded the role of ICT in learning and knowledge generation, leveraging on Internet technology to transmit education across the country. Technology advancement and the introduction of ODL in educationhas created heated competition among these private higher education providers in Malaysia. ODL mode offers a flexible form of learning. Learners of ODL tend to be more challenging to fulfill their needs as they have other commitments in life, therefore, these learners will have certain criteria when choosing their learning education institution. The aim of this study is to investigate the vital attributes contributing in choosing an ODL higher education institution in Malaysia and to explore the consumers’ socioeconomic characteristicswith their willingness-to-pay fees. Although studies on the attributes that influence student choice of a university exist, these have failed to use the choice experiment method to examine the attributes influencing choice of ODL education provider. The sample population was 320 using face-to-face interview. The results would be able to provide ODL education providers in Malaysia with knowledge on making the right marketing strategy.

  20. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models.

    Science.gov (United States)

    Veerkamp, R F; Koenen, E P; De Jong, G

    2001-10-01

    Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were added for 180,631 cows. Heritabilities and genetic correlations were estimated using a sire-maternal grandsire model. Heritability of BCS was 0.38. Heritabilities for fertility traits were low (0.01 to 0.07), but genetic standard deviations were substantial, 9 d for days to first service and calving interval, 0.25 for number of services, and 5% for first-service conception. Phenotypic correlations between fertility and yield or BCS were small (-0.15 to 0.20). Genetic correlations between yield and all fertility traits were unfavorable (0.37 to 0.74). Genetic correlations with BCS were between -0.4 and -0.6 for calving interval and days to first service. Random regression analysis (RR) showed that correlations changed with days in milk for BCS. Little agreement was found between variances and correlations from RR, and analysis including a single month (mo 1 to 10) of data for BCS, especially during early and late lactation. However, this was due to excluding data from the conventional analysis, rather than due to the polynomials used. RR and a conventional five-traits model where BCS in mo 1, 4, 7, and 10 was treated as a separate traits (plus yield or fertility) gave similar results. Thus a parsimonious random regression model gave more realistic estimates for the (co)variances than a series of bivariate analysis on subsets of the data for BCS. A higher genetic merit for yield has unfavorable effects on fertility, but the genetic correlation suggests that BCS (at some stages of lactation) might help to alleviate the unfavorable effect of selection for higher yield on fertility.

  1. Inferior frontal gyrus preserves working memory and emotional learning under conditions of impaired noradrenergic signaling

    Directory of Open Access Journals (Sweden)

    Benjamin eBecker

    2013-12-01

    Full Text Available Compensation has been widely applied to explain neuroimaging findings in neuropsychiatric patients. Functional compensation is often invoked when patients display equal performance and increased neural activity in comparison to healthy controls. According to the compensatory hypothesis increased activity allows the brain to maintain cognitive performance despite underlying neuropathological changes. Due to methodological and pathology-related issues, however, the functional relevance of the increased activity and the specific brain regions involved in the compensatory response remain unclear. An experimental approach that allows a transient induction of compensatory responses in the healthy brain could help to overcome these issues. To this end we used the nonselective beta-blocker propranolol to pharmacologically induce sub-optimal noradrenergic signaling in healthy participants. In two independent fMRI experiments participants received either placebo or propranolol before they underwent a cognitive challenge (experiment 1: working memory; experiment 2: emotional learning: Pavlovian fear conditioning. In experiment 1 propranolol had no effects on working memory performance, but evoked stronger activity in the left inferior frontal gyrus (IFG. In experiment 2 propranolol produced no effects on emotional memory formation, but evoked stronger activity in the right IFG. The present finding that sub-optimal beta-adrenergic signaling did not disrupt performance and concomitantly increased IFG activity is consistent with, and extends, current perspectives on functional compensation. Together, our findings suggest that under conditions of impaired noradrenergic signaling, heightened activity in brain regions located within the cognitive control network, particularly the IFG, may reflect compensatory operations subserving the maintenance of behavioral performance.

  2. The Patient Educator Presentation in Dental Education: Reinforcing the Importance of Learning About Rare Conditions.

    Science.gov (United States)

    Edwards, Paul C; Graham, Jasmine; Oling, Rebecca; Frantz, Kate E

    2016-05-01

    The aim of this study was to determine whether a patient educator presentation (PEP) on pemphigus vulgaris would increase second-year dental students' awareness of the importance of learning about rare conditions and improve their retention of rare disease knowledge. The study involved students' subjective assessments of a PEP experience at two U.S. dental schools. In this mixed methods study, cross-sectional data were obtained by surveys and in-depth interviews. Questions focused on students' assessment of the messages acquired from the PEP and its likely impact on their future clinical care. At University 1, students completed paper surveys with open-ended questions and participated in a focus group. At University 2, students completed an online survey consisting of rating scale and open-ended questions. Responses to open-ended questions were categorized into themes. At University 1, 79 students (out of a possible 102; response rate 77.5%) completed the survey, and an additional ten students participated in a focus group. At University 2, 30 students (out of a possible 104; response rate 28.8%) completed the survey. At Universities 1 and 2, 88% and 100%, respectively, of respondents stated the PEP would influence their future clinical decision making. The vast majority of respondents (94% and 100% at University 1 and University 2, respectively) were of the opinion that the personal testimonial from a patient would help them recall information about pemphigus vulgaris in five years' time. Respondents from both universities commented that the PEP emphasized the importance of not dismissing a patient's concerns. These results suggest that a presentation by a patient with a rare condition can be an effective educational tool for preclinical dental students.

  3. Promising Therapeutics with Natural Bioactive Compounds for Improving Learning and Memory — A Review of Randomized Trials

    Directory of Open Access Journals (Sweden)

    Jin-Yong Choi

    2012-09-01

    Full Text Available Cognitive disorders can be associated with brain trauma, neurodegenerative disease or as a part of physiological aging. Aging in humans is generally associated with deterioration of cognitive performance and, in particular, learning and memory. Different therapeutic approaches are available to treat cognitive impairment during physiological aging and neurodegenerative or psychiatric disorders. Traditional herbal medicine and numerous plants, either directly as supplements or indirectly in the form of food, improve brain functions including memory and attention. More than a hundred herbal medicinal plants have been traditionally used for learning and memory improvement, but only a few have been tested in randomized clinical trials. Here, we will enumerate those medicinal plants that show positive effects on various cognitive functions in learning and memory clinical trials. Moreover, besides natural products that show promising effects in clinical trials, we briefly discuss medicinal plants that have promising experimental data or initial clinical data and might have potential to reach a clinical trial in the near future.

  4. From conditioning to learning communities: implications of fifty years of research in e-learning interaction design

    Directory of Open Access Journals (Sweden)

    Andrew Ravenscroft

    2003-12-01

    Full Text Available This paper will consider e-learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e-learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné, cognitivist (Pask, Piaget and Papert, situated (Lave, Wenger and Seely-Brown, socioconstructivist (Vygotsky, socio-cultural (Nardi and Engestrom and community-based (Wenger and Preece. Emerging from this review is the argument that effective elearning usually requires, or involves, high-quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e-learning.

  5. E-learning or educational leaflet: does it make a difference in oral health promotion? A clustered randomized trial.

    Science.gov (United States)

    Al Bardaweel, Susan; Dashash, Mayssoon

    2018-05-10

    The early recognition of technology together with great ability to use computers and smart systems have promoted researchers to investigate the possibilities of utilizing technology for improving health care in children. The aim of this study was to compare between the traditional educational leaflets and E-applications in improving oral health knowledge, oral hygiene and gingival health in schoolchildren of Damascus city, Syria. A clustered randomized controlled trial at two public primary schools was performed. About 220 schoolchildren aged 10-11 years were included in this study and grouped into two clusters. Children in Leaflet cluster received oral health education through leaflets, while children in E-learning cluster received oral health education through an E-learning program. A questionnaire was designed to register information related to oral health knowledge and to record Plaque and Gingival indices. Questionnaire administration and clinical assessment were undertaken at baseline, 6 and at 12 weeks of oral health education. Data was analysed using one way repeated measures ANOVA, post hoc Bonferroni test and independent samples t-test. Leaflet cluster (107 participants) had statistically significant better oral health knowledge than E-learning cluster (104 participants) at 6 weeks (P E-learning cluster:100 participants). The mean knowledge gain compared to baseline was higher in Leaflet cluster than in E-learning cluster. A significant reduction in the PI means at 6 weeks and 12 weeks was observed in both clusters (P E-learning cluster at 6 weeks (P E-learning cluster at 6 weeks (P < 0.05) and 12 weeks (P < 0.05). Traditional educational leaflets are an effective tool in the improvement of both oral health knowledge as well as clinical indices of oral hygiene and care among Syrian children. Leaflets can be used in school-based oral health education for a positive outcome. Australian New Zealand Clinical Trials Registry ( ACTRN

  6. CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

    Science.gov (United States)

    McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

    2014-06-01

    Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

  7. Characterisation of mental health conditions in social media using Informed Deep Learning

    Science.gov (United States)

    Gkotsis, George; Oellrich, Anika; Velupillai, Sumithra; Liakata, Maria; Hubbard, Tim J. P.; Dobson, Richard J. B.; Dutta, Rina

    2017-03-01

    The number of people affected by mental illness is on the increase and with it the burden on health and social care use, as well as the loss of both productivity and quality-adjusted life-years. Natural language processing of electronic health records is increasingly used to study mental health conditions and risk behaviours on a large scale. However, narrative notes written by clinicians do not capture first-hand the patients’ own experiences, and only record cross-sectional, professional impressions at the point of care. Social media platforms have become a source of ‘in the moment’ daily exchange, with topics including well-being and mental health. In this study, we analysed posts from the social media platform Reddit and developed classifiers to recognise and classify posts related to mental illness according to 11 disorder themes. Using a neural network and deep learning approach, we could automatically recognise mental illness-related posts in our balenced dataset with an accuracy of 91.08% and select the correct theme with a weighted average accuracy of 71.37%. We believe that these results are a first step in developing methods to characterise large amounts of user-generated content that could support content curation and targeted interventions.

  8. Reciprocal learning with task cards for teaching Basic Life Support (BLS): investigating effectiveness and the effect of instructor expertise on learning outcomes. A randomized controlled trial.

    Science.gov (United States)

    Iserbyt, Peter; Mols, Liesbet; Charlier, Nathalie; De Meester, Sophie

    2014-01-01

    Basic Life Support (BLS) education in secondary schools and universities is often neglected or outsourced because teachers indicate not feeling competent to teach this content. Investigate reciprocal learning with task cards as instructional model for teaching BLS and the effect of instructor expertise in BLS on learning outcomes. There were 175 students (mean age = 18.9 years) randomized across a reciprocal/BLS instructor (RBI) group, a reciprocal/non-BLS instructor (RNI) group, and a traditional/BLS instructor group (TBI). In the RBI and RNI group, students were taught BLS through reciprocal learning with task cards. The instructor in the RBI group was certified in BLS by the European Resuscitation Council. In the TBI, students were taught BLS by a certified instructor according to the Belgian Red Cross instructional model. Student performance was assessed 1 day (intervention) and 3 weeks after intervention (retention). At retention, significantly higher BLS performances were found in the RBI group (M = 78%), p = 0.007, ES = 0.25, and the RNI group (M = 80%), p < 0.001, Effect Size (ES) = .36, compared to the TBI (M = 73%). Significantly more students remembered and performed all BLS skills in the experimental groups at intervention and retention. No differences in BLS performance were found between the reciprocal groups. Ventilation volumes and flow rates were significantly better in the TBI at intervention and retention. Reciprocal learning with task cards is a valuable model for teaching BLS when instructors are not experienced or skilled in BLS. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Learning Binomial Probability Concepts with Simulation, Random Numbers and a Spreadsheet

    Science.gov (United States)

    Rochowicz, John A., Jr.

    2005-01-01

    This paper introduces the reader to the concepts of binomial probability and simulation. A spreadsheet is used to illustrate these concepts. Random number generators are great technological tools for demonstrating the concepts of probability. Ideas of approximation, estimation, and mathematical usefulness provide numerous ways of learning…

  10. Learning Mathematics in a Visuospatial Format: A Randomized, Controlled Trial of Mental Abacus Instruction

    Science.gov (United States)

    Barner, David; Alvarez, George; Sullivan, Jessica; Brooks, Neon; Srinivasan, Mahesh; Frank, Michael C.

    2016-01-01

    Mental abacus (MA) is a technique of performing fast, accurate arithmetic using a mental image of an abacus; experts exhibit astonishing calculation abilities. Over 3 years, 204 elementary school students (age range at outset: 5-7 years old) participated in a randomized, controlled trial to test whether MA expertise (a) can be acquired in standard…

  11. Can Babies Learn to Read? A Randomized Trial of Baby Media

    Science.gov (United States)

    Neuman, Susan B.; Kaefer, Tanya; Pinkham, Ashley; Strouse, Gabrielle

    2014-01-01

    Targeted to children as young as 3 months old, there is a growing number of baby media products that claim to teach babies to read. This randomized controlled trial was designed to examine this claim by investigating the effects of a best-selling baby media product on reading development. One hundred and seventeen infants, ages 9 to 18 months,…

  12. Policy-into-practice for rheumatoid arthritis: randomized controlled trial and cohort study of e-learning targeting improved physiotherapy management.

    Science.gov (United States)

    Fary, Robyn E; Slater, Helen; Chua, Jason; Ranelli, Sonia; Chan, Madelynn; Briggs, Andrew M

    2015-07-01

    To examine the effectiveness of a physiotherapy-specific, web-based e-learning platform, "RAP-el," in best-practice management of rheumatoid arthritis (RA) using a single-blind, randomized controlled trial (RCT) and prospective cohort study. Australian-registered physiotherapists were electronically randomized into intervention and control groups. The intervention group accessed RAP-eL over 4 weeks. Change in self-reported confidence in knowledge and skills was compared between groups at the end of the RCT using linear regression conditioned for baseline scores by a blinded assessor, using intent-to-treat analysis. Secondary outcomes included physiotherapists' satisfaction with RA management and responses to RA-relevant clinical statements and practice-relevant vignettes. Retention was evaluated in a cohort study 8 weeks after the RCT. Eighty physiotherapists were randomized into the intervention and 79 into the control groups. Fifty-six and 48, respectively, provided baseline data. Significant between-group differences were observed for change in confidence in knowledge (mean difference 8.51; 95% confidence interval [95% CI] 6.29, 10.73; effect size 1.62) and skills (mean difference 7.26; 95% CI 5.1, 9.4; effect size 1.54), with the intervention group performing better. Satisfaction in ability to manage RA, 4 of the 6 clinical statements, and responses to vignettes demonstrated significant improvement in the intervention group. Although 8-week scores showed declines in most outcomes, their clinical significance remains uncertain. RAP-eL can improve self-reported confidence, likely practice behaviors and satisfaction in physiotherapists' ability to manage people with RA, and improve their clinical knowledge in several areas of best-practice RA management in the short term. © 2015, American College of Rheumatology.

  13. Under which conditions does ICT have a positive effect on teaching and learning? A Call to Action

    NARCIS (Netherlands)

    Voogt, Joke; Knezek, G.; Cox, M.; Knezek, D.; ten Brummelhuis, A.C.A.

    2013-01-01

    Under which conditions does ICT have a positive effect on teaching and learning?’ This was the leading question of the International EDUsummIT in The Hague, the Netherlands. The bases for the discussion were the scholarly findings of the International Handbook of Information Technology in Primary

  14. Under Which Conditions Does ICT Have a Positive Effect on Teaching and Learning? A Call to Action

    Science.gov (United States)

    Voogt, J.; Knezek, G.; Cox, M.; Knezek, D.; ten Brummelhuis, A.

    2013-01-01

    "Under which conditions does ICT have a positive effect on teaching and learning?" This was the leading question of the International EDUsummIT in The Hague, the Netherlands. The bases for the discussion were the scholarly findings of the International Handbook of Information Technology in Primary and Secondary Education, a synthesis of research…

  15. "It's Not Like a Normal 9 to 5!": The Learning Journeys of Media Production Apprentices in Distributed Working Conditions

    Science.gov (United States)

    Lahiff, Ann; Guile, David

    2016-01-01

    An apprenticeship in media production in England is at the centre of this case study exploration. The context is exemplified by the organisation of the process of production around project teams and the development of project-based working cultures. Given these developments, the working conditions and learning opportunities presented to…

  16. The Effect of Cooperative Learning Approach Based on Conceptual Change Condition on Students' Understanding of Chemical Equilibrium Concepts

    Science.gov (United States)

    Bilgin, Ibrahim; Geban, Omer

    2006-01-01

    The purpose of this study is to investigate the effects of the cooperative learning approach based on conceptual change conditions over traditional instruction on 10th grade students' conceptual understanding and achievement of computational problems related to chemical equilibrium concepts. The subjects of this study consisted of 87 tenth grade…

  17. De-identifying Swedish clinical text - refinement of a gold standard and experiments with Conditional random fields

    Directory of Open Access Journals (Sweden)

    Dalianis Hercules

    2010-04-01

    Full Text Available Abstract Background In order to perform research on the information contained in Electronic Patient Records (EPRs, access to the data itself is needed. This is often very difficult due to confidentiality regulations. The data sets need to be fully de-identified before they can be distributed to researchers. De-identification is a difficult task where the definitions of annotation classes are not self-evident. Results We present work on the creation of two refined variants of a manually annotated Gold standard for de-identification, one created automatically, and one created through discussions among the annotators. The data is a subset from the Stockholm EPR Corpus, a data set available within our research group. These are used for the training and evaluation of an automatic system based on the Conditional Random Fields algorithm. Evaluating with four-fold cross-validation on sets of around 4-6 000 annotation instances, we obtained very promising results for both Gold Standards: F-score around 0.80 for a number of experiments, with higher results for certain annotation classes. Moreover, 49 false positives that were verified true positives were found by the system but missed by the annotators. Conclusions Our intention is to make this Gold standard, The Stockholm EPR PHI Corpus, available to other research groups in the future. Despite being slightly more time-consuming we believe the manual consensus gold standard is the most valuable for further research. We also propose a set of annotation classes to be used for similar de-identification tasks.

  18. Conditions for excellence in teaching in medical education: The Frankfurt Model to ensure quality in teaching and learning

    Directory of Open Access Journals (Sweden)

    Giesler, Marianne

    2017-10-01

    Full Text Available Background: There is general consensus that the organizational and administrative aspects of academic study programs exert an important influence on teaching and learning. Despite this, no comprehensive framework currently exists to describe the conditions that affect the quality of teaching and learning in medical education. The aim of this paper is to systematically and comprehensively identify these factors to offer academic administrators and decision makers interested in improving teaching a theory-based and, to an extent, empirically founded framework on the basis of which improvements in teaching quality can be identified and implemented.Method: Primarily, the issue was addressed by combining a theory-driven deductive approach with an experience based, “best evidence” one during the course of two workshops held by the GMA Committee on Personnel and Organizational Development in Academic Teaching (POiL in Munich (2013 and Frankfurt (2014. Two models describing the conditions relevant to teaching and learning (Euler/Hahn and Rindermann were critically appraised and synthesized into a new third model. Practical examples of teaching strategies that promote or hinder learning were compiled and added to the categories of this model and, to the extent possible, supported with empirical evidence.Based on this, a checklist with recommendations for optimizing general academic conditions was formulated.Results: The covers six categories: and These categories have been supplemented by the interests, motives and abilities of the actual teachers and students in this particular setting. The categories of this model provide the structure for a checklist in which recommendations for optimizing teaching are given.Conclusions: The checklist derived from the Frankfurt Model for ensuring quality in teaching and learning can be used for quality assurance and to improve the conditions under which teaching and learning take place in medical schools.

  19. Properties of a genetic algorithm extended by a random self-learning operator and asymmetric mutations: A convergence study for a task of powder-pattern indexing

    International Nuclear Information System (INIS)

    Paszkowicz, Wojciech

    2006-01-01

    Genetic algorithms represent a powerful global-optimisation tool applicable in solving tasks of high complexity in science, technology, medicine, communication, etc. The usual genetic-algorithm calculation scheme is extended here by introduction of a quadratic self-learning operator, which performs a partial local search for randomly selected representatives of the population. This operator is aimed as a minor deterministic contribution to the (stochastic) genetic search. The population representing the trial solutions is split into two equal subpopulations allowed to exhibit different mutation rates (so called asymmetric mutation). The convergence is studied in detail exploiting a crystallographic-test example of indexing of powder diffraction data of orthorhombic lithium copper oxide, varying such parameters as mutation rates and the learning rate. It is shown through the averaged (over the subpopulation) fitness behaviour, how the genetic diversity in the population depends on the mutation rate of the given subpopulation. Conditions and algorithm parameter values favourable for convergence in the framework of proposed approach are discussed using the results for the mentioned example. Further data are studied with a somewhat modified algorithm using periodically varying mutation rates and a problem-specific operator. The chance of finding the global optimum and the convergence speed are observed to be strongly influenced by the effective mutation level and on the self-learning level. The optimal values of these two parameters are about 6 and 5%, respectively. The periodic changes of mutation rate are found to improve the explorative abilities of the algorithm. The results of the study confirm that the applied methodology leads to improvement of the classical genetic algorithm and, therefore, it is expected to be helpful in constructing of algorithms permitting to solve similar tasks of higher complexity

  20. Hospital recruitment for a pragmatic cluster-randomized clinical trial: Lessons learned from the COMPASS study.

    Science.gov (United States)

    Johnson, Anna M; Jones, Sara B; Duncan, Pamela W; Bushnell, Cheryl D; Coleman, Sylvia W; Mettam, Laurie H; Kucharska-Newton, Anna M; Sissine, Mysha E; Rosamond, Wayne D

    2018-01-26

    Pragmatic randomized clinical trials are essential to determine the effectiveness of interventions in "real-world" clinical practice. These trials frequently use a cluster-randomized methodology, with randomization at the site level. Despite policymakers' increased interest in supporting pragmatic randomized clinical trials, no studies to date have reported on the unique recruitment challenges faced by cluster-randomized pragmatic trials. We investigated key challenges and successful strategies for hospital recruitment in the Comprehensive Post-Acute Stroke Services (COMPASS) study. The COMPASS study is designed to compare the effectiveness of the COMPASS model versus usual care in improving functional outcomes, reducing the numbers of hospital readmissions, and reducing caregiver strain for patients discharged home after stroke or transient ischemic attack. This model integrates early supported discharge planning with transitional care management, including nurse-led follow-up phone calls after 2, 30, and 60 days and an in-person clinic visit at 7-14 days involving a functional assessment and neurological examination. We present descriptive statistics of the characteristics of successfully recruited hospitals compared with all eligible hospitals, reasons for non-participation, and effective recruitment strategies. We successfully recruited 41 (43%) of 95 eligible North Carolina hospitals. Leading, non-exclusive reasons for non-participation included: insufficient staff or financial resources (n = 33, 61%), lack of health system support (n = 16, 30%), and lack of support of individual decision-makers (n = 11, 20%). Successful recruitment strategies included: building and nurturing relationships, engaging team members and community partners with a diverse skill mix, identifying gatekeepers, finding mutually beneficial solutions, having a central institutional review board, sharing published pilot data, and integrating contracts and review board

  1. A randomized trial of two e-learning strategies for teaching substance abuse management skills to physicians.

    Science.gov (United States)

    Harris, John M; Sun, Huaping

    2013-09-01

    To compare the educational effectiveness of two virtual patient (VP)-based e-learning strategies, versus no training, in improving physicians' substance abuse management knowledge, attitudes, self-reported behaviors, and decision making. The 2011-2012 study was a posttest-only, three-arm, randomized controlled trial in 90 resident and 30 faculty physicians from five adult medicine primary care training programs. The intervention was one of two 2-hour VP-based e-learning programs, designed by national experts to teach structured screening, brief interventions, referral, and treatment skills. One used traditional problem solving with feedback (unworked example), and the other incorporated an expert demonstration first, followed by problem solving with feedback (worked example). The main outcome measure was performance on the Physicians' Competence in Substance Abuse Test (P-CSAT, maximum score = 315), a self-administered, previously validated measure of physicians' competence in managing substance abuse. The survey was completed at the outset of the study and two months later. Overall P-CSAT scores were virtually identical (202-211, P > .05) between both intervention groups and the no-training control group at both times. Average faculty P-CSAT scores (221.9, 224.6) were significantly higher (P study did not provide evidence that a brief, worked example, VP-based e-learning program or a traditional, unworked, VP-based e-learning program was superior to no training in improving physicians' substance abuse management skills. The study did provide additional evidence that the P-CSAT distinguishes between physicians who should possess different levels of substance abuse management skills.

  2. Learning crisis resource management: Practicing versus an observational role in simulation training - a randomized controlled trial.

    Science.gov (United States)

    Lai, Anita; Haligua, Alexis; Dylan Bould, M; Everett, Tobias; Gale, Mark; Pigford, Ashlee-Ann; Boet, Sylvain

    2016-08-01

    Simulation training has been shown to be an effective way to teach crisis resource management (CRM) skills. Deliberate practice theory states that learners need to actively practice so that learning is effective. However, many residency programs have limited opportunities for learners to be "active" participants in simulation exercises. This study compares the effectiveness of learning CRM skills when being an active participant versus being an observer participant in simulation followed by a debriefing. Participants were randomized to two groups: active or observer. Active participants managed a simulated crisis scenario (pre-test) while paired observer participants viewed the scenario via video transmission. Then, a trained instructor debriefed participants on CRM principles. On the same day, each participant individually managed another simulated crisis scenario (post-test) and completed a post-test questionnaire. Two independent, blinded raters evaluated all videos using the Ottawa Global Rating Scale (GRS). Thirty-nine residents were included in the analysis. Normally distributed data were analyzed using paired and unpaired t-tests. Inter-rater reliability was 0.64. Active participants significantly improved from pre-test to post-test (P=0.015). There was no significant difference between the post-test performance of active participants compared to observer participants (P=0.12). We found that learning CRM principles was not superior when learners were active participants compared to being observers followed by debriefing. These findings challenge the deliberate practice theory claiming that learning requires active practice. Assigning residents as observers in simulation training and involving them in debriefing is still beneficial. Copyright © 2016 Société française d'anesthésie et de réanimation (Sfar). Published by Elsevier Masson SAS. All rights reserved.

  3. Applying team-based learning of diagnostics for undergraduate students: assessing teaching effectiveness by a randomized controlled trial study.

    Science.gov (United States)

    Zeng, Rui; Xiang, Lian-Rui; Zeng, Jing; Zuo, Chuan

    2017-01-01

    We aimed to introduce team-based learning (TBL) as one of the teaching methods for diagnostics and to compare its teaching effectiveness with that of the traditional teaching methods. We conducted a randomized controlled trial on diagnostics teaching involving 111 third-year medical undergraduates, using TBL as the experimental intervention, compared with lecture-based learning as the control, for teaching the two topics of symptomatology. Individual Readiness Assurance Test (IRAT)-baseline and Group Readiness Assurance Test (GRAT) were performed in members of each TBL subgroup. The scores in Individual Terminal Test 1 (ITT1) immediately after class and Individual Terminal Test 2 (ITT2) 1 week later were compared between the two groups. The questionnaire and interview were also implemented to survey the attitude of students and teachers toward TBL. There was no significant difference between the two groups in ITT1 (19.85±4.20 vs 19.70±4.61), while the score of the TBL group was significantly higher than that of the control group in ITT2 (19.15±3.93 vs 17.46±4.65). In the TBL group, the scores of the two terminal tests after the teaching intervention were significantly higher than the baseline test score of individuals. IRAT-baseline, ITT1, and ITT2 scores of students at different academic levels in the TBL teaching exhibited significant differences, but the ITT1-IRAT-baseline and ITT2-IRAT-baseline indicated no significant differences among the three subgroups. Our TBL in symptomatology approach was highly accepted by students in the improvement of interest and self-directed learning and resulted in an increase in knowledge acquirements, which significantly improved short-term test scores compared with lecture-based learning. TBL is regarded as an effective teaching method worthy of promoting.

  4. Microcultures and Informal Learning: A Heuristic Guiding Analysis of Conditions for Informal Learning in Local Higher Education Workplaces

    Science.gov (United States)

    Roxå, Torgny; Mårtensson, Katarina

    2015-01-01

    This article contributes to knowledge about learning in workgroups, so called "microcultures" in higher education. It argues that socially constructed and institutionalised traditions, recurrent practices, and tacit assumptions in the various microcultures influence academic teachers towards certain behaviour. In line with this…

  5. PROGRAMS FOR MODELLING RANDOM EVENTS FOR THE SAKE OF LEARNING BOTH PROGRAMMING AND MATHEMATICS

    Directory of Open Access Journals (Sweden)

    Y. Gayev

    2015-04-01

    Full Text Available MATLAB-programs of some discrete random event has been developed and intended (1 as an exercise at the study of Algorithmization and Programming Course, and (2 for carrying out some "experiments" by lecturing the Course of Probability and Statistics Theory, or at its self-study by students. The programs allows to do several probabilistic experiments in a necessary amount M, using the random number generator, to count up frequency of "favorable events" appearance and compare it to theoretical probability. This displays the Law of large numbers, i.e. approaching experimental results to theory with unlimited increase of М. The work, however, lies not only in this pragmatic result. It should encourage students to study problems of Probability Theory by means of creation appropriate computer codes. The most easy and quick way to this leads to MATLAB-environment. That is why the paper suggests principles of programming in it along with creation of graphical user interface (GUI.

  6. Mobile Augmented Reality as a Feature for Self-Oriented, Blended Learning in Medicine: Randomized Controlled Trial

    Science.gov (United States)

    2017-01-01

    Background Advantages of mobile Augmented Reality (mAR) application-based learning versus textbook-based learning were already shown in a previous study. However, it was unclear whether the augmented reality (AR) component was responsible for the success of the self-developed app or whether this was attributable to the novelty of using mobile technology for learning. Objective The study’s aim was to test the hypothesis whether there is no difference in learning success between learners who employed the mobile AR component and those who learned without it to determine possible effects of mAR. Also, we were interested in potential emotional effects of using this technology. Methods Forty-four medical students (male: 25, female: 19, mean age: 22.25 years, standard deviation [SD]: 3.33 years) participated in this study. Baseline emotional status was evaluated using the Profile of Mood States (POMS) questionnaire. Dermatological knowledge was ascertained using a single choice (SC) test (10 questions). The students were randomly assigned to learn 45 min with either a mobile learning method with mAR (group A) or without AR (group B). Afterwards, both groups were again asked to complete the previous questionnaires. AttrakDiff 2 questionnaires were used to evaluate the perceived usability as well as pragmatic and hedonic qualities. For capturing longer term effects, after 14 days, all participants were again asked to complete the SC questionnaire. All evaluations were anonymous, and descriptive statistics were calculated. For hypothesis testing, an unpaired signed-rank test was applied. Results For the SC tests, there were only minor differences, with both groups gaining knowledge (average improvement group A: 3.59 [SD 1.48]; group B: 3.86 [SD 1.51]). Differences between both groups were statistically insignificant (exact Mann Whitney U, U=173.5; P=.10; r=.247). However, in the follow-up SC test after 14 days, group A had retained more knowledge (average decrease of the

  7. Mobile Augmented Reality as a Feature for Self-Oriented, Blended Learning in Medicine: Randomized Controlled Trial.

    Science.gov (United States)

    Noll, Christoph; von Jan, Ute; Raap, Ulrike; Albrecht, Urs-Vito

    2017-09-14

    Advantages of mobile Augmented Reality (mAR) application-based learning versus textbook-based learning were already shown in a previous study. However, it was unclear whether the augmented reality (AR) component was responsible for the success of the self-developed app or whether this was attributable to the novelty of using mobile technology for learning. The study's aim was to test the hypothesis whether there is no difference in learning success between learners who employed the mobile AR component and those who learned without it to determine possible effects of mAR. Also, we were interested in potential emotional effects of using this technology. Forty-four medical students (male: 25, female: 19, mean age: 22.25 years, standard deviation [SD]: 3.33 years) participated in this study. Baseline emotional status was evaluated using the Profile of Mood States (POMS) questionnaire. Dermatological knowledge was ascertained using a single choice (SC) test (10 questions). The students were randomly assigned to learn 45 min with either a mobile learning method with mAR (group A) or without AR (group B). Afterwards, both groups were again asked to complete the previous questionnaires. AttrakDiff 2 questionnaires were used to evaluate the perceived usability as well as pragmatic and hedonic qualities. For capturing longer term effects, after 14 days, all participants were again asked to complete the SC questionnaire. All evaluations were anonymous, and descriptive statistics were calculated. For hypothesis testing, an unpaired signed-rank test was applied. For the SC tests, there were only minor differences, with both groups gaining knowledge (average improvement group A: 3.59 [SD 1.48]; group B: 3.86 [SD 1.51]). Differences between both groups were statistically insignificant (exact Mann Whitney U, U=173.5; P=.10; r=.247). However, in the follow-up SC test after 14 days, group A had retained more knowledge (average decrease of the number of correct answers group A: 0

  8. Estimation of genotype X environment interactions, in a grassbased system, for milk yield, body condition score,and body weight using random regression models

    NARCIS (Netherlands)

    Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

    2003-01-01

    (Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.

  9. Lack of effect of Pitressin on the learning ability of Brattleboro rats with diabetes insipidus using positively reinforced operant conditioning.

    Science.gov (United States)

    Laycock, J F; Gartside, I B

    1985-08-01

    Brattleboro rats with hereditary hypothalamic diabetes insipidus (BDI) received daily subcutaneous injections of vasopressin in the form of Pitressin tannate (0.5 IU/24 hr). They were initially deprived of food and then trained to work for food reward in a Skinner box to a fixed ratio of ten presses for each pellet received. Once this schedule had been learned the rats were given a discrimination task daily for seven days. The performances of these BDI rats were compared with those of rats of the parent Long Evans (LE) strain receiving daily subcutaneous injections of vehicle (arachis oil). Comparisons were also made between these two groups of treated animals and untreated BDI and LE rats studied under similar conditions. In the initial learning trial, both control and Pitressin-treated BDI rats performed significantly better, and manifested less fear initially, than the control or vehicle-injected LE rats when first placed in the Skinner box. Once the initial task had been learned there was no marked difference in the discrimination learning between control or treated BDI and LE animals. These results support the view that vasopressin is not directly involved in all types of learning behaviour, particularly those involving positively reinforced operant conditioning.

  10. Task Experience as a Boundary Condition for the Negative Effects of Irrelevant Information on Learning

    NARCIS (Netherlands)

    G. Rop (Gertjan); M. van Wermeskerken (Margot); J.A. de Nooijer (Jacqueline); P.P.J.L. Verkoeijen (Peter); T.A.J.M. van Gog (Tamara)

    2016-01-01

    textabstractResearch on multimedia learning has shown that learning is hampered when a multimedia message includes extraneous information that is not relevant for the task, because processing the extraneous information uses up scarce attention and working memory resources. However, eye-tracking

  11. Task Experience as a Boundary Condition for the Negative Effects of Irrelevant Information on Learning

    Science.gov (United States)

    Rop, Gertjan; van Wermeskerken, Margot; de Nooijer, Jacqueline A.; Verkoeijen, Peter P. J. L.; van Gog, Tamara

    2018-01-01

    Research on multimedia learning has shown that learning is hampered when a multimedia message includes extraneous information that is not relevant for the task, because processing the extraneous information uses up scarce attention and working memory resources. However, eye-tracking research suggests that task experience might be a boundary…

  12. Simulating Conditions of Learned Helplessness: The Effects of Interventions and Attributions.

    Science.gov (United States)

    Donovan, Wilberta L.; Leavitt, Lewis A.

    1985-01-01

    Using a version of the "learned helplessness" paradigm, assesses mothers' performance on a solvable task following pretreatments that involved exposure to an infant cry but that differed in the mothers' ability to exert control over termination of the cry. Proposes that learned helplessness models are relevant to the study of…

  13. Deep Learning as an Individual, Conditional, and Contextual Influence on First-Year Student Outcomes

    Science.gov (United States)

    Reason, Robert D.; Cox, Bradley E.; McIntosh, Kadian; Terenzini, Patrick T.

    2010-01-01

    For years, educators have drawn a distinction between deep cognitive processing and surface-level cognitive processing, with the former resulting in greater learning. In recent years, researchers at NSSE have created DEEP Learning scales, which consist of items related to students' experiences which are believed to encourage deep processing. In…

  14. The role of conditioning, learning and dopamine in sexual behavior: a narrative review of animal and human studies.

    Science.gov (United States)

    Brom, Mirte; Both, Stephanie; Laan, Ellen; Everaerd, Walter; Spinhoven, Philip

    2014-01-01

    Many theories of human sexual behavior assume that sexual stimuli obtain arousing properties through associative learning processes. It is widely accepted that classical conditioning contributes to the etiology of both normal and maladaptive human behaviors. Despite the hypothesized importance of basic learning processes in sexual behavior, research on classical conditioning of the sexual response in humans is scarce. In the present paper, animal studies and studies in humans on the role of pavlovian conditioning on sexual responses are reviewed. Animal research shows robust, direct effects of conditioning processes on partner- and place preference. On the contrast, the empirical research with humans in this area is limited and earlier studies within this field are plagued by methodological confounds. Although recent experimental demonstrations of human sexual conditioning are neither numerous nor robust, sexual arousal showed to be conditionable in both men and women. The present paper serves to highlight the major empirical findings and to renew the insight in how stimuli can acquire sexually arousing value. Hereby also related neurobiological processes in reward learning are discussed. Finally, the connections between animal and human research on the conditionability of sexual responses are discussed, and suggestions for future directions in human research are given. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Contextual Change After Fear Acquisition Affects Conditioned Responding and the Time Course of Extinction Learning-Implications for Renewal Research.

    Science.gov (United States)

    Sjouwerman, Rachel; Niehaus, Johanna; Lonsdorf, Tina B

    2015-01-01

    Context plays a central role in retrieving (fear) memories. Accordingly, context manipulations are inherent to most return of fear (ROF) paradigms (in particular renewal), involving contextual changes after fear extinction. Context changes are, however, also often embedded during earlier stages of ROF experiments such as context changes between fear acquisition and extinction (e.g., in ABC and ABA renewal). Previous studies using these paradigms have however focused exclusively on the context switch after extinction (i.e., renewal). Thus, the possibility of a general effect of context switch on conditioned responding that may not be conditional to preceding extinction learning remains unstudied. Hence, the current study investigated the impact of a context switch between fear acquisition and extinction on immediate conditioned responding and on the time-course of extinction learning by using a multimodal approach. A group that underwent contextual change after fear conditioning (AB; n = 36) was compared with a group without a contextual change from acquisition to extinction (AA; n = 149), while measuring physiological (skin conductance and fear potentiated startle) measures and subjective fear ratings. Contextual change between fear acquisition and extinction had a pronounced effect on both immediate conditioned responding and on the time course of extinction learning in skin conductance responses and subjective fear ratings. This may have important implications for the mechanisms underlying and the interpretation of the renewal effect (i.e., contextual switch after extinction). Consequently, future studies should incorporate designs and statistical tests that disentangle general effects of contextual change from genuine ROF effects.

  16. Current distributions in superconducting wires subject to a random orientation magnetic field, and corresponding to the Tokamak usual conditions

    International Nuclear Information System (INIS)

    Artaud, J.F.

    1994-01-01

    The main themes of this thesis are: review of superconductivity principles; critical current in a random orientation magnetic field; the MHD model applied to superconductors (with comprehensive calculation of the field in a plate type conductor); the magnetization created by a variation of a random orientation magnetic field; the electric field in a superconductor in steady or quasi-steady state (MHD displacement, pinning and thermal effects). 145 figs., 166 refs

  17. Influence network linkages across implementation strategy conditions in a randomized controlled trial of two strategies for scaling up evidence-based practices in public youth-serving systems.

    Science.gov (United States)

    Palinkas, Lawrence A; Holloway, Ian W; Rice, Eric; Brown, C Hendricks; Valente, Thomas W; Chamberlain, Patricia

    2013-11-14

    Given the importance of influence networks in the implementation of evidence-based practices and interventions, it is unclear whether such networks continue to operate as sources of information and advice when they are segmented and disrupted by randomization to different implementation strategy conditions. The present study examines the linkages across implementation strategy conditions of social influence networks of leaders of youth-serving systems in 12 California counties participating in a randomized controlled trial of community development teams (CDTs) to scale up use of an evidence-based practice. Semi-structured interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. A web-based survey collected additional quantitative data on information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) to examine linkages between treatment and standard conditions. Of those network members who were affiliated with a county (n = 137), only 6 (4.4%) were directly connected to a member of the opposite implementation strategy condition; 19 (13.9%) were connected by two steps or fewer to a member of the opposite implementation strategy condition; 64 (46.7%) were connected by three or fewer steps to a member of the opposite implementation strategy condition. Most of the indirect steps between individuals who were in different implementation strategy conditions were connections involving a third non-county organizational entity that had an important role in the trial in keeping the implementation strategy conditions separate. When these entities were excluded, the CDT network exhibited fewer components and significantly higher betweenness centralization than did the standard condition network. Although the integrity of the RCT in this instance was not compromised by study participant influence

  18. Unsupervised Learning Through Randomized Algorithms for High-Volume High-Velocity Data (ULTRA-HV).

    Energy Technology Data Exchange (ETDEWEB)

    Pinar, Ali [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kolda, Tamara G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Wake Forest Univ., Winston-Salem, MA (United States); Ballard, Grey [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mahoney, Michael [Univ. of California, Berkeley, CA (United States)

    2018-01-01

    Through long-term investments in computing, algorithms, facilities, and instrumentation, DOE is an established leader in massive-scale, high-fidelity simulations, as well as science-leading experimentation. In both cases, DOE is generating more data than it can analyze and the problem is intensifying quickly. The need for advanced algorithms that can automatically convert the abundance of data into a wealth of useful information by discovering hidden structures is well recognized. Such efforts however, are hindered by the massive volume of the data and its high velocity. Here, the challenge is developing unsupervised learning methods to discover hidden structure in high-volume, high-velocity data.

  19. Procedures can be learned on the Web: a randomized study of ultrasound-guided vascular access training.

    Science.gov (United States)

    Chenkin, Jordan; Lee, Shirley; Huynh, Thien; Bandiera, Glen

    2008-10-01

    Web-based learning has several potential advantages over lectures, such as anytime-anywhere access, rich multimedia, and nonlinear navigation. While known to be an effective method for learning facts, few studies have examined the effectiveness of Web-based formats for learning procedural skills. The authors sought to determine whether a Web-based tutorial is at least as effective as a didactic lecture for learning ultrasound-guided vascular access (UGVA). Participating staff emergency physicians (EPs) and junior emergency medicine (EM) residents with no UGVA experience completed a precourse test and were randomized to either a Web-based or a didactic group. The Web-based group was instructed to use an online tutorial and the didactic group attended a lecture. Participants then practiced on simulators and live models without any further instruction. Following a rest period, participants completed a four-station objective structured clinical examination (OSCE), a written examination, and a postcourse questionnaire. Examination results were compared using a noninferiority data analysis with a 10% margin of difference. Twenty-one residents and EPs participated in the study. There were no significant differences in mean OSCE scores (absolute difference = -2.8%; 95% confidence interval [CI] = -9.3% to 3.8%) or written test scores (absolute difference = -1.4%; 95% CI = -7.8% to 5.0%) between the Web group and the didactic group. Both groups demonstrated similar improvements in written test scores (26.1% vs. 25.8%; p = 0.95). Ninety-one percent (10/11) of the Web group and 80% (8/10) of the didactic group participants found the teaching format to be effective (p = 0.59). Our Web-based tutorial was at least as effective as a traditional didactic lecture for teaching the knowledge and skills essential for UGVA. Participants expressed high satisfaction with this teaching technology. Web-based teaching may be a useful alternative to didactic teaching for learning procedural

  20. Applying team-based learning of diagnostics for undergraduate students: assessing teaching effectiveness by a randomized controlled trial study

    Directory of Open Access Journals (Sweden)

    Zeng R

    2017-03-01

    Full Text Available Rui Zeng,1,* Lian-rui Xiang,2,* Jing Zeng,3 Chuan Zuo4 1Department of Cardiovascular Diseases, 2Department of Public Affairs Development, 3Department of Internal Medicine, 4Department of Rheumatology and Immunology, West China Hospital, School of Clinic Medicine, Sichuan University, Chengdu, People’s Republic of China *These authors contributed equally to this work Background: We aimed to introduce team-based learning (TBL as one of the teaching methods for diagnostics and to compare its teaching effectiveness with that of the traditional teaching methods.Methods: We conducted a randomized controlled trial on diagnostics teaching involving 111 third-year medical undergraduates, using TBL as the experimental intervention, compared with lecture-based learning as the control, for teaching the two topics of symptomatology. Individual Readiness Assurance Test (IRAT-baseline and Group Readiness Assurance Test (GRAT were performed in members of each TBL subgroup. The scores in Individual Terminal Test 1 (ITT1 immediately after class and Individual Terminal Test 2 (ITT2 1 week later were compared between the two groups. The questionnaire and interview were also implemented to survey the attitude of students and teachers toward TBL.Results: There was no significant difference between the two groups in ITT1 (19.85±4.20 vs 19.70±4.61, while the score of the TBL group was significantly higher than that of the control group in ITT2 (19.15±3.93 vs 17.46±4.65. In the TBL group, the scores of the two terminal tests after the teaching intervention were significantly higher than the baseline test score of individuals. IRAT-baseline, ITT1, and ITT2 scores of students at different academic levels in the TBL teaching exhibited significant differences, but the ITT1-IRAT-baseline and ITT2-IRAT-baseline indicated no significant differences among the three subgroups.Conclusion: Our TBL in symptomatology approach was highly accepted by students in the improvement

  1. Development and assessment of an e-learning course on breast imaging for radiographers: a stratified randomized controlled trial.

    Science.gov (United States)

    Moreira, Inês C; Ventura, Sandra Rua; Ramos, Isabel; Rodrigues, Pedro Pereira

    2015-01-05

    Mammography is considered the best imaging technique for breast cancer screening, and the radiographer plays an important role in its performance. Therefore, continuing education is critical to improving the performance of these professionals and thus providing better health care services. Our goal was to develop an e-learning course on breast imaging for radiographers, assessing its efficacy, effectiveness, and user satisfaction. A stratified randomized controlled trial was performed with radiographers and radiology students who already had mammography training, using pre- and post-knowledge tests, and satisfaction questionnaires. The primary outcome was the improvement in test results (percentage of correct answers), using intention-to-treat and per-protocol analysis. A total of 54 participants were assigned to the intervention (20 students plus 34 radiographers) with 53 controls (19+34). The intervention was completed by 40 participants (11+29), with 4 (2+2) discontinued interventions, and 10 (7+3) lost to follow-up. Differences in the primary outcome were found between intervention and control: 21 versus 4 percentage points (pp), Peffect in radiographers (23 pp vs 4 pp; P=.004) but was unclear in students (18 pp vs 5 pp; P=.098). Nonetheless, differences in students' posttest results were found (88% vs 63%; P=.003), which were absent in pretest (63% vs 63%; P=.106). The per-protocol analysis showed a higher effect (26 pp vs 2 pp; Pe-learning course is effective, especially for radiographers, which highlights the need for continuing education.

  2. Development and Assessment of an E-Learning Course on Breast Imaging for Radiographers: A Stratified Randomized Controlled Trial

    Science.gov (United States)

    Ventura, Sandra Rua; Ramos, Isabel; Rodrigues, Pedro Pereira

    2015-01-01

    Background Mammography is considered the best imaging technique for breast cancer screening, and the radiographer plays an important role in its performance. Therefore, continuing education is critical to improving the performance of these professionals and thus providing better health care services. Objective Our goal was to develop an e-learning course on breast imaging for radiographers, assessing its efficacy, effectiveness, and user satisfaction. Methods A stratified randomized controlled trial was performed with radiographers and radiology students who already had mammography training, using pre- and post-knowledge tests, and satisfaction questionnaires. The primary outcome was the improvement in test results (percentage of correct answers), using intention-to-treat and per-protocol analysis. Results A total of 54 participants were assigned to the intervention (20 students plus 34 radiographers) with 53 controls (19+34). The intervention was completed by 40 participants (11+29), with 4 (2+2) discontinued interventions, and 10 (7+3) lost to follow-up. Differences in the primary outcome were found between intervention and control: 21 versus 4 percentage points (pp), Pe-learning course is effective, especially for radiographers, which highlights the need for continuing education. PMID:25560547

  3. Effect of an e-Learning Tool on Expectations and Satisfaction Following Total Knee Arthroplasty: A Randomized Controlled Trial.

    Science.gov (United States)

    Culliton, Sharon E; Bryant, Dianne M; MacDonald, Steven J; Hibbert, Kathy M; Chesworth, Bert M

    2018-07-01

    Orthopedic surgeons recognize patient expectations of total knee arthroplasty (TKA) can be managed through education. E-learning is the application of educational technology. The objective of this study was to evaluate whether an e-learning tool could affect whether patients' expectations were met and they were satisfied 1 year following TKA. Patients with osteoarthritis from the London Health Sciences Centre, Canada, were randomly assigned to either a control group (n = 207) receiving standard patient education or an intervention group (n = 209) using the e-learning tool in addition to the standard. We used a web-based system with permuted block sizes, stratified by surgeon and first or second TKA. Preoperative measures were completed following the patients' preadmission clinic visit. Postoperative patient-reported outcome measures were completed at 6 weeks, 3 months, and 1 year after TKA. One year after TKA, risk difference was used to determine between-group differences for patient satisfaction and expectations being met. One year postoperatively, the risk that expectations of patients were not met was 21.8% in the control group and 21.4% in the intervention group for an adjusted risk difference of 1.3% (95% confidence interval, -7.8% to 10.4%, P = .78). The proportion of patients satisfied with their TKA at 1 year postoperative was 78.6% in the intervention and 78.2% in the control groups. There was no between-group difference at 1 year between intervention and control groups for either the risk that expectations of patients were not met or the proportion of patients who were dissatisfied with their TKA. Copyright © 2018 Elsevier Inc. All rights reserved.

  4. E-learning in order to improve drug prescription for hospitalized older patients: a cluster-randomized controlled study.

    Science.gov (United States)

    Franchi, Carlotta; Tettamanti, Mauro; Djade, Codjo Dgnefa; Pasina, Luca; Mannucci, Pier Mannuccio; Onder, Graziano; Gussoni, Gualberto; Manfellotto, Dario; Bonassi, Stefano; Salerno, Francesco; Nobili, Alessandro

    2016-07-01

    The aim of the study was to evaluate the effect of an e-learning educational program meant to foster the quality of drug prescription in hospitalized elderly patients. Twenty geriatric and internal medicine wards were randomized to intervention (e-learning educational program) or control (basic geriatric pharmacology notions). Logistic regression analysis was used in order to assess the effect of the intervention on the use of potentially inappropriate medication (PIM, primary outcome) at hospital discharge. Secondary outcomes were a reduced prevalence of at least one potential drug-drug interaction (DDI) and potentially severe DDI at discharge. Mortality rate and incidence of re-hospitalizations were other secondary outcomes assessed at the 12-month follow-up. A total of 697 patients (347 in the intervention and 350 in the control arms) were enrolled. No difference in the prevalence of PIM at discharge was found between arms (OR 1.29 95%CI 0.87-1.91). We also found no decrease in the prevalence of DDI (OR 0.67 95%CI 0.34-1.28) and potentially severe DDI (OR 0.86 95%CI 0.63-1.15) at discharge, nor in mortality rates and incidence of re-hospitalization at 12-month follow-up. This e-learning educational program had no clear effect on the quality of drug prescription and clinical outcomes in hospitalized elderly patients. Given the high prevalence of PIMs and potential DDIs recorded in the frame of this study, other approaches should be developed in order to improve the quality of drug prescription in this population. © 2016 The British Pharmacological Society.

  5. Learning classifier systems with memory condition to solve non-Markov problems

    OpenAIRE

    Zang, Zhaoxiang; Li, Dehua; Wang, Junying

    2012-01-01

    In the family of Learning Classifier Systems, the classifier system XCS has been successfully used for many applications. However, the standard XCS has no memory mechanism and can only learn optimal policy in Markov environments, where the optimal action is determined solely by the state of current sensory input. In practice, most environments are partially observable environments on agent's sensation, which are also known as non-Markov environments. Within these environments, XCS either fail...

  6. Expatriate’s and Host Country National’s Professional Learning in Adverse Conditions

    DEFF Research Database (Denmark)

    Romani, Laurence; Lorenzen, Julie; Holck, Lotte

    important professional learning, which leads them to become better officers once back in Denmark. This contribution, based on a qualitative case study, intends to elicit this unexpected finding and to contribute to further theory development in expatriate adjustment literature. In the present case, no cross-cultural....... This case provides an example of how an environment perceived as foreign and undesirable turns out to be beneficial for individual learning...

  7. EHLS at School: school-age follow-up of the Early Home Learning Study cluster randomized controlled trial.

    Science.gov (United States)

    Westrupp, Elizabeth M; Bennett, Clair; Cullinane, Meabh; Hackworth, Naomi J; Berthelsen, Donna; Reilly, Sheena; Mensah, Fiona K; Gold, Lisa; Bennetts, Shannon K; Levickis, Penny; Nicholson, Jan M

    2018-05-02

    Targeted interventions during early childhood can assist families in providing strong foundations that promote children's health and wellbeing across the life course. There is growing recognition that longer follow-up times are necessary to assess intervention outcomes, as effects may change as children develop. The Early Home Learning Study, or 'EHLS', comprised two cluster randomized controlled superiority trials of a brief parenting intervention, smalltalk, aimed at supporting parents to strengthen the early childhood home learning environment of infants (6-12 months) or toddlers (12-36 months). Results showed sustained improvements in parent-child interactions and the home environment at the 32 week follow-up for the toddler but not the infant trial. The current study will therefore follow up the EHLS toddler cohort to primary school age, with the aim of addressing a gap in literature concerning long-term effects of early childhood interventions focused on improving school readiness and later developmental outcomes. 'EHLS at School' is a school-aged follow-up study of the toddler cluster randomized controlled trial (n = 1226). Data will be collected by parent-, child- and teacher-report questionnaires, recorded observations of parent-child interactions, and direct child assessment when children are aged 7.5 years old. Data linkage will provide additional data on child health and academic functioning at ages 5, 8 and 10 years. Child outcomes will be compared for families allocated to standard/usual care (control) versus those allocated to the smalltalk program (group program only or group program with additional home coaching). Findings from The Early Home Learning Study provided evidence of the benefits of the smalltalk intervention delivered via facilitated playgroups for parents of toddlers. The EHLS at School Study aims to examine the long-term outcomes of this initiative to determine whether improvements in the quality of the parent

  8. Impact of cap-assisted colonoscopy on the learning curve and quality in colonoscopy: a randomized controlled trial.

    Science.gov (United States)

    Tang, Zhouwen; Zhang, Daniel S; Thrift, Aaron P; Patel, Kalpesh K

    2018-03-01

    Colonoscopy competency assessment in trainees traditionally has been informal. Comprehensive metrics such as the Assessment of Competency in Endoscopy (ACE) tool suggest that competency thresholds are higher than assumed. Cap-assisted colonoscopy (CAC) may improve competency, but data regarding novice trainees are lacking. We compared CAC versus standard colonoscopy (SC) performed by novice trainees in a randomized controlled trial. All colonoscopies performed by 3 gastroenterology fellows without prior experience were eligible for the study. Exclusion criteria included patient age 90 years, pregnancy, prior colon resection, diverticulitis, colon obstruction, severe hematochezia, referral for EMR, or a procedure done without patient sedation. Patients were randomized to either CAC or SC in a 1:1 fashion. The primary outcome was the independent cecal intubation rate (ICIR). Secondary outcomes were cecal intubation time, polyp detection rate, polyp miss rate, adenoma detection rate, ACE tool scores, and cumulative summation learning curves. A total of 203 colonoscopies were analyzed, 101 in CAC and 102 in SC. CAC resulted in a significantly higher cecal intubation rate, at 79.2% in CAC compared with 66.7% in SC (P = .04). Overall cecal intubation time was significantly shorter at 13.7 minutes for CAC versus 16.5 minutes for SC (P =.02). Cecal intubation time in the case of successful independent fellow intubation was not significantly different between CAC and SC (11.6 minutes vs 12.7 minutes; P = .29). Overall ACE tool motor and cognitive scores were higher with CAC. Learning curves for ICIR approached the competency threshold earlier with cap use but reached competency for only 1 fellow. The polyp detection rate, polyp miss rate, and adenoma detection rate were not significantly different between groups. CAC resulted in significant improvement in ICIR, overall ACE tool scores, and trend toward competency on learning curves when compared with SC in colonoscopy

  9. Can a single session of motor imagery promote motor learning of locomotion in older adults? A randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Nicholson VP

    2018-04-01

    Full Text Available Vaughan P Nicholson,1 Justin WL Keogh,2–4 Nancy L Low Choy1 1School of Physiotherapy, Australian Catholic University, Brisbane, QLD, Australia; 2Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia; 3Human Potential Centre, AUT University, Auckland, New Zealand; 4Cluster for Health Improvement, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Sunshine Coast, QLD, Australia Purpose: To investigate the influence of a single session of locomotor-based motor imagery training on motor learning and physical performance. Patients and methods: Thirty independent adults aged >65 years took part in the randomized controlled trial. The study was conducted within an exercise science laboratory. Participants were randomly divided into three groups following baseline locomotor testing: motor imagery training, physical training, and control groups. The motor imagery training group completed 20 imagined repetitions of a locomotor task, the physical training group completed 20 physical repetitions of a locomotor task, and the control group spent 25 minutes playing mentally stimulating games on an iPad. Imagined and physical performance times were measured for each training repetition. Gait speed (preferred and fast, timed-up-and-go, gait variability and the time to complete an obstacle course were completed before and after the single training session. Results: Motor learning occurred in both the motor imagery training and physical training groups. Motor imagery training led to refinements in motor planning resulting in imagined movements better matching the physically performed movement at the end of training. Motor imagery and physical training also promoted improvements in some locomotion outcomes as demonstrated by medium to large effect size improvements after training for fast gait speed and timed-up-and-go. There were no training effects on gait variability. Conclusion: A single session

  10. Successive and discrete spaced conditioning in active avoidance learning in young and aged zebrafish.

    Science.gov (United States)

    Yang, Peng; Kajiwara, Riki; Tonoki, Ayako; Itoh, Motoyuki

    2018-05-01

    We designed an automated device to study active avoidance learning abilities of zebrafish. Open source tools were used for the device control, statistical computing, and graphic outputs of data. Using the system, we developed active avoidance tests to examine the effects of trial spacing and aging on learning. Seven-month-old fish showed stronger avoidance behavior as measured by color preference index with discrete spaced training as compared to successive spaced training. Fifteen-month-old fish showed a similar trend, but with reduced cognitive abilities compared with 7-month-old fish. Further, in 7-month-old fish, an increase in learning ability during trials was observed with discrete, but not successive, spaced training. In contrast, 15-month-old fish did not show increase in learning ability during trials. Therefore, these data suggest that discrete spacing is more effective for learning than successive spacing, with the zebrafish active avoidance paradigm, and that the time course analysis of active avoidance using discrete spaced training is useful to detect age-related learning impairment. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

  11. eEduHeart I: A Multicenter, Randomized, Controlled Trial Investigating the Effectiveness of a Cardiac Web-Based eLearning Platform - Rationale and Study Design.

    Science.gov (United States)

    Frederix, Ines; Vandenberk, Thijs; Janssen, Leen; Geurden, Anne; Vandervoort, Pieter; Dendale, Paul

    Cardiac telerehabilitation includes, in its most comprehensive format, telemonitoring, telecoaching, social interaction, and eLearning. The specific role of eLearning, however, was seldom assessed. The aim of eEduHeart I is to investigate the medium-term effectiveness of the addition of a cardiac web-based eLearing platform to conventional cardiac care. In this prospective, multicenter randomized, controlled trial, 1,000 patients with coronary artery disease will be randomized 1:1 to an intervention group (receiving 1-month unrestricted access to the cardiac eLearning platform in addition to conventional cardiac care) or to conventional cardiac care alone. The primary endpoint is health-related quality of life, assessed by the HeartQoL questionnaire at the 1- and 3-month follow-ups. Secondary endpoints include pathology-specific knowledge and self-reported eLearning platform user experience. Data on the eLearning platform usage will be gathered through web logging during the study period. eEduHeart I will be one of the first studies to report on the added value of eLearning. If the intervention is proven effective, current cardiac telerehabilitation programs can be augmented by including eLearning, too. The platform can then be used as a model for other chronic diseases in which patient education plays a key role. © 2016 S. Karger AG, Basel.

  12. Deep Learning the Quantum Phase Transitions in Random Electron Systems: Applications to Three Dimensions

    Science.gov (United States)

    Ohtsuki, Tomi; Ohtsuki, Tomoki

    2017-04-01

    Three-dimensional random electron systems undergo quantum phase transitions and show rich phase diagrams. Examples of the phases are the band gap insulator, Anderson insulator, strong and weak topological insulators, Weyl semimetal, and diffusive metal. As in the previous paper on two-dimensional quantum phase transitions [J. Phys. Soc. Jpn. 85, 123706 (2016)], we use an image recognition algorithm based on a multilayered convolutional neural network to identify which phase the eigenfunction belongs to. The Anderson model for localization-delocalization transition, the Wilson-Dirac model for topological insulators, and the layered Chern insulator model for Weyl semimetal are studied. The situation where the standard transfer matrix approach is not applicable is also treated by this method.

  13. Duration of the Unconditioned Stimulus in Appetitive Conditioning of Honeybees Differentially Impacts Learning, Long-Term Memory Strength, and the Underlying Protein Synthesis

    Science.gov (United States)

    Marter, Kathrin; Grauel, M. Katharina; Lewa, Carmen; Morgenstern, Laura; Buckemüller, Christina; Heufelder, Karin; Ganz, Marion; Eisenhardt, Dorothea

    2014-01-01

    This study examines the role of stimulus duration in learning and memory formation of honeybees ("Apis mellifera"). In classical appetitive conditioning honeybees learn the association between an initially neutral, conditioned stimulus (CS) and the occurrence of a meaningful stimulus, the unconditioned stimulus (US). Thereby the CS…

  14. A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.

    Science.gov (United States)

    Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias

    2008-12-01

    We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.

  15. Preschool Teachers Can Use a PBS KIDS Transmedia Curriculum Supplement to Support Young Children's Mathematics Learning: Results of a Randomized Controlled Trial

    Science.gov (United States)

    Llorente, Carlin; Pasnik, Shelley; Moorthy, Savitha; Hupert, Naomi; Rosenfeld, Deborah; Gerard, Sarah

    2015-01-01

    The current study, a randomized controlled trial, explores how technology and educational transmedia resources can enhance prekindergarten math teaching and learning in preschools, especially those serving children who may be at risk for academic difficulties due to economic and social disadvantages. This research is part of a multi-year summative…

  16. New machine learning tools for predictive vegetation mapping after climate change: Bagging and Random Forest perform better than Regression Tree Analysis

    Science.gov (United States)

    L.R. Iverson; A.M. Prasad; A. Liaw

    2004-01-01

    More and better machine learning tools are becoming available for landscape ecologists to aid in understanding species-environment relationships and to map probable species occurrence now and potentially into the future. To thal end, we evaluated three statistical models: Regression Tree Analybib (RTA), Bagging Trees (BT) and Random Forest (RF) for their utility in...

  17. Effect of Peer-Led Team Learning (PLTL) on Student Achievement, Attitude, and Self-Concept in College General Chemistry in Randomized and Quasi Experimental Designs

    Science.gov (United States)

    Chan, Julia Y. K.; Bauer, Christopher F.

    2015-01-01

    This study investigated exam achievement and affective characteristics of students in general chemistry in a fully-randomized experimental design, contrasting Peer-Led Team Learning (PLTL) participation with a control group balanced for time-on-task and study activity. This study population included two independent first-semester courses with…

  18. Separation of random telegraph sSignals from 1/f noise in MOSFETs under constant and switched bias conditions

    NARCIS (Netherlands)

    Kolhatkar, J.S.; Vandamme, L.K.J.; Salm, Cora; Wallinga, Hans

    2004-01-01

    The low-frequency noise power spectrum of small dimension MOSFETs is dominated by Lorentzians arising from random telegraph signals (RTS). The low-frequency noise is observed to decrease when the devices are periodically switched 'off'. The technique of determining the statistical lifetimes and

  19. Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations.

    Directory of Open Access Journals (Sweden)

    Florian Lesaint

    2014-02-01

    Full Text Available Reinforcement Learning has greatly influenced models of conditioning, providing powerful explanations of acquired behaviour and underlying physiological observations. However, in recent autoshaping experiments in rats, variation in the form of Pavlovian conditioned responses (CRs and associated dopamine activity, have questioned the classical hypothesis that phasic dopamine activity corresponds to a reward prediction error-like signal arising from a classical Model-Free system, necessary for Pavlovian conditioning. Over the course of Pavlovian conditioning using food as the unconditioned stimulus (US, some rats (sign-trackers come to approach and engage the conditioned stimulus (CS itself - a lever - more and more avidly, whereas other rats (goal-trackers learn to approach the location of food delivery upon CS presentation. Importantly, although both sign-trackers and goal-trackers learn the CS-US association equally well, only in sign-trackers does phasic dopamine activity show classical reward prediction error-like bursts. Furthermore, neither the acquisition nor the expression of a goal-tracking CR is dopamine-dependent. Here we present a computational model that can account for such individual variations. We show that a combination of a Model-Based system and a revised Model-Free system can account for the development of distinct CRs in rats. Moreover, we show that revising a classical Model-Free system to individually process stimuli by using factored representations can explain why classical dopaminergic patterns may be observed for some rats and not for others depending on the CR they develop. In addition, the model can account for other behavioural and pharmacological results obtained using the same, or similar, autoshaping procedures. Finally, the model makes it possible to draw a set of experimental predictions that may be verified in a modified experimental protocol. We suggest that further investigation of factored representations in

  20. Modelling Individual Differences in the Form of Pavlovian Conditioned Approach Responses: A Dual Learning Systems Approach with Factored Representations

    Science.gov (United States)

    Lesaint, Florian; Sigaud, Olivier; Flagel, Shelly B.; Robinson, Terry E.; Khamassi, Mehdi

    2014-01-01

    Reinforcement Learning has greatly influenced models of conditioning, providing powerful explanations of acquired behaviour and underlying physiological observations. However, in recent autoshaping experiments in rats, variation in the form of Pavlovian conditioned responses (CRs) and associated dopamine activity, have questioned the classical hypothesis that phasic dopamine activity corresponds to a reward prediction error-like signal arising from a classical Model-Free system, necessary for Pavlovian conditioning. Over the course of Pavlovian conditioning using food as the unconditioned stimulus (US), some rats (sign-trackers) come to approach and engage the conditioned stimulus (CS) itself – a lever – more and more avidly, whereas other rats (goal-trackers) learn to approach the location of food delivery upon CS presentation. Importantly, although both sign-trackers and goal-trackers learn the CS-US association equally well, only in sign-trackers does phasic dopamine activity show classical reward prediction error-like bursts. Furthermore, neither the acquisition nor the expression of a goal-tracking CR is dopamine-dependent. Here we present a computational model that can account for such individual variations. We show that a combination of a Model-Based system and a revised Model-Free system can account for the development of distinct CRs in rats. Moreover, we show that revising a classical Model-Free system to individually process stimuli by using factored representations can explain why classical dopaminergic patterns may be observed for some rats and not for others depending on the CR they develop. In addition, the model can account for other behavioural and pharmacological results obtained using the same, or similar, autoshaping procedures. Finally, the model makes it possible to draw a set of experimental predictions that may be verified in a modified experimental protocol. We suggest that further investigation of factored representations in

  1. Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations.

    Science.gov (United States)

    Lesaint, Florian; Sigaud, Olivier; Flagel, Shelly B; Robinson, Terry E; Khamassi, Mehdi

    2014-02-01

    Reinforcement Learning has greatly influenced models of conditioning, providing powerful explanations of acquired behaviour and underlying physiological observations. However, in recent autoshaping experiments in rats, variation in the form of Pavlovian conditioned responses (CRs) and associated dopamine activity, have questioned the classical hypothesis that phasic dopamine activity corresponds to a reward prediction error-like signal arising from a classical Model-Free system, necessary for Pavlovian conditioning. Over the course of Pavlovian conditioning using food as the unconditioned stimulus (US), some rats (sign-trackers) come to approach and engage the conditioned stimulus (CS) itself - a lever - more and more avidly, whereas other rats (goal-trackers) learn to approach the location of food delivery upon CS presentation. Importantly, although both sign-trackers and goal-trackers learn the CS-US association equally well, only in sign-trackers does phasic dopamine activity show classical reward prediction error-like bursts. Furthermore, neither the acquisition nor the expression of a goal-tracking CR is dopamine-dependent. Here we present a computational model that can account for such individual variations. We show that a combination of a Model-Based system and a revised Model-Free system can account for the development of distinct CRs in rats. Moreover, we show that revising a classical Model-Free system to individually process stimuli by using factored representations can explain why classical dopaminergic patterns may be observed for some rats and not for others depending on the CR they develop. In addition, the model can account for other behavioural and pharmacological results obtained using the same, or similar, autoshaping procedures. Finally, the model makes it possible to draw a set of experimental predictions that may be verified in a modified experimental protocol. We suggest that further investigation of factored representations in computational

  2. Contextual change after fear acquisition affects conditioned responding and the time course of extinction learning – Implications for renewal research

    Directory of Open Access Journals (Sweden)

    Rachel eSjouwerman

    2015-12-01

    Full Text Available Context plays a central role in retrieving (fear memories. Accordingly, context manipulations are inherent to most return of fear (ROF paradigms (in particular renewal, involving contextual changes after fear extinction. Context changes are, however, also often embedded during earlier stages of ROF experiments such as context changes between fear acquisition and extinction (e.g. in ABC and ABA renewal. Previous studies using these paradigms have however focused exclusively on the context switch after extinction (i.e. renewal. Thus, the possibility of a general effect of a context switch on conditioned responding that may not be conditional to preceding extinction learning remains unstudied.Hence, the current study investigated the impact of a context switch between fear acquisition and extinction on immediate conditioned responding and on the time-course of extinction learning by using a multimodal approach. A group that underwent contextual change after fear conditioning (AB; n = 36 was compared with a group without a contextual change from acquisition to extinction (AA; n = 149, while measuring autonomic (skin conductance and fear potentiated startle measures and subjective fear ratings. Contextual change between fear acquisition and extinction had a pronounced effect on both immediate conditioned responding and on the time course of extinction learning in skin conductance responses and subjective fear ratings. This may have important implications for the mechanisms underlying and the interpretation of the renewal effect (i.e. contextual switch after extinction. Consequently, future studies should incorporate designs and statistical tests that disentangle general effects of contextual change from genuine ROF effects.

  3. Nuclear interactions for 15 GeV/c protons and pions under random and channeling conditions in germanium single crystals

    CERN Document Server

    Andersen, S K; Fich, O.; Golovchenko, J.A.; Nielsen, Henry; Schiott, H.E.; Uggerhoj, E.; Vraast-Thomsen, C.; Charpak, Georges; Petersen, G.; Sauli, F.; Ponpon, J.P.; Siffert, P.

    1978-01-01

    Strong directional effects for nuclear-reaction probabilities have been observed when 15 GeV/ c protons and pions are incident on a 4.2 mm Ge single crystal. In the random situation, our measurements are in agreement with Glauber's theory of diffraction scattering and with published particle-production data. When protons are incident in an aligned direction, the nuclear-reaction probabilities fall off very drastically but in a way which is in agreement with standard channeling theory; for aligned negative pions where a simple channeling theory is lacking, there is some experimental indication that nuclear-reaction probabilities are enhanced compared to the corresponding random rates, an indication which is supported by detailed computer-simulation studies.

  4. Effects of pre-conditioning on behavior and physiology of horses during a standardised learning task.

    Directory of Open Access Journals (Sweden)

    Kate Fenner

    Full Text Available Rein tension is used to apply pressure to control both ridden and unridden horses. The pressure is delivered by equipment such as the bit, which may restrict voluntary movement and cause changes in behavior and physiology. Managing the effects of such pressure on arousal level and behavioral indicators will optimise horse learning outcomes. This study examined the effect of training horses to turn away from bit pressure on cardiac outcomes and behavior (including responsiveness over the course of eight trials in a standardised learning task. The experimental procedure consisted of a resting phase, treatment/control phase, standardised learning trials requiring the horses (n = 68 to step backwards in response to bit pressure and a recovery phase. As expected, heart rate increased (P = 0.028 when the handler applied rein tension during the treatment phase. The amount of rein tension required to elicit a response during treatment was higher on the left than the right rein (P = 0.009. Total rein tension required for trials reduced (P < 0.001 as they progressed, as did time taken (P < 0.001 and steps taken (P < 0.001. The incidence of head tossing decreased (P = 0.015 with the progression of the trials and was higher (P = 0.018 for the control horses than the treated horses. These results suggest that preparing the horses for the lesson and slightly raising their arousal levels, improved learning outcomes.

  5. Lateralized Implicit Sequence Learning in Uni- and Bi-Manual Conditions

    Science.gov (United States)

    Schmitz, Remy; Pasquali, Antoine; Cleeremans, Axel; Peigneux, Philippe

    2013-01-01

    It has been proposed that the right hemisphere (RH) is better suited to acquire novel material whereas the left hemisphere (LH) is more able to process well-routinized information. Here, we ask whether this potential dissociation also manifests itself in an implicit learning task. Using a lateralized version of the serial reaction time task (SRT),…

  6. Cholinergic Modulation during Acquisition of Olfactory Fear Conditioning Alters Learning and Stimulus Generalization in Mice

    Science.gov (United States)

    Pavesi, Eloisa; Gooch, Allison; Lee, Elizabeth; Fletcher, Max L.

    2013-01-01

    We investigated the role of cholinergic neurotransmission in olfactory fear learning. Mice receiving pairings of odor and foot shock displayed fear to the trained odor the following day. Pretraining injections of the nicotinic antagonist mecamylamine had no effect on subsequent freezing, while the muscarinic antagonist scopolamine significantly…

  7. Engagement in Learning after Errors at Work: Enabling Conditions and Types of Engagement

    Science.gov (United States)

    Bauer, Johannes; Mulder, Regina H.

    2013-01-01

    This article addresses two research questions concerning nurses' engagement in social learning activities after errors at work. Firstly, we investigated how this engagement relates to nurses' interpretations of the error situation and perceptions of a safe team climate. The results indicate that the individual estimation of an error as relevant to…

  8. Motor learning strategies in basketball players and its implications for ACL injury prevention: a randomized controlled trial.

    Science.gov (United States)

    Benjaminse, Anne; Otten, Bert; Gokeler, Alli; Diercks, Ron L; Lemmink, Koen A P M

    2017-08-01

    Adding external focus of attention (EF, focus on the movement effect) may optimize current anterior cruciate ligament (ACL) injury prevention programmes. The purpose of the current study was to investigate the effects of an EF, by a visual stimulus and an internal focus, by a verbal stimulus during unexpected sidestep cutting in female and male athletes and how these effects remained over time. Ninety experienced basketball athletes performed sidestep cutting manoeuvres in three sessions (S1, S2 and S3). In this randomized controlled trial, athletes were allocated to three groups: visual (VIS), verbal (VER) and control (CTRL). Kinematics and kinetics were collected at the time of peak knee frontal plane moment. Males in the VIS group showed a larger vertical ground reaction force (S1: 25.4 ± 3.1 N/kg, S2: 25.8 ± 2.9 N/kg, S3: 25.2 ± 3.2 N/kg) and knee flexion moments (S1: -3.8 ± 0.9 Nm/kg, S2: -4.0 ± 1.2 Nm/kg, S3: -3.9 ± 1.3 Nm/kg) compared to the males in the VER and CTRL groups and to the females in the VIS group (p knee valgus moment and the females in the VER group reduced knee varus moment over time (n.s.). Male subjects clearly benefit from visual feedback. Females may need different feedback modes to learn a correct movement pattern. Sex-specific learning preferences may have to be acknowledged in day by day practice. Adding video instruction or feedback to regular training regimens when teaching athletes safe movement patterns and providing individual feedback might target suboptimal long-term results and optimize ACL injury prevention programmes. I.

  9. Mirnacle: machine learning with SMOTE and random forest for improving selectivity in pre-miRNA ab initio prediction.

    Science.gov (United States)

    Marques, Yuri Bento; de Paiva Oliveira, Alcione; Ribeiro Vasconcelos, Ana Tereza; Cerqueira, Fabio Ribeiro

    2016-12-15

    MicroRNAs (miRNAs) are key gene expression regulators in plants and animals. Therefore, miRNAs are involved in several biological processes, making the study of these molecules one of the most relevant topics of molecular biology nowadays. However, characterizing miRNAs in vivo is still a complex task. As a consequence, in silico methods have been developed to predict miRNA loci. A common ab initio strategy to find miRNAs in genomic data is to search for sequences that can fold into the typical hairpin structure of miRNA precursors (pre-miRNAs). The current ab initio approaches, however, have selectivity issues, i.e., a high number of false positives is reported, which can lead to laborious and costly attempts to provide biological validation. This study presents an extension of the ab initio method miRNAFold, with the aim of improving selectivity through machine learning techniques, namely, random forest combined with the SMOTE procedure that copes with imbalance datasets. By comparing our method, termed Mirnacle, with other important approaches in the literature, we demonstrate that Mirnacle substantially improves selectivity without compromising sensitivity. For the three datasets used in our experiments, our method achieved at least 97% of sensitivity and could deliver a two-fold, 20-fold, and 6-fold increase in selectivity, respectively, compared with the best results of current computational tools. The extension of miRNAFold by the introduction of machine learning techniques, significantly increases selectivity in pre-miRNA ab initio prediction, which optimally contributes to advanced studies on miRNAs, as the need of biological validations is diminished. Hopefully, new research, such as studies of severe diseases caused by miRNA malfunction, will benefit from the proposed computational tool.

  10. {sup 90}Y -PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction

    Energy Technology Data Exchange (ETDEWEB)

    Carlier, Thomas, E-mail: thomas.carlier@chu-nantes.fr [Department of Nuclear Medicine, University Hospital of Nantes, Place Alexis Ricordeau, Nantes 44093, France and CRCNA–UMR 892 INSERM 6299 CNRS, 8 quai Moncousu BP 70721, Nantes 44007 (France); Willowson, Kathy P. [Institute of Medical Physics, University of Sydney, Camperdown, New South Wales 2006 (Australia); Fourkal, Eugene [Department of Radiation Oncology, Allegheny General Hospital, Pittsburgh, Pennsylvania 15212 (United States); Bailey, Dale L. [Faculty of Health Sciences, University of Sydney, Lidcombe 2141, Australia and Department of Nuclear Medicine, Royal North Shore Hospital, St Leonards, New South Wales 2065 (Australia); Doss, Mohan [Department of Diagnostic Imaging, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111 (United States); Conti, Maurizio [Siemens Healthcare Molecular Imaging, 810 Innovation Drive, Knoxville, Tennessee 37932 (United States)

    2015-07-15

    Purpose: {sup 90}Y -positron emission tomography (PET) imaging is becoming a recognized modality for postinfusion quantitative assessment following radioembolization therapy. However, the extremely low counts and high random fraction associated with {sup 90}Y -PET may significantly impair both qualitative and quantitative results. The aim of this work was to study image quality and noise level in relation to the quantification and bias performance of two types of Siemens PET scanners when imaging {sup 90}Y and to compare experimental results with clinical data from two types of commercially available {sup 90}Y microspheres. Methods: Data were acquired on both Siemens Biograph TruePoint [non-time-of-flight (TOF)] and Biograph microcomputed tomography (mCT) (TOF) PET/CT scanners. The study was conducted in three phases. The first aimed to assess quantification and bias for different reconstruction methods according to random fraction and number of true counts in the scan. The NEMA 1994 PET phantom was filled with water with one cylindrical insert left empty (air) and the other filled with a solution of {sup 90}Y . The phantom was scanned for 60 min in the PET/CT scanner every one or two days. The second phase used the NEMA 2001 PET phantom to derive noise and image quality metrics. The spheres and the background were filled with a {sup 90}Y solution in an 8:1 contrast ratio and four 30 min acquisitions were performed over a one week period. Finally, 32 patient data (8 treated with Therasphere{sup ®} and 24 with SIR-Spheres{sup ®}) were retrospectively reconstructed and activity in the whole field of view and the liver was compared to theoretical injected activity. Results: The contribution of both bremsstrahlung and LSO trues was found to be negligible, allowing data to be decay corrected to obtain correct quantification. In general, the recovered activity for all reconstruction methods was stable over the range studied, with a small bias appearing at extremely

  11. (90)Y -PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction.

    Science.gov (United States)

    Carlier, Thomas; Willowson, Kathy P; Fourkal, Eugene; Bailey, Dale L; Doss, Mohan; Conti, Maurizio

    2015-07-01

    (90)Y -positron emission tomography (PET) imaging is becoming a recognized modality for postinfusion quantitative assessment following radioembolization therapy. However, the extremely low counts and high random fraction associated with (90)Y -PET may significantly impair both qualitative and quantitative results. The aim of this work was to study image quality and noise level in relation to the quantification and bias performance of two types of Siemens PET scanners when imaging (90)Y and to compare experimental results with clinical data from two types of commercially available (90)Y microspheres. Data were acquired on both Siemens Biograph TruePoint [non-time-of-flight (TOF)] and Biograph microcomputed tomography (mCT) (TOF) PET/CT scanners. The study was conducted in three phases. The first aimed to assess quantification and bias for different reconstruction methods according to random fraction and number of true counts in the scan. The NEMA 1994 PET phantom was filled with water with one cylindrical insert left empty (air) and the other filled with a solution of (90)Y . The phantom was scanned for 60 min in the PET/CT scanner every one or two days. The second phase used the NEMA 2001 PET phantom to derive noise and image quality metrics. The spheres and the background were filled with a (90)Y solution in an 8:1 contrast ratio and four 30 min acquisitions were performed over a one week period. Finally, 32 patient data (8 treated with Therasphere(®) and 24 with SIR-Spheres(®)) were retrospectively reconstructed and activity in the whole field of view and the liver was compared to theoretical injected activity. The contribution of both bremsstrahlung and LSO trues was found to be negligible, allowing data to be decay corrected to obtain correct quantification. In general, the recovered activity for all reconstruction methods was stable over the range studied, with a small bias appearing at extremely high random fraction and low counts for iterative algorithms

  12. 90Y -PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction

    International Nuclear Information System (INIS)

    Carlier, Thomas; Willowson, Kathy P.; Fourkal, Eugene; Bailey, Dale L.; Doss, Mohan; Conti, Maurizio

    2015-01-01

    Purpose: 90 Y -positron emission tomography (PET) imaging is becoming a recognized modality for postinfusion quantitative assessment following radioembolization therapy. However, the extremely low counts and high random fraction associated with 90 Y -PET may significantly impair both qualitative and quantitative results. The aim of this work was to study image quality and noise level in relation to the quantification and bias performance of two types of Siemens PET scanners when imaging 90 Y and to compare experimental results with clinical data from two types of commercially available 90 Y microspheres. Methods: Data were acquired on both Siemens Biograph TruePoint [non-time-of-flight (TOF)] and Biograph microcomputed tomography (mCT) (TOF) PET/CT scanners. The study was conducted in three phases. The first aimed to assess quantification and bias for different reconstruction methods according to random fraction and number of true counts in the scan. The NEMA 1994 PET phantom was filled with water with one cylindrical insert left empty (air) and the other filled with a solution of 90 Y . The phantom was scanned for 60 min in the PET/CT scanner every one or two days. The second phase used the NEMA 2001 PET phantom to derive noise and image quality metrics. The spheres and the background were filled with a 90 Y solution in an 8:1 contrast ratio and four 30 min acquisitions were performed over a one week period. Finally, 32 patient data (8 treated with Therasphere ® and 24 with SIR-Spheres ® ) were retrospectively reconstructed and activity in the whole field of view and the liver was compared to theoretical injected activity. Results: The contribution of both bremsstrahlung and LSO trues was found to be negligible, allowing data to be decay corrected to obtain correct quantification. In general, the recovered activity for all reconstruction methods was stable over the range studied, with a small bias appearing at extremely high random fraction and low counts for

  13. Learning by Preparing to Teach: Fostering Self-Regulatory Processes and Achievement during Complex Mathematics Problem Solving

    Science.gov (United States)

    Muis, Krista R.; Psaradellis, Cynthia; Chevrier, Marianne; Di Leo, Ivana; Lajoie, Susanne P.

    2016-01-01

    We developed an intervention based on the learning by teaching paradigm to foster self-regulatory processes and better learning outcomes during complex mathematics problem solving in a technology-rich learning environment. Seventy-eight elementary students were randomly assigned to 1 of 2 conditions: learning by preparing to teach, or learning for…

  14. Autonomous Scanning Probe Microscopy in Situ Tip Conditioning through Machine Learning.

    Science.gov (United States)

    Rashidi, Mohammad; Wolkow, Robert A

    2018-05-23

    Atomic-scale characterization and manipulation with scanning probe microscopy rely upon the use of an atomically sharp probe. Here we present automated methods based on machine learning to automatically detect and recondition the quality of the probe of a scanning tunneling microscope. As a model system, we employ these techniques on the technologically relevant hydrogen-terminated silicon surface, training the network to recognize abnormalities in the appearance of surface dangling bonds. Of the machine learning methods tested, a convolutional neural network yielded the greatest accuracy, achieving a positive identification of degraded tips in 97% of the test cases. By using multiple points of comparison and majority voting, the accuracy of the method is improved beyond 99%.

  15. A Machine-Learning Approach to Predict Main Energy Consumption under Realistic Operational Conditions

    DEFF Research Database (Denmark)

    Petersen, Joan P; Winther, Ole; Jacobsen, Daniel J

    2012-01-01

    The paper presents a novel and publicly available set of high-quality sensory data collected from a ferry over a period of two months and overviews exixting machine-learning methods for the prediction of main propulsion efficiency. Neural networks are applied on both real-time and predictive...... settings. Performance results for the real-time models are shown. The presented models were successfully developed in a trim optimisation application onboard a product tanker....

  16. Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

    Science.gov (United States)

    Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

    2018-02-01

    A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

  17. Conditioned Object Preference: An Alternative Approach to Measuring Reward Learning in Rats

    Science.gov (United States)

    Kennedy, Bruce C.; Kohli, Maulika; Maertens, Jamie J.; Marell, Paulina S.; Gewirtz, Jonathan C.

    2016-01-01

    Pavlovian conditioned approach behavior can be directed as much toward discrete cues as it is toward the environmental contexts in which those cues are encountered. The current experiments characterized a tendency of rats to approach object cues whose prior exposure had been paired with reward (conditioned object preference, COP). To demonstrate…

  18. Electrophysiological correlates of associative learning in smokers: A higher-order conditioning experiment

    NARCIS (Netherlands)

    M. Littel (Marianne); I.H.A. Franken (Ingmar)

    2012-01-01

    textabstractBackground: Classical conditioning has been suggested to play an important role in the development, maintenance, and relapse of tobacco smoking. Several studies have shown that initially neutral stimuli that are directly paired with smoking are able to elicit conditioned responses.

  19. Randomized controlled trial evaluating the temporal effects of high-intensity exercise on learning, short-term and long-term memory, and prospective memory.

    Science.gov (United States)

    Frith, Emily; Sng, Eveleen; Loprinzi, Paul D

    2017-11-01

    The broader purpose of this study was to examine the temporal effects of high-intensity exercise on learning, short-term and long-term retrospective memory and prospective memory. Among a sample of 88 young adult participants, 22 were randomized into one of four different groups: exercise before learning, control group, exercise during learning, and exercise after learning. The retrospective assessments (learning, short-term and long-term memory) were assessed using the Rey Auditory Verbal Learning Test. Long-term memory including a 20-min and 24-hr follow-up assessment. Prospective memory was assessed using a time-based procedure by having participants contact (via phone) the researchers at a follow-up time period. The exercise stimulus included a 15-min bout of progressive maximal exertion treadmill exercise. High-intensity exercise prior to memory encoding (vs. exercise during memory encoding or consolidation) was effective in enhancing long-term memory (for both 20-min and 24-h follow-up assessments). We did not observe a differential temporal effect of high-intensity exercise on short-term memory (immediate post-memory encoding), learning or prospective memory. The timing of high-intensity exercise may play an important role in facilitating long-term memory. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  20. E-learning interventions are comparable to user's manual in a randomized trial of training strategies for the AGREE II

    Directory of Open Access Journals (Sweden)

    Durocher Lisa D

    2011-07-01

    Full Text Available Abstract Background Practice guidelines (PGs are systematically developed statements intended to assist in patient and practitioner decisions. The AGREE II is the revised tool for PG development, reporting, and evaluation, comprised of 23 items, two global rating scores, and a new User's Manual. In this study, we sought to develop, execute, and evaluate the impact of two internet interventions designed to accelerate the capacity of stakeholders to use the AGREE II. Methods Participants were randomized to one of three training conditions. 'Tutorial'--participants proceeded through the online tutorial with a virtual coach and reviewed a PDF copy of the AGREE II. 'Tutorial + Practice Exercise'--in addition to the Tutorial, participants also appraised a 'practice' PG. For the practice PG appraisal, participants received feedback on how their scores compared to expert norms and formative feedback if scores fell outside the predefined range. 'AGREE II User's Manual PDF (control condition'--participants reviewed a PDF copy of the AGREE II only. All participants evaluated a test PG using the AGREE II. Outcomes of interest were learners' performance, satisfaction, self-efficacy, mental effort, time-on-task, and perceptions of AGREE II. Results No differences emerged between training conditions on any of the outcome measures. Conclusions We believe these results can be explained by better than anticipated performance of the AGREE II PDF materials (control condition or the participants' level of health methodology and PG experience rather than the failure of the online training interventions. Some data suggest the online tools may be useful for trainees new to this field; however, this requires further study.

  1. A randomized controlled trial of telemonitoring in older adults with multiple chronic conditions: the Tele-ERA study

    Directory of Open Access Journals (Sweden)

    Takahashi Paul Y

    2010-09-01

    Full Text Available Abstract Background Older adults with multiple chronic illnesses are at risk for worsening functional and medical status and hospitalization. Home telemonitoring may help slow this decline. This protocol of a randomized controlled trial was designed to help determine the impact of home telemonitoring on hospitalization. The specific aim of the study reads as follows: to determine the effectiveness of home telemonitoring compared with usual care in reducing the combined outcomes of hospitalization and emergency department visits in an at-risk population 60 years of age or older. Methods/Design Two-hundred patients with the highest 10% Mayo Clinic Elder Risk Assessment scores will be randomly assigned to one of two interventions. Home telemonitoring involves the use of a computer device, the Intel Health Guide, which records biometric and symptom data from patients in their homes. This information is monitored by midlevel providers associated with a primary care medical practice. Under the usual care scenario, patients make appointments with their providers as problems arise and use ongoing support such as a 24-hour nurse line. Patients will have initial evaluations of gait and quality of life using instruments such as the SF-12 Health Survey, the Kokmen Short Test of Mental Status, and the PHQ-9 health questionnaire. Patients will be followed for 1 year for primary outcomes of hospitalizations and emergency department visits. Secondary analysis will include quality of life, compliance with the device, and attitudes about telemonitoring. Sample size is based on an 80% power to detect a 36% difference between the two groups. The primary analysis will involve Cox proportional time-to-event analysis. Secondary analysis will use t-test comparisons for continuous variables and the chi square test for proportional analysis. Discussion Patients randomized to home telemonitoring will have daily assessments of their health status using the device

  2. The effect of methylphenidate on postural stability under single and dual task conditions in children with attention deficit hyperactivity disorder - a double blind randomized control trial.

    Science.gov (United States)

    Jacobi-Polishook, Talia; Shorer, Zamir; Melzer, Itshak

    2009-05-15

    To investigate the effects of Methylphenidate (MPH) on postural stability in attention deficit hyperactivity disorder (ADHD) children in single and dual task conditions. A randomized controlled double-blind study analyzing postural stability in 24 ADHD children before and after MPH vs. placebo treatments, in three task conditions: (1) Single task, standing still; (2) dual task, standing still performing a memory-attention demanding task; (3) standing still listening to music. MPH resulted in a significant improvement in postural stability during the dual task condition and while listening to music, with no equivalent improvement in placebo controls. MPH improves postural stability in ADHD, especially when an additional task is performed. This is probably due to enhanced attention abilities, thus contributing to improved balance control during performance of tasks that require attention. MPH remains to be studied as a potential drug treatment to improve balance control and physical functioning in other clinical populations.

  3. Learning from simple ebooks, online cases or classroom teaching when acquiring complex knowledge. A randomized controlled trial in respiratory physiology and pulmonology.

    Science.gov (United States)

    Worm, Bjarne Skjødt

    2013-01-01

    E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01). The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001), while the eCase group spent significantly more time on the subject (53 minutes, p<0.001) and logged into the system significantly more (2.8 vs 1.6, p<0.001). E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method.

  4. Infant rats can learn time intervals before the maturation of the striatum: evidence from odor fear conditioning

    Directory of Open Access Journals (Sweden)

    Julie eBoulanger Bertolus

    2014-05-01

    Full Text Available Interval timing refers to the ability to perceive, estimate and discriminate durations in the range of seconds to minutes. Very little is currently known about the ontogeny of interval timing throughout development. On the other hand, even though the neural circuit sustaining interval timing is a matter of debate, the striatum has been suggested to be an important component of the system and its maturation occurs around the third post-natal week in rats. The global aim of the present study was to investigate interval timing abilities at an age for which striatum is not yet mature. We used odor fear conditioning, as it can be applied to very young animals. In odor fear conditioning, an odor is presented to the animal and a mild footshock is delivered after a fixed interval. Adult rats have been shown to learn the temporal relationships between the odor and the shock after a few associations. The first aim of the present study was to assess the activity of the striatum during odor fear conditioning using 2-Deoxyglucose autoradiography during development in rats. The data showed that although fear learning was displayed at all tested ages, activation of the striatum was observed in adults but not in juvenile animals. Next, we assessed the presence of evidence of interval timing in ages before and after the inclusion of the striatum into the fear conditioning circuit. We used an experimental setup allowing the simultaneous recording of freezing and respiration that have been demonstrated to be sensitive to interval timing in adult rats. This enabled the detection of duration-related temporal patterns for freezing and/or respiration curves in infants as young as 12 days post-natal during odor-fear conditioning. This suggests that infants are able to encode time durations as well as and as quickly as adults while their striatum is not yet functional. Alternative networks possibly sustaining interval timing in infant rats are discussed.

  5. Repeated Remote Ischemic Conditioning Effect on Ankle-brachial Index in Diabetic Patients - A Randomized Control Trial

    Directory of Open Access Journals (Sweden)

    Najmeh Shahvazian

    2017-01-01

    Full Text Available Background: Remote ischemic preconditioning (RIPC is a phenomenon where a short period of ischemia in one organ protects against further ischemia in the other organs. We hypothesized that RIPC occurring in diabetic patients with ankle brachial index (ABI between 0.70 and 0.90 were included with peripheral arterial disease, would make the better coronary flow resulted in the increasing ABI. Materials and Methods: This randomized clinical trial study was done in the Afshar Cardiovascular Hospital in Yazd between 2013 and 2014. Sixty participants were randomly divided into two groups (intervention and control groups. The intervention group was undergoing RIPC, and the control group was tested without RIPC. RIPC was stimulated by giving three cycles of 5 min of ischemia followed by 5 min of reperfusion of both upper arms using a blood pressure cuff inflated to 200 mm Hg (n = 30. This was compared with no RIPC group which consisted of placing a deflated blood pressure cuff on the upper limbs (n = 30. Results: The mean of ABI level before intervention in the RIPC and control group group was 0.82 ± 0.055 and 0.83 ± 0.0603 (P = 0.347 respectively, with no significant difference. It was 0.86 ± 0.066 in the RIPC group compared the control 0.83 ± 0.0603 (P = 0.046. So levels of ABI were greater after intervention in the RIPC group. The mean of ABI level increase from 0.82 ± 0.05 to 0.86 ± 0.06 in RIPC group (P = 0.008. So the intervention group showed a significant increase in ABI. Conclusions: RIPC through using a simple, noninvasive technique, composing three cycles of 5 min-ischemia of both upper arms, showing a significant increase in ABI level in diabetic patients.

  6. Operant Conditioning Principles in the Treatment of Learning and Behavior Problems with Delinquent Boys

    Science.gov (United States)

    Bednar, Richard L.; And Others

    1970-01-01

    This study on operant conditioning showed that both groups showed significant improvement in reading skills from pretest to posttest, but that the reinforced group showed significantly more improvement than the nonreinforced group. (Author)

  7. Dumb and Lazy? A Comparison of Color Learning and Memory Retrieval in Drones and Workers of the Buff-Tailed Bumblebee, Bombus terrestris, by Means of PER Conditioning.

    Science.gov (United States)

    Lichtenstein, Leonie; Sommerlandt, Frank M J; Spaethe, Johannes

    2015-01-01

    More than 100 years ago, Karl von Frisch showed that honeybee workers learn and discriminate colors. Since then, many studies confirmed the color learning capabilities of females from various hymenopteran species. Yet, little is known about visual learning and memory in males despite the fact that in most bee species males must take care of their own needs and must find rewarding flowers to obtain food. Here we used the proboscis extension response (PER) paradigm to study the color learning capacities of workers and drones of the bumblebee, Bombus terrestris. Light stimuli were paired with sucrose reward delivered to the insects' antennae and inducing a reflexive extension of the proboscis. We evaluated color learning (i.e. conditioned PER to color stimuli) in absolute and differential conditioning protocols and mid-term memory retention was measured two hours after conditioning. Different monochromatic light stimuli in combination with neutral density filters were used to ensure that the bumblebees could only use chromatic and not achromatic (e.g. brightness) information. Furthermore, we tested if bees were able to transfer the learned information from the PER conditioning to a novel discrimination task in a Y-maze. Both workers and drones were capable of learning and discriminating between monochromatic light stimuli and retrieved the learned stimulus after two hours. Drones performed as well as workers during conditioning and in the memory test, but failed in the transfer test in contrast to workers. Our data clearly show that bumblebees can learn to associate a color stimulus with a sugar reward in PER conditioning and that both workers and drones reach similar acquisition and mid-term retention performances. Additionally, we provide evidence that only workers transfer the learned information from a Pavlovian to an operant situation.

  8. Dumb and Lazy? A Comparison of Color Learning and Memory Retrieval in Drones and Workers of the Buff-Tailed Bumblebee, Bombus terrestris, by Means of PER Conditioning.

    Directory of Open Access Journals (Sweden)

    Leonie Lichtenstein

    Full Text Available More than 100 years ago, Karl von Frisch showed that honeybee workers learn and discriminate colors. Since then, many studies confirmed the color learning capabilities of females from various hymenopteran species. Yet, little is known about visual learning and memory in males despite the fact that in most bee species males must take care of their own needs and must find rewarding flowers to obtain food. Here we used the proboscis extension response (PER paradigm to study the color learning capacities of workers and drones of the bumblebee, Bombus terrestris. Light stimuli were paired with sucrose reward delivered to the insects' antennae and inducing a reflexive extension of the proboscis. We evaluated color learning (i.e. conditioned PER to color stimuli in absolute and differential conditioning protocols and mid-term memory retention was measured two hours after conditioning. Different monochromatic light stimuli in combination with neutral density filters were used to ensure that the bumblebees could only use chromatic and not achromatic (e.g. brightness information. Furthermore, we tested if bees were able to transfer the learned information from the PER conditioning to a novel discrimination task in a Y-maze. Both workers and drones were capable of learning and discriminating between monochromatic light stimuli and retrieved the learned stimulus after two hours. Drones performed as well as workers during conditioning and in the memory test, but failed in the transfer test in contrast to workers. Our data clearly show that bumblebees can learn to associate a color stimulus with a sugar reward in PER conditioning and that both workers and drones reach similar acquisition and mid-term retention performances. Additionally, we provide evidence that only workers transfer the learned information from a Pavlovian to an operant situation.

  9. Learning-dependent and -independent enhancement of mitral/tufted cell glomerular odor responses following olfactory fear conditioning in awake mice.

    Science.gov (United States)

    Ross, Jordan M; Fletcher, Max L

    2018-04-18

    Associative fear learning produces fear toward the conditioned stimulus (CS) and often generalization, the expansion of fear from the CS to similar, unlearned stimuli. However, how fear learning affects early sensory processing of learned and unlearned stimuli in relation to behavioral fear responses to these stimuli remains unclear. We subjected male and female mice expressing the fluorescent calcium indicator GCaMP3 in olfactory bulb mitral and tufted cells to a classical olfactory fear conditioning paradigm. We then used awake, in vivo calcium imaging to quantify learning-induced changes in glomerular odor responses, which constitute the first site of olfactory processing in the brain. The results demonstrate that odor-shock pairing non-specifically enhances glomerular odor representations in a learning-dependent manner and increases representational similarity between the CS and non-conditioned odors, potentially priming the system towards generalization of learned fear. Additionally, CS-specific glomerular enhancements remain even when associative learning is blocked, suggesting two separate mechanisms lead to enhanced glomerular responses following odor-shock pairings. SIGNIFICANCE STATEMENT In the olfactory bulb (OB), odors are uniquely coded in a spatial map that represents odor identity, making the OB a unique model system for investigating how learned fear alters sensory processing. Classical fear conditioning causes fear of the conditioned stimulus (CS) and of neutral stimuli, known as generalization. Combining fear conditioning with fluorescent calcium imaging of OB glomeruli, we found enhanced glomerular responses of the CS as well as neutral stimuli in awake mice, which mirrors fear generalization. We report that CS and neutral stimuli enhancements are, respectively, learning- independent and learning-dependent. Together, these results reveal distinct mechanisms leading to enhanced OB processing of fear-inducing stimuli and provide important

  10. Learning the condition of satisfaction of an elementary behavior in dynamic field theory

    OpenAIRE

    Luciw, M; Kazerounian, S; Lahkman, K; Richter, M; Sandamirskaya, Y

    2015-01-01

    In order to proceed along an action sequence, an autonomous agent has to recognize that the intended final condition of the previous action has been achieved. In previous work, we have shown how a sequence of actions can be generated by an embodied agent using a neural-dynamic architecture for behavioral organization, in which each action has an intention and condition of satisfaction. These components are represented by dynamic neural fields, and are coupled to motors...

  11. Attentional processing of input in explicit and implicit learning conditions : an eye-tracking study

    OpenAIRE

    Indrarathne, Bimali; Kormos, Judit

    2017-01-01

    In this study we examined language learners’ attentional processing of a target syntactic construction in written L2 input in different input conditions, the change in learners’ knowledge of the targeted construction in these conditions and the relationship between the change in knowledge and attentional processing. 100 L2 learners of English in Sri Lanka were divided into four experimental groups and control group: input flood, input enhancement, a specific instruction to pay attention to th...

  12. LCoMotion - Learning, Cognition and Motion; a multicomponent cluster randomized school-based intervention aimed at increasing learning and cognition - rationale, design and methods.

    Science.gov (United States)

    Bugge, Anna; Tarp, Jakob; Østergaard, Lars; Domazet, Sidsel Louise; Andersen, Lars Bo; Froberg, Karsten

    2014-09-18

    The aim of the study; LCoMotion - Learning, Cognition and Motion was to develop, document, and evaluate a multi-component physical activity (PA) intervention in public schools in Denmark. The primary outcome was cognitive function. Secondary outcomes were academic skills, body composition, aerobic fitness and PA. The primary aim of the present paper was to describe the rationale, design and methods of the LCoMotion study. LCoMotion was designed as a cluster-randomized controlled study. Fourteen schools from all five regions in Denmark participated. All students from 6th and 7th grades were invited to participate (n = 869) and consent was obtained for 87% (n = 759). Baseline measurements were obtained in November/December 2013 and follow-up measurements in May/June 2014. The intervention lasted five months and consisted of a "package" of three main components: PA during academic lessons, PA during recess and PA homework. Furthermore a cycling campaign was conducted during the intervention period. Intervention schools should endeavor to ensure that students were physically active for at least 60 min every school day. Cognitive function was measured by a modified Eriksen flanker task and academic skills by a custom made mathematics test. PA was objectively measured by accelerometers (ActiGraph, GT3X and GT3X+) and aerobic fitness assessed by an intermittent shuttle-run test (the Andersen intermittent running test). Furthermore, compliance with the intervention was assessed by short message service (SMS)-tracking and questionnaires were delivered to students, parents and teachers. LCoMotion has ability to provide new insights on the effectiveness of a multicomponent intervention on cognitive function and academic skills in 6th and 7th grade students. Clinicaltrials.gov: NCT02012881 (10/10/2013).

  13. Genetic correlations between body condition score, yield and fertility in Holstein heifers estimated by random regression models

    NARCIS (Netherlands)

    Veerkamp, R.F.; Koenen, E.P.C.; Jong, de G.

    2001-01-01

    Twenty type classifiers scored body condition (BCS) of 91,738 first-parity cows from 601 sires and 5518 maternal grandsires. Fertility data during first lactation were extracted for 177,220 cows, of which 67,278 also had a BCS observation, and first-lactation 305-d milk, fat, and protein yields were

  14. Self-regulated learning of important information under sequential and simultaneous encoding conditions.

    Science.gov (United States)

    Middlebrooks, Catherine D; Castel, Alan D

    2018-05-01

    Learners make a number of decisions when attempting to study efficiently: they must choose which information to study, for how long to study it, and whether to restudy it later. The current experiments examine whether documented impairments to self-regulated learning when studying information sequentially, as opposed to simultaneously, extend to the learning of and memory for valuable information. In Experiment 1, participants studied lists of words ranging in value from 1-10 points sequentially or simultaneously at a preset presentation rate; in Experiment 2, study was self-paced and participants could choose to restudy. Although participants prioritized high-value over low-value information, irrespective of presentation, those who studied the items simultaneously demonstrated superior value-based prioritization with respect to recall, study selections, and self-pacing. The results of the present experiments support the theory that devising, maintaining, and executing efficient study agendas is inherently different under sequential formatting than simultaneous. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  15. Evaluating Machine Learning-Based Automated Personalized Daily Step Goals Delivered Through a Mobile Phone App: Randomized Controlled Trial.

    Science.gov (United States)

    Zhou, Mo; Fukuoka, Yoshimi; Mintz, Yonatan; Goldberg, Ken; Kaminsky, Philip; Flowers, Elena; Aswani, Anil

    2018-01-25

    Growing evidence shows that fixed, nonpersonalized daily step goals can discourage individuals, resulting in unchanged or even reduced physical activity. The aim of this randomized controlled trial (RCT) was to evaluate the efficacy of an automated mobile phone-based personalized and adaptive goal-setting intervention using machine learning as compared with an active control with steady daily step goals of 10,000. In this 10-week RCT, 64 participants were recruited via email announcements and were required to attend an initial in-person session. The participants were randomized into either the intervention or active control group with a one-to-one ratio after a run-in period for data collection. A study-developed mobile phone app (which delivers daily step goals using push notifications and allows real-time physical activity monitoring) was installed on each participant's mobile phone, and participants were asked to keep their phone in a pocket throughout the entire day. Through the app, the intervention group received fully automated adaptively personalized daily step goals, and the control group received constant step goals of 10,000 steps per day. Daily step count was objectively measured by the study-developed mobile phone app. The mean (SD) age of participants was 41.1 (11.3) years, and 83% (53/64) of participants were female. The baseline demographics between the 2 groups were similar (P>.05). Participants in the intervention group (n=34) had a decrease in mean (SD) daily step count of 390 (490) steps between run-in and 10 weeks, compared with a decrease of 1350 (420) steps among control participants (n=30; P=.03). The net difference in daily steps between the groups was 960 steps (95% CI 90-1830 steps). Both groups had a decrease in daily step count between run-in and 10 weeks because interventions were also provided during run-in and no natural baseline was collected. The results showed the short-term efficacy of this intervention, which should be formally

  16. Cocoa Flavanol Supplementation Influences Skin Conditions of Photo-Aged Women: A 24-Week Double-Blind, Randomized, Controlled Trial.

    Science.gov (United States)

    Yoon, Hyun-Sun; Kim, Jong Rhan; Park, Gyeong Yul; Kim, Jong-Eun; Lee, Dong Hun; Lee, Ki Won; Chung, Jin Ho

    2016-01-01

    The consumption of dietary antioxidants is considered to be a good strategy against photo-aging. However, the results of previous clinical trials that investigated the effects of oral consumption of high-flavanol cocoa products on skin photo-aging have been contradictory. The aim of this study was to investigate whether high-flavanol cocoa supplementation would improve the moderately photo-aged facial skin of female participants, by assessing skin wrinkles and elasticity. We performed a 24-wk, randomized, double-blind, placebo-controlled study to evaluate the effects of oral supplementation of cocoa flavanols on cutaneous photo-aging. All participants were moderately photo-aged Korean women with visible facial wrinkles (age range: 43-86 y). Participants were randomly assigned to receive a placebo beverage or cocoa beverage that contained 320 mg total cocoa flavanols/d. We measured wrinkles, skin elasticity, and hydration at baseline and at 12 and 24 wk. The primary endpoint was the mean percentage change in the average roughness value (Rz) at 24 wk. At 24 wk, the mean percentage change in Rz (primary endpoint) was significantly lower in the cocoa group than in the placebo group (-8.7 percentage points; 95% CI: -16.1, -1.3 percentage points; P = 0.023). The mean percentage changes in gross elasticity, as determined by a cutometer, also differed between the groups at 12 wk (9.1 percentage points; 95% CI: 1.5, 16.7 percentage points; P = 0.020) and 24 wk (8.6 percentage points; 95% CI: 1.0, 16.2 percentage points; P = 0.027). However, there were no significant differences in skin hydration and barrier integrity between the 2 groups. In moderately photo-aged women, regular cocoa flavanol consumption had positive effects on facial wrinkles and elasticity. Cocoa flavanol supplementation may contribute to the prevention of the progression of photo-aging. This trial was registered at clinicaltrials.gov as NCT02060097. © 2016 American Society for Nutrition.

  17. The effect of reminder letters on the uptake of an e-learning programme on dementia: a randomized trial in general practice

    DEFF Research Database (Denmark)

    Waldorff, Frans Boch; Siersma, V.; Nielsen, B.

    2009-01-01

    BACKGROUND AND AIMS: The aim of the present study was to evaluate whether three reminder letters mailed to GPs after dissemination of a Dementia Guideline increased the GPs' use of the corresponding e-learning programme (ELP). METHODS: Single-blinded randomized trial among all GPs in Copenhagen......, further research is needed in order to consider future implementation strategies for Internet-based Continuous Medical Education activities among not primed GPs Udgivelsesdato: 2009/12...

  18. Lessons Learned "Establishing an Electrically Safe Work Condition" Specifically related to Racking Electrical Breakers

    Energy Technology Data Exchange (ETDEWEB)

    Martinez, Tommy Robert [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Romero, Philbert Roland [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Garcia, Samuel Anthony [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-11-09

    During low voltage electrical equipment maintenance, a bad breaker was identified. The breaker was racked out from the substation cubicle without following the hazardous energy control process identified in the Integrated Work Document (IWD). The IWD required the substation to be in an electrically safe work condition prior to racking the breaker. Per NFPA 70E requirements, electrical equipment shall be put into an electrically safe work condition before an employee performs work on or interacts with equipment in a manner that increases the likelihood of creating an arc flash. Racking in or out a breaker on an energized bus may increase the likelihood of creating an arc flash dependent on equipment conditions. A thorough risk assessment must be performed prior to performing such a task. The risk assessment determines the risk control measures to be put in place prior to performing the work. Electrical Safety Officers (ESO) can assist in performing risk assessments and incorporating risk control measures.

  19. Application of unfolding transformation in the random matrix theory to analyze in vivo neuronal spike firing during awake and anesthetized conditions

    Directory of Open Access Journals (Sweden)

    Risako Kato

    2018-03-01

    Full Text Available General anesthetics decrease the frequency and density of spike firing. This effect makes it difficult to detect spike regularity. To overcome this problem, we developed a method utilizing the unfolding transformation which analyzes the energy level statistics in the random matrix theory. We regarded the energy axis as time axis of neuron spike and analyzed the time series of cortical neural firing in vivo. Unfolding transformation detected regularities of neural firing while changes in firing densities were associated with pentobarbital. We found that unfolding transformation enables us to compare firing regularity between awake and anesthetic conditions on a universal scale. Keywords: Unfolding transformation, Spike-timing, Regularity

  20. Learning to Design Together: Introducing Conditional Design as a Method for Co-design Activities

    DEFF Research Database (Denmark)

    Akoglu, Canan

    2017-01-01

    In today’s world, designing include participation of users and stakeholders at different levels varying from minimum participation to co-creating with these actors. In such a context, it becomes crucial to include related educational modules to be able to prepare design students for their future...... as the empirical study of this paper. The participants of the workshops were students from Communication Design and Industrial Design undergraduate programs with different seniorities in the same faculty. In terms of its content and operative flow, all the workshops were organized in a way that would enable equal...... contribution from each student and an active learning space was provided to the students. Based on the feedbacks, it is possible to foresee that the workshops were positive experiences especially in terms of understanding the importance of collective creativity and beyond the educational purposes...

  1. Meeting the Challenge of Chronic Conditions in a Sustainable Manner: Building on the AHC Learning.

    Science.gov (United States)

    Delgado, Pedro

    2016-01-01

    The Atlantic Healthcare Collaboration for Innovation and Improvement in Chronic Disease (AHC) set out to achieve three aims: to create a patient- and family-centred approach to manage chronic diseases; to build a network of organizational, regional and provincial teams to share evidence-informed, systems-level solutions and work together to develop, implement and sustain improvement initiatives; and to promote the sustainability of the participating health systems. Important elements of all three aims were achieved and the synthesis provides a meaningful contribution to systems working to improve chronic care. This paper explores those achievements as well as some of the areas for improvement, including replicability, expanded outcome measurement, greater detail around patient and family engagement, increased focus on specific outcomes and processes, and further articulation of lessons learned and recommendations.

  2. Forecasting of flowrate under rolling motion flow instability condition based on on-line sequential extreme learning machine

    International Nuclear Information System (INIS)

    Chen Hanying; Gao Puzhen; Tan Sichao; Tang Jiguo; Hou Xiaofan; Xu Huiqiang; Wu Xiangcheng

    2015-01-01

    The coupling of multiple thermal-hydraulic parameters can result in complex flow instability in natural circulation system under rolling motion. A real-time thermal-hydraulic condition prediction is helpful to the operation of systems in such condition. A single hidden layer feedforward neural networks algorithm named extreme learning machine (ELM) is considered as suitable method for this application because of its extremely fast training time, good accuracy and simplicity. However, traditional ELM assumes that all the training data are ready before the training process, while the training data is received sequentially in practical forecasting of flowrate. Therefore, this paper proposes a forecasting method for flowrate under rolling motion based on on-line sequential ELM (OS-ELM), which can learn the data one by one or chunk-by-chunk. The experiment results show that the OS-ELM method can achieve a better forecasting performance than basic ELM method and still keep the advantage of fast training and simplicity. (author)

  3. Prior Learning of Relevant Nonaversive Information Is a Boundary Condition for Avoidance Memory Reconsolidation in the Rat Hippocampus.

    Science.gov (United States)

    Radiske, Andressa; Gonzalez, Maria Carolina; Conde-Ocazionez, Sergio A; Feitosa, Anatildes; Köhler, Cristiano A; Bevilaqua, Lia R; Cammarota, Martín

    2017-10-04

    Reactivated memories can be modified during reconsolidation, making this process a potential therapeutic target for posttraumatic stress disorder (PTSD), a mental illness characterized by the recurring avoidance of situations that evoke trauma-related fears. However, avoidance memory reconsolidation depends on a set of still loosely defined boundary conditions, limiting the translational value of basic research. In particular, the involvement of the hippocampus in fear-motivated avoidance memory reconsolidation remains controversial. Combining behavioral and electrophysiological analyses in male Wistar rats, we found that previous learning of relevant nonaversive information is essential to elicit the participation of the hippocampus in avoidance memory reconsolidation, which is associated with an increase in theta- and gamma-oscillation power and cross-frequency coupling in dorsal CA1 during reactivation of the avoidance response. Our results indicate that the hippocampus is involved in memory reconsolidation only when reactivation results in contradictory representations regarding the consequences of avoidance and suggest that robust nesting of hippocampal theta-gamma rhythms at the time of retrieval is a specific reconsolidation marker. SIGNIFICANCE STATEMENT Posttraumatic stress disorder (PTSD) is characterized by maladaptive avoidance responses to stimuli or behaviors that represent or bear resemblance to some aspect of a traumatic experience. Disruption of reconsolidation, the process by which reactivated memories become susceptible to modifications, is a promising approach for treating PTSD patients. However, much of what is known about fear-motivated avoidance memory reconsolidation derives from studies based on fear conditioning instead of avoidance-learning paradigms. Using a step-down inhibitory avoidance task in rats, we found that the hippocampus is involved in memory reconsolidation only when the animals acquired the avoidance response in an

  4. Learning and memory in conditioned fear extinction: effects of d-cycloserine

    NARCIS (Netherlands)

    Vervliet, B.

    2008-01-01

    This review addresses the effects of the cognitive enhancer D-cycloserine (DCS) on the memory processes that occur in conditioned fear extinction, which is the experimental model for exposure techniques to reduce clinical anxiety. All reported rat studies show an enhanced fear extinction effect when

  5. The Education Penalty: Schooling, Learning and the Diminishment of Wages, Working Conditions and Worker Power

    Science.gov (United States)

    Sukarieh, Mayssoun; Tannock, Stuart

    2017-01-01

    Currently dominant human capital and knowledge economy rhetoric holds that education can raise wages, empower workers and enhance working conditions. Education, however, can also have the opposite impact in the workplace and labour market, an impact that has received only limited attention. In this article we draw together a broad range of…

  6. Learning Together: How Families Responded to Education Incentives in New York City's Conditional Cash Transfer Program

    Science.gov (United States)

    Greenberg, David; Dechausay, Nadine; Fraker, Carolyn

    2011-01-01

    In 2007, New York City's Center for Economic Opportunity launched Opportunity NYC-Family Rewards, an experimental, privately funded, conditional cash transfer (CCT) program to help families break the cycle of poverty. Family Rewards provided payments to low-income families in six of the city's poorest communities for achieving specific goals…

  7. How Learning Conditions and Program Structure Predict Burnout and Satisfaction in Teacher Education

    Science.gov (United States)

    Zimmermann, Friederike; Rösler, Lena; Möller, Jens; Köller, Olaf

    2018-01-01

    To support prospective teachers' professional development, teacher education should be characterised by conditions that help to prevent burnout and facilitate satisfaction. This study investigates predictors of burnout and satisfaction in teacher education by drawing on universities with different teacher education programme structures and assumed…

  8. One Size Fits All? Learning Conditions and Working Memory Capacity in "Ab Initio" Language Development

    Science.gov (United States)

    Sanz, Cristina; Lin, Hui-Ju; Lado, Beatriz; Stafford, Catherine A.; Bowden, Harriet W.

    2016-01-01

    The article summarizes results from two experimental studies (N = 23, N = 21) investigating the extent to which working memory capacity (WMC) intervenes in "ab initio" language development under two pedagogical conditions [± grammar lesson + input-based practice + explicit feedback]. The linguistic target is the use of morphosyntax to…

  9. Joint management of working conditions, environment and quality : in search of synergy and organizational learning

    NARCIS (Netherlands)

    Zwetsloot, G.

    1994-01-01

    Working conditions, environmental protection and quality control are increasingly important for organizations. Most companies are being confronted with sharply increasing requirements in all three areas. It is up to the managers and the respective experts to determine the most desirable strategies

  10. Conditions for Ubiquitous Computing: What Can Be Learned from a Longitudinal Study

    Science.gov (United States)

    Lei, Jing

    2010-01-01

    Based on survey data and interview data collected over four academic years, this longitudinal study examined how a ubiquitous computing project evolved along with the changes in teachers, students, the human infrastructure, and technology infrastructure in the school. This study also investigated what conditions were necessary for successful…

  11. CFD Analysis of Random Turbulent Flow Load in Steam Generator of APR1400 Under Normal Operation Condition

    International Nuclear Information System (INIS)

    Lim, Sang Gyu; You, Sung Chang; Kim, Han Gon

    2011-01-01

    Regulatory guide 1.20 revision 3 of the Nuclear Regulatory Committee (NRC) modifies guidance for vibration assessments of reactor internals and steam generator internals. The new guidance requires applicants to provide a preliminary analysis and evaluation of the design and performance of a facility, including the safety margins of during normal operation and transient conditions anticipated during the life of the facility. Especially, revision 3 require rigorous assessments of adverse flow effects in the steam dryer cased by flow-excited acoustic and structural resonances such as the abnormality from power-uprated BWR cases. For two nearly identical nuclear power plants, the steam system of one BWR plant experienced failure of steam dryers and the main steam system components when steam flow was increased by 16 percent for extended power uprate (EPU). The mechanisms of those failures have revealed that a small adverse flow changing from the prototype condition induced severe flow-excited acoustic and structural resonances, leading to structural failures. In accordance with the historical background, therefore, potential adverse flow effects should be evaluated rigorously for steam generator internals in both BWR and Pressurized Water Reactor (PWR). The Advanced Power Reactor 1400 (APR1400), an evolutionary light water reactor, increased the power by 7.7 percent from the design of the 'Valid Prototype', System80+. Thus, reliable evaluations of potential adverse flow effects on the steam generator of APR1400 are necessary according to the regulatory guide. This paper is part of the computational fluid dynamics (CFD) analysis results for evaluation of the adverse flow effect for the steam generator internals of APR1400, including a series of sensitivity analyses to enhance the reliability of CFD analysis and an estimation the effect of flow loads on the internals of the steam generator under normal operation conditions

  12. The effect of a cognitive-motor intervention on voluntary step execution under single and dual task conditions in older adults: a randomized controlled pilot study

    Directory of Open Access Journals (Sweden)

    Pichierri G

    2012-07-01

    Full Text Available Giuseppe Pichierri,1 Amos Coppe,1 Silvio Lorenzetti,2 Kurt Murer,1 Eling D de Bruin11Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Switzerland; 2Institute for Biomechanics, Department of Health Sciences and Technology, ETH Zurich, SwitzerlandBackground: This randomized controlled pilot study aimed to explore whether a cognitive-motor exercise program that combines traditional physical exercise with dance video gaming can improve the voluntary stepping responses of older adults under attention demanding dual task conditions.Methods: Elderly subjects received twice weekly cognitive-motor exercise that included progressive strength and balance training supplemented by dance video gaming for 12 weeks (intervention group. The control group received no specific intervention. Voluntary step execution under single and dual task conditions was recorded at baseline and post intervention (Week 12.Results: After intervention between-group comparison revealed significant differences for initiation time of forward steps under dual task conditions (U = 9, P = 0.034, r = 0.55 and backward steps under dual task conditions (U = 10, P = 0.045, r = 0.52 in favor of the intervention group, showing altered stepping levels in the intervention group compared to the control group.Conclusion: A cognitive-motor intervention based on strength and balance exercises with additional dance video gaming is able to improve voluntary step execution under both single and dual task conditions in older adults.Keywords: fall prevention, exercise, dance, video game

  13. Ultrasound simulator-assisted teaching of cardiac anatomy to preclinical anatomy students: A pilot randomized trial of a three-hour learning exposure.

    Science.gov (United States)

    Canty, David Jeffrey; Hayes, Jenny A; Story, David Andrew; Royse, Colin Forbes

    2015-01-01

    Ultrasound simulation allows students to virtually explore internal anatomy by producing accurate, moving, color, three-dimensional rendered slices from any angle or approach leaving the organs and their relationships intact without requirement for consumables. The aim was to determine the feasibility and efficacy of self-directed learning of cardiac anatomy with an ultrasound simulator compared to cadavers and plastic models. After a single cardiac anatomy lecture, fifty university anatomy students participated in a three-hour supervised self-directed learning exposure in groups of five, randomized to an ultrasound simulator or human cadaveric specimens and plastic models. Pre- and post-tests were conducted using pictorial and non-pictorial multiple-choice questions (MCQs). Simulator students completed a survey on their experience. Four simulator and seven cadaver group students did not attend after randomization. Simulator use in groups of five students was feasible and feedback from participants was very positive. Baseline test scores were similar (P = 0.9) between groups. After the learning intervention, there was no difference between groups in change in total test score (P = 0.37), whether they were pictorial (P = 0.6) or non-pictorial (P = 0.21). In both groups there was an increase in total test scores (simulator +19.8 ±12.4%% and cadaver: +16.4% ± 10.2, P human cadaveric prosections for learning cardiac anatomy. © 2014 American Association of Anatomists.

  14. Machine-Learning Techniques for the Determination of Attrition of Forces Due to Atmospheric Conditions

    Science.gov (United States)

    2018-02-01

    selected as a proof of concept due to its vast number of data points. While this report does note some trends associated with temperature and dew...separate data sets for helicopters and airplanes, while selectively requesting the event IDs, descriptions of events, light conditions, temperature , dew...weather events) and the error rate for that class . The rows are labeled for the actual occurrence of those events. Thus, for every row–column

  15. The effects of cocaine, alcohol and cocaine/alcohol combinations in conditioned taste aversion learning.

    Science.gov (United States)

    Busse, Gregory D; Verendeev, Andrey; Jones, Jermaine; Riley, Anthony L

    2005-09-01

    We have recently reported that alcohol attenuates cocaine place preferences. Although the basis for this effect is unknown, alcohol may attenuate cocaine reward by potentiating its aversive effects. To examine this possibility, these experiments assessed the effects of alcohol on cocaine-induced taste aversions under conditions similar to those that resulted in attenuated place preferences. Specifically, Experiments 1 and 2 assessed the effects of alcohol (0.5 g/kg) on taste aversions induced by 20, 30 and 40 mg/kg cocaine. Experiment 3 examined the role of intertrial interval in the effects of alcohol (0.5 g/kg) on cocaine (30 mg/kg) taste aversions. In Experiments 1 and 2, cocaine was effective at conditioning aversions. Alcohol produced no measurable effect. Combining cocaine and alcohol produced no greater aversion than cocaine alone (and, in fact, weakened aversions at the lowest dose of cocaine). In Experiment 3, varying the intertrial interval from 3 days (as in the case of Experiments 1 and 2) to 1 day (a procedure identical to that in which alcohol attenuated cocaine place preferences) resulted in significant alcohol- and cocaine-induced taste aversions. Nonetheless, alcohol remained ineffective in potentiating cocaine aversions. Thus, under these conditions alcohol does not potentiate cocaine's aversiveness. These results were discussed in terms of their implication for the effects of alcohol on cocaine-induced place preferences. Further, the effects of alcohol on place preferences conditioned by cocaine were discussed in relation to other assessments of the effects of alcohol on the affective properties of cocaine and the implications of these interactions for alcohol and cocaine co-use.

  16. LEARNING TO BE BAD: ADVERSE SOCIAL CONDITIONS, SOCIAL SCHEMAS, AND CRIME

    Science.gov (United States)

    Simons, Ronald L.; Burt, Callie Harbin

    2011-01-01

    In this paper we develop and test a new approach to explain the link between social factors and individual offending. We argue that seemingly disparate family, peer, and community conditions lead to crime because the lessons communicated by these events are similar and promote social schemas involving a hostile view of people and relationships, a preference for immediate rewards, and a cynical view of conventional norms. Further, we posit that these three schemas are interconnected and combine to form a criminogenic knowledge structure that gives rise to situational interpretations legitimating criminal behavior. Structural equation modeling with a sample of roughly 700 hundred African American teens provided strong support for the model. The findings indicated that persistent exposure to adverse conditions such as community crime, discrimination, harsh parenting, deviant peers and low neighborhood collective efficacy increased commitment to the three social schemas. The three schemas were highly intercorrelated and combined to form a latent construct that strongly predicted increases in crime. Further, in large measure the effect of the various adverse conditions on increases in crime was indirect through their impact on this latent construct. We discuss the extent to which the social schematic model presented in the paper might be used to integrate concepts and findings from several of the major theories of criminal behavior. PMID:21760641

  17. Lesson Learned from Conditioning of Disused Sealed Radioactive Sources (DSRS) in Malaysia

    International Nuclear Information System (INIS)

    Nik Marzukee Nik Ibrahim; Mohd Abdul Wahab Yusof; Norasalwa Zakaria

    2016-01-01

    This paper presents the conditioning of disused sealed radioactive source (DSRS) in Malaysia. In Malaysia, sealed radioactive sources (SRS) are widely used in Malaysia especially in industry, medicine and research. Once SRS are no longer in use, they are declared disused and managed as radioactive waste. In order to reduce the risk associated with disused sealed radioactive sources (DSRS), the first priority would be to bring them under appropriate controls. This paper describes the experience developed and activities performed by Nuclear Malaysia throughout the period in conditioning of DSRS as well as future programme to further enhancing the infrastructure. Collaborative efforts with the various relevant groups such as Loji and Prototaip Development Centre (PDC) and Industrial Technology Division (BTI) provide an effective avenue in ensuring successful implementation of the programme. Currently, until August 2015, Malaysia has in possession about 12,154 unit of DSRS categories 3-5 and 4 units of DSRS category 2 sources which being stored at the interim storage facility Nuclear Malaysia. A national activity was implemented for the on-the-job training of personnel tasked with the conditioning of DSRS, at the Waste Technology Development Centre (WasTeC) facilities. This is part of -cradle-to-grave- control of radioactive sources to protect the workers and public from the hazards of ionizing radiation. (author)

  18. Waterbodies Extraction from LANDSAT8-OLI Imagery Using Awater Indexs-Guied Stochastic Fully-Connected Conditional Random Field Model and the Support Vector Machine

    Science.gov (United States)

    Wang, X.; Xu, L.

    2018-04-01

    One of the most important applications of remote sensing classification is wa