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.)

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.

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.

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.

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.

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.

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.

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

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…

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

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.

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

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.

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...

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,

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.

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

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...

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.

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.

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.

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.

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...

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

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.

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.

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.

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.

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…

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

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…

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....

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.

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...

Some psycholinguistic conditions for second language learning

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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.

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

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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.

Conditioning and learning in relation to disease.

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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.

VALIDATION OF A SCALE OF LEVELS AND CONDITIONS OF ORGANIZATIONAL LEARNING

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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.

Sex differences in learning processes of classical and operant conditioning.

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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.

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

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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.

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....

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

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....

MULTITEMPORAL CROP TYPE CLASSIFICATION USING CONDITIONAL RANDOM FIELDS AND RAPIDEYE DATA

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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.

Contingency learning in human fear conditioning involves the ventral striatum.

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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.

Statistical learning of action: the role of conditional probability.

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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.

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.

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.

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…

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

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

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.

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.

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.

Singing can facilitate foreign language learning.

Science.gov (United States)

Ludke, Karen M; Ferreira, Fernanda; Overy, Katie

2014-01-01

This study presents the first experimental evidence that singing can facilitate short-term paired-associate phrase learning in an unfamiliar language (Hungarian). Sixty adult participants were randomly assigned to one of three "listen-and-repeat" learning conditions: speaking, rhythmic speaking, or singing. Participants in the singing condition showed superior overall performance on a collection of Hungarian language tests after a 15-min learning period, as compared with participants in the speaking and rhythmic speaking conditions. This superior performance was statistically significant (p sing" learning method can facilitate verbatim memory for spoken foreign language phrases.

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.

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.

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.

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).

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.

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…

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.

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

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.

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

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...

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.

Instructed fear learning, extinction, and recall: additive effects of cognitive information on emotional learning of fear.

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Javanbakht, Arash; Duval, Elizabeth R; Cisneros, Maria E; Taylor, Stephan F; Kessler, Daniel; Liberzon, Israel

2017-08-01

The effects of instruction on learning of fear and safety are rarely studied. We aimed to examine the effects of cognitive information and experience on fear learning. Fourty healthy participants, randomly assigned to three groups, went through fear conditioning, extinction learning, and extinction recall with two conditioned stimuli (CS+). Information was presented about the presence or absence of conditioned stimulus-unconditioned stimulus (CS-US) contingency at different stages of the experiment. Information about the CS-US contingency prior to fear conditioning enhanced fear response and reduced extinction recall. Information about the absence of CS-US contingency promoted extinction learning and recall, while omission of this information prior to recall resulted in fear renewal. These findings indicate that contingency information can facilitate fear expression during fear learning, and can facilitate extinction learning and recall. Information seems to function as an element of the larger context in which conditioning occurs.

Modulating effects in learned helplessness of dyadic dominance-submission relations.

Science.gov (United States)

Díaz-Berciano, Cristina; de Vicente, Francisco; Fontecha, Elisa

2008-01-01

In this experiment, learned helplessness was studied from an ethological perspective by examining individual differences in social dominance and its influence on the effects of helplessness. Ninety animals were used, 30 randomly selected and 60 selected because of their clear dominance or submission. Each condition (dominant, submissive, and random) was distributed in three subgroups corresponding to the triadic design. The test consisted of an escape/avoidance task. The results showed that the animals in the uncontrollable condition performed worse than those in the controllable and no treatment conditions. Social submission and dominance reduced vulnerability of the subjects against learned helplessness. Submission had a facilitating effect on subsequent learning, independently of whether pretreatment was controllability or uncontrollability. Learned mastery was observed in the submissive condition, because submission benefited the subjects in the controllable condition in comparison with the untreated subjects, and dominance impaired the subjects in the controllable condition. Copyright 2007 Wiley-Liss, Inc.

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…

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.

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 (�

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)

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)

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.

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.

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.

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.

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...

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.…

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

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.

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

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.

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.

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.

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.

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

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

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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.

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...

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.

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

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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.

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

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.

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.

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…

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…

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.

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

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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.

Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method

Directory of Open Access Journals (Sweden)

Wei Xue

2016-08-01

Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.

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

Measuring strategic control in artificial grammar learning.

Science.gov (United States)

Norman, Elisabeth; Price, Mark C; Jones, Emma

2011-12-01

In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

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.

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.

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

Does Combining the Embodiment and Personalization Principles of Multimedia Learning Affect Learning the Culture of a Foreign Language?

Science.gov (United States)

Wang, Yanlin; Crooks, Steven M.

2015-01-01

The purpose of this study was to investigate how social cues associated with the personalization and embodiment principles in multimedia learning affect the learning and attitude of students studying the culture of a foreign language. University students were randomly assigned to one of two experimental conditions that consisted of an…

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.

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.

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

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.

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.

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…

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)

Production Practice During Language Learning Improves Comprehension.

Science.gov (United States)

Hopman, Elise W M; MacDonald, Maryellen C

2018-04-01

Language learners often spend more time comprehending than producing a new language. However, memory research suggests reasons to suspect that production practice might provide a stronger learning experience than comprehension practice. We tested the benefits of production during language learning and the degree to which this learning transfers to comprehension skill. We taught participants an artificial language containing multiple linguistic dependencies. Participants were randomly assigned to either a production- or a comprehension-learning condition, with conditions designed to balance attention demands and other known production-comprehension differences. After training, production-learning participants outperformed comprehension-learning participants on vocabulary comprehension and on comprehension tests of grammatical dependencies, even when we controlled for individual differences in vocabulary learning. This result shows that producing a language during learning can improve subsequent comprehension, which has implications for theories of memory and learning, language representations, and educational practices.

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).

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.

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....

Examining Culturally Structured Learning Environments with Different Types of Music-Linked Movement Opportunity

Science.gov (United States)

Cole, Juanita M.; Boykin, A. Wade

2008-01-01

This study describes two experiments that extended earlier work on the Afrocultural theme Movement Expression. The impact of various learning conditions characterized by different types of music-linked movement on story recall performance was examined. African American children were randomly assigned to a learning condition, presented a story, and…

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

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.

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.

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.

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)

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…

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

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.

Implicit learning in cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia).

Science.gov (United States)

Locurto, Charles; Fox, Maura; Mazzella, Andrea

2015-06-01

There is considerable interest in the conditions under which human subjects learn patterned information without explicit instructions to learn that information. This form of learning, termed implicit or incidental learning, can be approximated in nonhumans by exposing subjects to patterned information but delivering reinforcement randomly, thereby not requiring the subjects to learn the information in order to be reinforced. Following acquisition, nonhuman subjects are queried as to what they have learned about the patterned information. In the present experiment, we extended the study of implicit learning in nonhumans by comparing two species, cotton-top tamarins (Saguinus oedipus) and pigeons (Columba livia), on an implicit learning task that used an artificial grammar to generate the patterned elements for training. We equated the conditions of training and testing as much as possible between the two species. The results indicated that both species demonstrated approximately the same magnitude of implicit learning, judged both by a random test and by choice tests between pairs of training elements. This finding suggests that the ability to extract patterned information from situations in which such learning is not demanded is of longstanding origin.

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

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

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

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

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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.

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...

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.

A random walk model to evaluate autism

Science.gov (United States)

Moura, T. R. S.; Fulco, U. L.; Albuquerque, E. L.

2018-02-01

A common test administered during neurological examination in children is the analysis of their social communication and interaction across multiple contexts, including repetitive patterns of behavior. Poor performance may be associated with neurological conditions characterized by impairments in executive function, such as the so-called pervasive developmental disorders (PDDs), a particular condition of the autism spectrum disorders (ASDs). Inspired in these diagnosis tools, mainly those related to repetitive movements and behaviors, we studied here how the diffusion regimes of two discrete-time random walkers, mimicking the lack of social interaction and restricted interests developed for children with PDDs, are affected. Our model, which is based on the so-called elephant random walk (ERW) approach, consider that one of the random walker can learn and imitate the microscopic behavior of the other with probability f (1 - f otherwise). The diffusion regimes, measured by the Hurst exponent (H), is then obtained, whose changes may indicate a different degree of autism.

Learning in the machine: The symmetries of the deep learning channel.

Science.gov (United States)

Baldi, Pierre; Sadowski, Peter; Lu, Zhiqin

2017-11-01

In a physical neural system, learning rules must be local both in space and time. In order for learning to occur, non-local information must be communicated to the deep synapses through a communication channel, the deep learning channel. We identify several possible architectures for this learning channel (Bidirectional, Conjoined, Twin, Distinct) and six symmetry challenges: (1) symmetry of architectures; (2) symmetry of weights; (3) symmetry of neurons; (4) symmetry of derivatives; (5) symmetry of processing; and (6) symmetry of learning rules. Random backpropagation (RBP) addresses the second and third symmetry, and some of its variations, such as skipped RBP (SRBP) address the first and the fourth symmetry. Here we address the last two desirable symmetries showing through simulations that they can be achieved and that the learning channel is particularly robust to symmetry variations. Specifically, random backpropagation and its variations can be performed with the same non-linear neurons used in the main input-output forward channel, and the connections in the learning channel can be adapted using the same algorithm used in the forward channel, removing the need for any specialized hardware in the learning channel. Finally, we provide mathematical results in simple cases showing that the learning equations in the forward and backward channels converge to fixed points, for almost any initial conditions. In symmetric architectures, if the weights in both channels are small at initialization, adaptation in both channels leads to weights that are essentially symmetric during and after learning. Biological connections are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

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…

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...

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.

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 ...

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

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....

Randomizing Roaches: Exploring the "Bugs" of Randomization in Experimental Design

Science.gov (United States)

Wagler, Amy; Wagler, Ron

2014-01-01

Understanding the roles of random selection and random assignment in experimental design is a central learning objective in most introductory statistics courses. This article describes an activity, appropriate for a high school or introductory statistics course, designed to teach the concepts, values and pitfalls of random selection and assignment…

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.

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

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.

Is sequence awareness mandatory for perceptual sequence learning: An assessment using a pure perceptual sequence learning design.

Science.gov (United States)

Deroost, Natacha; Coomans, Daphné

2018-02-01

We examined the role of sequence awareness in a pure perceptual sequence learning design. Participants had to react to the target's colour that changed according to a perceptual sequence. By varying the mapping of the target's colour onto the response keys, motor responses changed randomly. The effect of sequence awareness on perceptual sequence learning was determined by manipulating the learning instructions (explicit versus implicit) and assessing the amount of sequence awareness after the experiment. In the explicit instruction condition (n = 15), participants were instructed to intentionally search for the colour sequence, whereas in the implicit instruction condition (n = 15), they were left uninformed about the sequenced nature of the task. Sequence awareness after the sequence learning task was tested by means of a questionnaire and the process-dissociation-procedure. The results showed that the instruction manipulation had no effect on the amount of perceptual sequence learning. Based on their report to have actively applied their sequence knowledge during the experiment, participants were subsequently regrouped in a sequence strategy group (n = 14, of which 4 participants from the implicit instruction condition and 10 participants from the explicit instruction condition) and a no-sequence strategy group (n = 16, of which 11 participants from the implicit instruction condition and 5 participants from the explicit instruction condition). Only participants of the sequence strategy group showed reliable perceptual sequence learning and sequence awareness. These results indicate that perceptual sequence learning depends upon the continuous employment of strategic cognitive control processes on sequence knowledge. Sequence awareness is suggested to be a necessary but not sufficient condition for perceptual learning to take place. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.

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.

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.

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.

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.

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.

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

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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.

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

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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.

Evaluation of an e-learning system for diagnosis of gastric lesions using magnifying narrow-band imaging: a multicenter randomized controlled study.

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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.

Studying the Effectiveness of an Online Language Learning Platform in China

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Baker, Ryan; Wang, Feng; Ma, Zhenjun; Ma, Wei; Zheng, Shiyue

2018-01-01

In this paper we evaluate the effectiveness of an adaptive online learning platform, designed to support Chinese students in learning the English language. The adaptive platform is studied in three studies, where the experimental platform is compared to an alternate, non-adaptive platform, with random assignment to conditions (the adaptive…

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

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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.

Digital Games, Design, and Learning

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Clark, Douglas B.; Tanner-Smith, Emily E.; Killingsworth, Stephen S.

2016-01-01

In this meta-analysis, we systematically reviewed research on digital games and learning for K–16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions (g¯ = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value-added comparisons indicated significant learning benefits associated with augmented game designs (g¯ = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium. PMID:26937054

Dissociable effects of practice variability on learning motor and timing skills.

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Caramiaux, Baptiste; Bevilacqua, Frédéric; Wanderley, Marcelo M; Palmer, Caroline

2018-01-01

Motor skill acquisition inherently depends on the way one practices the motor task. The amount of motor task variability during practice has been shown to foster transfer of the learned skill to other similar motor tasks. In addition, variability in a learning schedule, in which a task and its variations are interweaved during practice, has been shown to help the transfer of learning in motor skill acquisition. However, there is little evidence on how motor task variations and variability schedules during practice act on the acquisition of complex motor skills such as music performance, in which a performer learns both the right movements (motor skill) and the right time to perform them (timing skill). This study investigated the impact of rate (tempo) variability and the schedule of tempo change during practice on timing and motor skill acquisition. Complete novices, with no musical training, practiced a simple musical sequence on a piano keyboard at different rates. Each novice was assigned to one of four learning conditions designed to manipulate the amount of tempo variability across trials (large or small tempo set) and the schedule of tempo change (randomized or non-randomized order) during practice. At test, the novices performed the same musical sequence at a familiar tempo and at novel tempi (testing tempo transfer), as well as two novel (but related) sequences at a familiar tempo (testing spatial transfer). We found that practice conditions had little effect on learning and transfer performance of timing skill. Interestingly, practice conditions influenced motor skill learning (reduction of movement variability): lower temporal variability during practice facilitated transfer to new tempi and new sequences; non-randomized learning schedule improved transfer to new tempi and new sequences. Tempo (rate) and the sequence difficulty (spatial manipulation) affected performance variability in both timing and movement. These findings suggest that there is a

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.

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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.

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

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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.

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

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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.

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

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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.

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

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

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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.

Does Teaching Mnemonics for Vocabulary Learning Make a Difference? Putting the Keyword Method and the Word Part Technique to the Test

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Wei, Zheng

2015-01-01

The present research tested the effectiveness of the word part technique in comparison with the keyword method and self-strategy learning. One hundred and twenty-one Chinese year-one university students were randomly assigned to one of the three learning conditions: word part, keyword or self-strategy learning condition. Half of the target words…

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

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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

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

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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

Bearing Fault Classification Based on Conditional Random Field

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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.

Biomimetic propulsion under random heaving conditions, using active pitch control

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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.

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

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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.

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

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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

Effectiveness of the universal prevention program 'Healthy School and Drugs': Study protocol of a randomized clustered trial

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Malmberg Monique

2010-09-01

Full Text Available Abstract Background Substance use is highly prevalent among Dutch adolescents. The Healthy School and Drugs program is a nationally implemented school-based prevention program aimed at reducing early and excessive substance use among adolescents. Although the program's effectiveness was tested in a quasi-experimental design before, many program changes were made afterwards. The present study, therefore, aims to test the effects of this widely used, renewed universal prevention program. Methods/Design A randomized clustered trial will be conducted among 3,784 adolescents of 23 secondary schools in The Netherlands. The trial has three conditions; two intervention conditions (i.e., e-learning and integral and a control condition. The e-learning condition consists of three digital learning modules (i.e., about alcohol, tobacco, and marijuana that are sequentially offered over the course of three school years (i.e., grade 1, grade 2, and grade 3. The integral condition consists of parental participation in a parental meeting on substance use, regulation of substance use, and monitoring and counseling of students' substance use at school, over and above the three digital modules. The control condition is characterized as business as usual. Participating schools were randomly assigned to either an intervention or control condition. Participants filled out a digital questionnaire at baseline and will fill out the same questionnaire three more times at follow-up measurements (8, 20, and 32 months after baseline. Outcome variables included in the questionnaire are the percentage of binge drinking (more than five drinks per occasion, the average weekly number of drinks, and the percentage of adolescents who ever drunk a glass of alcohol and the percentage of adolescents who ever smoked a cigarette or a joint respectively for tobacco and marijuana. Discussion This study protocol describes the design of a randomized clustered trial that evaluates the

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

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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

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

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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.

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.

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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.

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

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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.

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

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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.

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

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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.

Effects of learning climate and registered nurse staffing on medication errors.

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Chang, YunKyung; Mark, Barbara

2011-01-01

Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.

Efficient Training Methods for Conditional Random Fields

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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

Understanding Frame-of-Reference Training Success: A Social Learning Theory Perspective

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Sulsky, Lorne M.; Kline, Theresa J. B.

2007-01-01

Employing the social learning theory (SLT) perspective on training, we analysed the effects of alternative frame-of-reference (FOR) training protocols on various criteria of training effectiveness. Undergraduate participants (N = 65) were randomly assigned to one of four FOR training conditions and a control condition. Training effectiveness was…

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

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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

The effect of a dopamine antagonist on conditioning of sexual arousal in women.

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

2016-04-01

Dopamine (DA) plays a key role in reward-seeking behaviours. Accumulating evidence from animal and human studies suggests that human sexual reward learning may also depend on DA transmission. However, research on the role of DA in human sexual reward learning is completely lacking. To investigate whether DA antagonism attenuates classical conditioning of sexual response in humans. Healthy women were randomly allocated to one of two treatment conditions: haloperidol (n = 29) or placebo (n = 29). A differential conditioning paradigm was applied with genital vibrostimulation as unconditional stimulus (US) and neutral pictures as conditional stimuli (CSs). Genital arousal was assessed, and ratings of affective value and subjective sexual arousal were obtained. Haloperidol administration affected unconditional genital responding. However, no significant effects of medication were found for conditioned responding. No firm conclusions can be drawn about whether female sexual reward learning implicates DA transmission since the results do not lend themselves to unambiguous interpretation.

How do medium naturalness and personality traits shape academic achievement and perceived learning? An experimental study of face-to-face and synchronous e-learning

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Ina Blau

2017-07-01

Full Text Available This controlled experiment examined how academic achievement and cognitive, emotional and social aspects of perceived learning are affected by the level of medium naturalness (face-to-face, one-way and two-way videoconferencing and by learners’ personality traits (extroversion–introversion and emotional stability–neuroticism. The Media Naturalness Theory explains the degree of medium naturalness by comparing its characteristics to face-to-face communication, considered to be the most natural form of communication. A total of 76 participants were randomly assigned to three experimental conditions: face-to-face, one-way and two-way videoconferencing. E-learning conditions were conducted through Zoom videoconferencing, which enables natural and spontaneous communication. Findings shed light on the trade-off involved in media naturalness: one-way videoconferencing, the less natural learning condition, enhanced the cognitive aspect of perceived learning but compromised the emotional and social aspects. Regarding the impact of personality, neurotic students tended to enjoy and succeed more in face-to-face learning, whereas emotionally stable students enjoyed and succeeded in all of the learning conditions. Extroverts tended to enjoy more natural learning environments but had lower achievements in these conditions. In accordance with the ‘poor get richer’ principle, introverts enjoyed environments with a low level of medium naturalness. However, they remained focused and had higher achievements in the face-to-face learning.

Learning-dependent and -independent enhancement of mitral/tufted cell glomerular odor responses following olfactory fear conditioning in awake mice.

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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

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...

Mechanisms within the Parietal Cortex Correlate with the Benefits of Random Practice in Motor Adaptation

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Benjamin Thürer

2017-08-01

Full Text Available The motor learning literature shows an increased retest or transfer performance after practicing under unstable (random conditions. This random practice effect (also known as contextual interference effect is frequently investigated on the behavioral level and discussed in the context of mechanisms of the dorsolateral prefrontal cortex and increased cognitive efforts during movement planning. However, there is a lack of studies examining the random practice effect in motor adaptation tasks and, in general, the underlying neural processes of the random practice effect are not fully understood. We tested 24 right-handed human subjects performing a reaching task using a robotic manipulandum. Subjects learned to adapt either to a blocked or a random schedule of different force field perturbations while subjects’ electroencephalography (EEG was recorded. The behavioral results showed a distinct random practice effect in terms of a more stabilized retest performance of the random compared to the blocked practicing group. Further analyses showed that this effect correlates with changes in the alpha band power in electrodes over parietal areas. We conclude that the random practice effect in this study is facilitated by mechanisms within the parietal cortex during movement execution which might reflect online feedback mechanisms.

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

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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

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

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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

Kinematics and dynamics of green water on a fixed platform in a large wave basin in focusing wave and random wave conditions

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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.

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

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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.

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

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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}.

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

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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.

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.

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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.

Learned Helplessness and Depression in a Clinical Population: A Test of Two Behavioral Hypotheses

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And Others; Price, Kenneth P.

1978-01-01

This study was undertaken to extend the learned helplessness phenomenon to a clinical population and to test the competing hypotheses of Seligman and Lewinsohn. 96 male hospitalized psychiatric and medical patients were randomly assigned to one of four experimental conditions. Results replicate the learned helplessness phenomenon in a group of…

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

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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.

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

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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.

Random forest learning of ultrasonic statistical physics and object spaces for lesion detection in 2D sonomammography

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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.

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

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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

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.

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

The effect of learning climate on snack consumption and ego depletion among undergraduate students.

Science.gov (United States)

Magaraggia, Christian; Dimmock, James A; Jackson, Ben

2013-10-01

We explored the effect of controlled and autonomous learning choices on the consumption of a high-energy snack food, and also examined whether snack consumption during a controlled choice learning activity could 'up-regulate' subsequent performance on a self-regulation task. Participants were randomly assigned to a controlled choice learning condition in which food was provided, a controlled choice learning condition in which food was not provided, or an autonomous choice learning condition in which food was provided. Results indicated that the autonomous choice group consumed significantly less snack food than the controlled-choice-and-food group. Participants in the autonomous choice condition also performed better on the subsequent self-regulation task than the controlled-choice-and-food group, even after controlling for the amount of food consumed. Furthermore, within the controlled-choice-and-food condition, there was no association between food consumption and subsequent self-regulation task performance. Discussion focuses on the potential impact of a controlled learning climate on snack food consumption and on the degradation of self-regulation capacities. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Effects of Learning about Historical Gender Discrimination on Early Adolescents' Occupational Judgments and Aspirations

Science.gov (United States)

Pahlke, Erin; Bigler, Rebecca S.; Green, Vanessa A.

2010-01-01

To examine the consequences of learning about gender discrimination, early adolescents (n = 121, aged 10-14) were randomly assigned to receive either (a) standard biographical lessons about historical figures (standard condition) or (b) nearly identical lessons that included information about gender discrimination (discrimination condition).…

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.

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.

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...

Improving the application of a practice guideline for the assessment and treatment of suicidal behavior by training the full staff of psychiatric departments via an e-learning supported Train-the-Trainer program: study protocol for a randomized controlled trial.

Science.gov (United States)

de Beurs, Derek P; de Groot, Marieke H; de Keijser, Jos; Verwey, Bastiaan; Mokkenstorm, Jan; Twisk, Jos W R; van Duijn, Erik; van Hemert, Albert M; Verlinde, Lia; Spijker, Jan; van Luijn, Bert; Vink, Jan; Kerkhof, Ad J F M

2013-01-09

In 2012, in The Netherlands a multidisciplinary practice guideline for the assessment and treatment of suicidal behavior was issued. The release of guidelines often fails to change professional behavior due to multiple barriers. Structured implementation may improve adherence to guidelines. This article describes the design of a study measuring the effect of an e-learning supported Train-the-Trainer program aiming at the training of the full staff of departments in the application of the guideline. We hypothesize that both professionals and departments will benefit from the program. In a multicenter cluster randomized controlled trial, 43 psychiatric departments spread over 10 regional mental health institutions throughout The Netherlands will be clustered in pairs with respect to the most prevalent diagnostic category of patients and average duration of treatment. Pair members are randomly allocated to either the experimental or the control condition. In the experimental condition, the full staff of departments, that is, all registered nurses, psychologists, physicians and psychiatrists (n = 532, 21 departments) will be trained in the application of the guideline, in a one-day small interactive group Train-the-Trainer program. The program is supported by a 60-minute e-learning module with video vignettes of suicidal patients and additional instruction. In the control condition (22 departments, 404 professionals), the guideline shall be disseminated in the traditional way: through manuals, books, conferences, internet, reviews and so on. The effectiveness of the program will be assessed at the level of both health care professionals and departments. We aim to demonstrate the effect of training of the full staff of departments with an e-learning supported Train-the-Trainer program in the application of a new clinical guideline. Strengths of the study are the natural setting, the training of full staff, the random allocation to the conditions, the large scale of the

Errorful and errorless learning: The impact of cue-target constraint in learning from errors.

Science.gov (United States)

Bridger, Emma K; Mecklinger, Axel

2014-08-01

The benefits of testing on learning are well described, and attention has recently turned to what happens when errors are elicited during learning: Is testing nonetheless beneficial, or can errors hinder learning? Whilst recent findings have indicated that tests boost learning even if errors are made on every trial, other reports, emphasizing the benefits of errorless learning, have indicated that errors lead to poorer later memory performance. The possibility that this discrepancy is a function of the materials that must be learned-in particular, the relationship between the cues and targets-was addressed here. Cued recall after either a study-only errorless condition or an errorful learning condition was contrasted across cue-target associations, for which the extent to which the target was constrained by the cue was either high or low. Experiment 1 showed that whereas errorful learning led to greater recall for low-constraint stimuli, it led to a significant decrease in recall for high-constraint stimuli. This interaction is thought to reflect the extent to which retrieval is constrained by the cue-target association, as well as by the presence of preexisting semantic associations. The advantage of errorful retrieval for low-constraint stimuli was replicated in Experiment 2, and the interaction with stimulus type was replicated in Experiment 3, even when guesses were randomly designated as being either correct or incorrect. This pattern provides support for inferences derived from reports in which participants made errors on all learning trials, whilst highlighting the impact of material characteristics on the benefits and disadvantages that accrue from errorful learning in episodic memory.

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

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.

Random Forest as an Imputation Method for Education and Psychology Research: Its Impact on Item Fit and Difficulty of the Rasch Model

Science.gov (United States)

Golino, Hudson F.; Gomes, Cristiano M. A.

2016-01-01

This paper presents a non-parametric imputation technique, named random forest, from the machine learning field. The random forest procedure has two main tuning parameters: the number of trees grown in the prediction and the number of predictors used. Fifty experimental conditions were created in the imputation procedure, with different…

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…

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).

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

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.

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.

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.

DROUGHT FORECASTING BASED ON MACHINE LEARNING OF REMOTE SENSING AND LONG-RANGE FORECAST DATA

Directory of Open Access Journals (Sweden)

J. Rhee

2016-06-01

Full Text Available The reduction of drought impacts may be achieved through sustainable drought management and proactive measures against drought disaster. Accurate and timely provision of drought information is essential. In this study, drought forecasting models to provide high-resolution drought information based on drought indicators for ungauged areas were developed. The developed models predict drought indices of the 6-month Standardized Precipitation Index (SPI6 and the 6-month Standardized Precipitation Evapotranspiration Index (SPEI6. An interpolation method based on multiquadric spline interpolation method as well as three machine learning models were tested. Three machine learning models of Decision Tree, Random Forest, and Extremely Randomized Trees were tested to enhance the provision of drought initial conditions based on remote sensing data, since initial conditions is one of the most important factors for drought forecasting. Machine learning-based methods performed better than interpolation methods for both classification and regression, and the methods using climatology data outperformed the methods using long-range forecast. The model based on climatological data and the machine learning method outperformed overall.

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.

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

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.

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…

[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.

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.

Solution Methods for Structures with Random Properties Subject to Random Excitation

DEFF Research Database (Denmark)

Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.

This paper deals with the lower order statistical moments of the response of structures with random stiffness and random damping properties subject to random excitation. The arising stochastic differential equations (SDE) with random coefficients are solved by two methods, a second order...... the SDE with random coefficients with deterministic initial conditions to an equivalent nonlinear SDE with deterministic coefficient and random initial conditions. In both methods, the statistical moment equations are used. Hierarchy of statistical moments in the markovian approach is closed...... by the cumulant neglect closure method applied at the fourth order level....

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.

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.

Effectiveness of the 'Healthy School and Drugs' prevention programme on adolescents' substance use: a randomized clustered trial

NARCIS (Netherlands)

Malmberg, M.; Kleinjan, M.; Overbeek, G.; Vermulst, A.; Monshouwer, K.; Lammers, J.; Vollebergh, W.A.M.; Engels, R.C.M.E.

2014-01-01

Aim: To evaluate the effectiveness of the Healthy School and Drugs programme on alcohol, tobacco and marijuana use among Dutch early adolescents. Design: Randomized clustered trial with two intervention conditions (i.e. e-learning and integral). Setting: General population of 11-15-year-old

Effectiveness of the 'Healthy School and Drugs' prevention programme on adolescents' substance use : A randomized clustered trial

NARCIS (Netherlands)

Malmberg, Monique; Kleinjan, Marloes; Overbeek, Geertjan; Vermulst, Ad; Monshouwer, Karin; Lammers, Jeroen; Vollebergh, Wilma A M; Engels, Rutger C M E

2014-01-01

Aim: To evaluate the effectiveness of the Healthy School and Drugs programme on alcohol, tobacco and marijuana use among Dutch early adolescents. Design: Randomized clustered trial with two intervention conditions (i.e. e-learning and integral). Setting: General population of 11-15-year-old

Effectiveness of the 'Healthy School and Drugs' prevention programme on adolescents' substance use: a randomized clustered trial

NARCIS (Netherlands)

Malmberg, M.; Kleinjan, M.; Overbeek, G.J.; Vermulst, A.A.; Monshouwer, K.; Lammers, J.; Vollebergh, W.A.M.; Engels, R.C.M.E.

2014-01-01

Aim To evaluate the effectiveness of the Healthy School and Drugs programme on alcohol, tobacco and marijuana use among Dutch early adolescents. Design Randomized clustered trial with two intervention conditions (i.e. e-learning and integral). Setting General population of 11-15-year-old adolescents

Gift from statistical learning: Visual statistical learning enhances memory for sequence elements and impairs memory for items that disrupt regularities.

Science.gov (United States)

Otsuka, Sachio; Saiki, Jun

2016-02-01

Prior studies have shown that visual statistical learning (VSL) enhances familiarity (a type of memory) of sequences. How do statistical regularities influence the processing of each triplet element and inserted distractors that disrupt the regularity? Given that increased attention to triplets induced by VSL and inhibition of unattended triplets, we predicted that VSL would promote memory for each triplet constituent, and degrade memory for inserted stimuli. Across the first two experiments, we found that objects from structured sequences were more likely to be remembered than objects from random sequences, and that letters (Experiment 1) or objects (Experiment 2) inserted into structured sequences were less likely to be remembered than those inserted into random sequences. In the subsequent two experiments, we examined an alternative account for our results, whereby the difference in memory for inserted items between structured and random conditions is due to individuation of items within random sequences. Our findings replicated even when control letters (Experiment 3A) or objects (Experiment 3B) were presented before or after, rather than inserted into, random sequences. Our findings suggest that statistical learning enhances memory for each item in a regular set and impairs memory for items that disrupt the regularity. Copyright © 2015 Elsevier B.V. All rights reserved.

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

eEduHeart I: A Multicenter, Randomized, Controlled Trial Investigating the Effectiveness of a Cardiac Web-Based eLearning Platform - Rationale and Study Design.

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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.

Improving Pediatric Basic Life Support Performance Through Blended Learning With Web-Based Virtual Patients: Randomized Controlled Trial.

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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.

Immersive and interactive virtual reality to improve learning and retention of neuroanatomy in medical students: a randomized controlled study.

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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.

Policy-into-practice for rheumatoid arthritis: randomized controlled trial and cohort study of e-learning targeting improved physiotherapy management.

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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.

Evaluative Conditioning with Facial Stimuli in Dementia Patients

OpenAIRE

Blessing, Andreas; Zöllig, Jacqueline; Weierstall, Roland; Dammann, Gerhard; Martin, Mike

2013-01-01

We present results of a study investigating evaluative learning in dementia patients with a classic evaluative conditioning paradigm. Picture pairs of three unfamiliar faces with liked, disliked, or neutral faces, that were rated prior to the presentation, were presented 10 times each to a group of dementia patients (N = 15) and healthy controls (N = 14) in random order. Valence ratings of all faces were assessed before and after presentation. In contrast to controls, dementia patients chan...

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

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

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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.

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

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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.

Cognitive Style and Mobile E-Learning in Emergent Otorhinolaryngology-Head and Neck Surgery Disorders for Millennial Undergraduate Medical Students: Randomized Controlled Trial.

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Lee, Li-Ang; Chao, Yi-Ping; Huang, Chung-Guei; Fang, Ji-Tseng; Wang, Shu-Ling; Chuang, Cheng-Keng; Kang, Chung-Jan; Hsin, Li-Jen; Lin, Wan-Ni; Fang, Tuan-Jen; Li, Hsueh-Yu

2018-02-13

Electronic learning (e-learning) through mobile technology represents a novel way to teach emergent otorhinolaryngology-head and neck surgery (ORL-HNS) disorders to undergraduate medical students. Whether a cognitive style of education combined with learning modules can impact learning outcomes and satisfaction in millennial medical students is unknown. The aim of this study was to assess the impact of cognitive styles and learning modules using mobile e-learning on knowledge gain, competence gain, and satisfaction for emergent ORL-HNS disorders. This randomized controlled trial included 60 undergraduate medical students who were novices in ORL-HNS at an academic teaching hospital. The cognitive style of the participants was assessed using the group embedded figures test. The students were randomly assigned (1:1) to a novel interactive multimedia (IM) group and conventional Microsoft PowerPoint show (PPS) group matched by age, sex, and cognitive style. The content for the gamified IM module was derived from and corresponded to the textbook-based learning material of the PPS module (video lectures). The participants were unblinded and used fully automated courseware containing the IM or PPS module on a 7-inch tablet for 100 min. Knowledge and competence were assessed using multiple-choice questions and multimedia situation tests, respectively. Each participant also rated their global satisfaction. All of the participants (median age 23 years, range 22-26 years; 36 males and 24 females) received the intended intervention after randomization. Overall, the participants had significant gains in knowledge (median 50%, interquartile range [IQR]=17%-80%, Plearning modules (IM or PPS) had significant effects on both knowledge gain (both adjusted Plearning is an effective modality to improve knowledge of emergent ORL-HNS in millennial undergraduate medical students. Our findings suggest the necessity of developing various modules for undergraduate medical students with

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

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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.

Influence of case-based e-learning on students' performance in point-of-care ultrasound courses: a randomized trial.

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

2016-08-01

Theoretical knowledge, visual perception, and sensorimotor skills are key elements in ultrasound education. Classroom-based presentations are used routinely to teach theoretical knowledge, whereas visual perception and sensorimotor skills typically require hands-on training (HT). We aimed to compare the effect of classroom-based lectures versus a case-based e-learning (based on clinical cases only) on the hands-on performance of trainees during an emergency ultrasound course. This is a randomized, controlled, parallel-group study. Sixty-two medical students were randomized into two groups [group 1 (G1) and group 2 (G2)]. G1 (n=29) was subjected to a precourse e-learning, based on 14 short screencasts (each 5 min), an on-site discussion (60 min), and a standardized HT session on the day of the course. G2 (n=31) received classroom-based presentations on the day of the course before an identical HT session. Both groups completed a multiple-choice (MC) pretest (test A), a practical postcourse test (objective structured clinical exam), and MC tests directly after the HT (test B) and 1 day after the course (test C). The Mann-Whitney U-test was used for statistical analysis. G1 performed markedly better in test A (median 84.2, 25%; 75% percentile: 68.5; 92.2) compared with G2 (65.8; 53.8; 80.4), who had not participated in case-based e-learning (P=0.0009). No differences were found in the objective structured clinical exam, test B, and test C. e-learning exclusively based on clinical cases is an effective method of education in preparation for HT sessions and can reduce attendance time in ultrasound courses.

Strategic Resource Use for Learning: A Self-Administered Intervention That Guides Self-Reflection on Effective Resource Use Enhances Academic Performance.

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Chen, Patricia; Chavez, Omar; Ong, Desmond C; Gunderson, Brenda

2017-06-01

Many educational policies provide learners with more resources (e.g., new learning activities, study materials, or technologies), but less often do they address whether students are using these resources effectively. We hypothesized that making students more self-reflective about how they should approach their learning with the resources available to them would improve their class performance. We designed a novel Strategic Resource Use intervention that students could self-administer online and tested its effects in two cohorts of a college-level introductory statistics class. Before each exam, students randomly assigned to the treatment condition strategized about which academic resources they would use for studying, why each resource would be useful, and how they would use their resources. Students randomly assigned to the treatment condition reported being more self-reflective about their learning throughout the class, used their resources more effectively, and outperformed students in the control condition by an average of one third of a letter grade in the class.

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

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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

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.

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

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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

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

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

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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.

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

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

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

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.

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…

Proactive and reactive effects of vigorous exercise on learning and vocabulary comprehension.

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Salis, Andrea S

2013-06-01

College students (N = 90) were randomly assigned to participate in vigorous, moderate or no physical exercise and vocabulary recall and comprehension learning activities under varying conditions to assess whether or not increased intensities of exercise, performed either before a vocabulary recall and comprehension learning activity (i.e., proactive effect) or after a vocabulary recall and comprehension learning activity (i.e., reactive effect), would improve vocabulary recall and comprehension. The results demonstrated that performing exercise at a vigorous intensity before or after rehearsing for a vocabulary comprehension test improved test results.

Ultrasound simulator-assisted teaching of cardiac anatomy to preclinical anatomy students: A pilot randomized trial of a three-hour learning exposure.

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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.

Three-dimensional printing model improves morphological understanding in acetabular fracture learning: A multicenter, randomized, controlled study.

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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.

Statistical learning from a regression perspective

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Berk, Richard A

2016-01-01

This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response. As a first approximation, this can be seen as an extension of nonparametric regression. This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives from sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. A continued emphasis on the implications for practice runs through the text. Among the statistical learning procedures examined are bagging, random forests, boosting, support vector machines and neural networks. Response variables may be quantitative or categorical. As in the first edition, a unifying theme is supervised learning that can be trea...

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

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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.

A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.

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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.

Predicting Coastal Flood Severity using Random Forest Algorithm

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Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

2017-12-01

Coastal floods have become more common recently and are predicted to further increase in frequency and severity due to sea level rise. Predicting floods in coastal cities can be difficult due to the number of environmental and geographic factors which can influence flooding events. Built stormwater infrastructure and irregular urban landscapes add further complexity. This paper demonstrates the use of machine learning algorithms in predicting street flood occurrence in an urban coastal setting. The model is trained and evaluated using data from Norfolk, Virginia USA from September 2010 - October 2016. Rainfall, tide levels, water table levels, and wind conditions are used as input variables. Street flooding reports made by city workers after named and unnamed storm events, ranging from 1-159 reports per event, are the model output. Results show that Random Forest provides predictive power in estimating the number of flood occurrences given a set of environmental conditions with an out-of-bag root mean squared error of 4.3 flood reports and a mean absolute error of 0.82 flood reports. The Random Forest algorithm performed much better than Poisson regression. From the Random Forest model, total daily rainfall was by far the most important factor in flood occurrence prediction, followed by daily low tide and daily higher high tide. The model demonstrated here could be used to predict flood severity based on forecast rainfall and tide conditions and could be further enhanced using more complete street flooding data for model training.

Guided Instruction Improves Elementary Student Learning and Self-Efficacy in Science

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Hushman, Carolyn J.; Marley, Scott C.

2015-01-01

The authors investigated whether the amount of instructional guidance affects science learning and self-efficacy. Sixty 9- and 10-year-old children were randomly assigned to one of the following three instructional conditions: (a) guided instruction consisting of examples and student-generated explanations, (b) direct instruction consisting of a…

Effects of Multimedia and Schema Induced Analogical Reasoning on Science Learning

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Zheng, R. Z.; Yang, W.; Garcia, D.; McCadden, E. P.

2008-01-01

The present study investigates the effects of multimedia and schema induced analogical reasoning on science learning. It involves 89 fourth grade elementary students in the north-east of the United States. Participants are randomly assigned into four conditions: (a) multimedia with analogy; (b) multimedia without analogy; (c) analogy without…

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

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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.

Engaging Environments Enhance Motor Skill Learning in a Computer Gaming Task.

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Lohse, Keith R; Boyd, Lara A; Hodges, Nicola J

2016-01-01

Engagement during practice can motivate a learner to practice more, hence having indirect effects on learning through increased practice. However, it is not known whether engagement can also have a direct effect on learning when the amount of practice is held constant. To address this question, 40 participants played a video game that contained an embedded repeated sequence component, under either highly engaging conditions (the game group) or mechanically identical but less engaging conditions (the sterile group). The game environment facilitated retention over a 1-week interval. Specifically, the game group improved in both speed and accuracy for random and repeated trials, suggesting a general motor-related improvement, rather than a specific influence of engagement on implicit sequence learning. These data provide initial evidence that increased engagement during practice has a direct effect on generalized learning, improving retention and transfer of a complex motor skill.

Cognitive Style and Mobile E-Learning in Emergent Otorhinolaryngology-Head and Neck Surgery Disorders for Millennial Undergraduate Medical Students: Randomized Controlled Trial

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Chao, Yi-Ping; Huang, Chung-Guei; Fang, Ji-Tseng; Wang, Shu-Ling; Chuang, Cheng-Keng; Kang, Chung-Jan; Hsin, Li-Jen; Lin, Wan-Ni; Fang, Tuan-Jen; Li, Hsueh-Yu

2018-01-01

Background Electronic learning (e-learning) through mobile technology represents a novel way to teach emergent otorhinolaryngology-head and neck surgery (ORL-HNS) disorders to undergraduate medical students. Whether a cognitive style of education combined with learning modules can impact learning outcomes and satisfaction in millennial medical students is unknown. Objective The aim of this study was to assess the impact of cognitive styles and learning modules using mobile e-learning on knowledge gain, competence gain, and satisfaction for emergent ORL-HNS disorders. Methods This randomized controlled trial included 60 undergraduate medical students who were novices in ORL-HNS at an academic teaching hospital. The cognitive style of the participants was assessed using the group embedded figures test. The students were randomly assigned (1:1) to a novel interactive multimedia (IM) group and conventional Microsoft PowerPoint show (PPS) group matched by age, sex, and cognitive style. The content for the gamified IM module was derived from and corresponded to the textbook-based learning material of the PPS module (video lectures). The participants were unblinded and used fully automated courseware containing the IM or PPS module on a 7-inch tablet for 100 min. Knowledge and competence were assessed using multiple-choice questions and multimedia situation tests, respectively. Each participant also rated their global satisfaction. Results All of the participants (median age 23 years, range 22-26 years; 36 males and 24 females) received the intended intervention after randomization. Overall, the participants had significant gains in knowledge (median 50%, interquartile range [IQR]=17%-80%, P<.001) and competence (median 13%, IQR=0%-33%, P=.006). There were no significant differences in knowledge gain (40%, IQR=13%-76% vs 60%, IQR=20%-100%, P=.42) and competence gain (0%, IQR= −21% to 38% vs 25%, IQR=0%-33%, P=.16) between the IM and PPS groups. However, the IM group had

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

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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.

Random a-adic groups and random net fractals

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Li Yin [Department of Mathematics, Nanjing University, Nanjing 210093 (China)], E-mail: Lyjerry7788@hotmail.com; Su Weiyi [Department of Mathematics, Nanjing University, Nanjing 210093 (China)], E-mail: suqiu@nju.edu.cn

2008-08-15

Based on random a-adic groups, this paper investigates the relationship between the existence conditions of a positive flow in a random network and the estimation of the Hausdorff dimension of a proper random net fractal. Subsequently we describe some particular random fractals for which our results can be applied. Finally the Mauldin and Williams theorem is shown to be very important example for a random Cantor set with application in physics as shown in E-infinity theory.

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

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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…

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

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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.

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

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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

Conditions for excellence in teaching in medical education: The Frankfurt Model to ensure quality in teaching and learning

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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.

Comparisons between physics-based, engineering, and statistical learning models for outdoor sound propagation.

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Hart, Carl R; Reznicek, Nathan J; Wilson, D Keith; Pettit, Chris L; Nykaza, Edward T

2016-05-01

Many outdoor sound propagation models exist, ranging from highly complex physics-based simulations to simplified engineering calculations, and more recently, highly flexible statistical learning methods. Several engineering and statistical learning models are evaluated by using a particular physics-based model, namely, a Crank-Nicholson parabolic equation (CNPE), as a benchmark. Narrowband transmission loss values predicted with the CNPE, based upon a simulated data set of meteorological, boundary, and source conditions, act as simulated observations. In the simulated data set sound propagation conditions span from downward refracting to upward refracting, for acoustically hard and soft boundaries, and low frequencies. Engineering models used in the comparisons include the ISO 9613-2 method, Harmonoise, and Nord2000 propagation models. Statistical learning methods used in the comparisons include bagged decision tree regression, random forest regression, boosting regression, and artificial neural network models. Computed skill scores are relative to sound propagation in a homogeneous atmosphere over a rigid ground. Overall skill scores for the engineering noise models are 0.6%, -7.1%, and 83.8% for the ISO 9613-2, Harmonoise, and Nord2000 models, respectively. Overall skill scores for the statistical learning models are 99.5%, 99.5%, 99.6%, and 99.6% for bagged decision tree, random forest, boosting, and artificial neural network regression models, respectively.

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

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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

Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies

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Tjalla, Awaluddin; Sofiah, Evi

2015-01-01

This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…

OPTIMAL practice conditions enhance the benefits of gradually increasing error opportunities on retention of a stepping sequence task.

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Levac, Danielle; Driscoll, Kate; Galvez, Jessica; Mercado, Kathleen; O'Neil, Lindsey

2017-12-01

Physical therapists should implement practice conditions that promote motor skill learning after neurological injury. Errorful and errorless practice conditions are effective for different populations and tasks. Errorful learning provides opportunities for learners to make task-relevant choices. Enhancing learner autonomy through choice opportunities is a key component of the Optimizing Performance through Intrinsic Motivation and Attention for Learning (OPTIMAL) theory of motor learning. The objective of this study was to evaluate the interaction between error opportunity frequency and OPTIMAL (autonomy-supportive) practice conditions during stepping sequence acquisition in a virtual environment. Forty healthy young adults were randomized to autonomy-supportive or autonomy-controlling practice conditions, which differed in instructional language, focus of attention (external vs internal) and positive versus negative nature of verbal and visual feedback. All participants practiced 40 trials of 4, six-step stepping sequences in a random order. Each of the 4 sequences offered different amounts of choice opportunities about the next step via visual cue presentation (4 choices; 1 choice; gradually increasing [1-2-3-4] choices, and gradually decreasing [4-3-2-1] choices). Motivation and engagement were measured by the Intrinsic Motivation Inventory (IMI) and the User Engagement Scale (UES). Participants returned 1-3 days later for retention tests, where learning was measured by time to complete each sequence. No choice cues were offered on retention. Participants in the autonomy-supportive group outperformed the autonomy-controlling group at retention on all sequences (mean difference 2.88s, p errorful (4 choice) sequence (p error opportunities over time, suggest that participants relied on implicit learning strategies for this full body task and that feedback about successes minimized errors and reduced their potential information-processing benefits. Subsequent

Active learning: a step towards automating medical concept extraction.

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Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2016-03-01

This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robustness of incremental active learning framework across different selection criteria and data sets are determined. The comparative performance of an active learning framework and a fully supervised approach were investigated to study how active learning reduces the annotation effort while achieving the same effectiveness as a supervised approach. Conditional random fields as the supervised method, and least confidence and information density as 2 selection criteria for active learning framework were used. The effect of incremental learning vs standard learning on the robustness of the models within the active learning framework with different selection criteria was also investigated. The following 2 clinical data sets were used for evaluation: the Informatics for Integrating Biology and the Bedside/Veteran Affairs (i2b2/VA) 2010 natural language processing challenge and the Shared Annotated Resources/Conference and Labs of the Evaluation Forum (ShARe/CLEF) 2013 eHealth Evaluation Lab. The annotation effort saved by active learning to achieve the same effectiveness as supervised learning is up to 77%, 57%, and 46% of the total number of sequences, tokens, and concepts, respectively. Compared with the random sampling baseline, the saving is at least doubled. Incremental active learning is a promising approach for building effective and robust medical concept extraction models while significantly reducing the burden of manual annotation. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

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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.

Music listening while you learn: no influence of background music on verbal learning.

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Jäncke, Lutz; Sandmann, Pascale

2010-01-07

Whether listening to background music enhances verbal learning performance is still disputed. In this study we investigated the influence of listening to background music on verbal learning performance and the associated brain activations. Musical excerpts were composed for this study to ensure that they were unknown to the subjects and designed to vary in tempo (fast vs. slow) and consonance (in-tune vs. out-of-tune). Noise was used as control stimulus. 75 subjects were randomly assigned to one of five groups and learned the presented verbal material (non-words with and without semantic connotation) with and without background music. Each group was exposed to one of five different background stimuli (in-tune fast, in-tune slow, out-of-tune fast, out-of-tune slow, and noise). As dependent variable, the number of learned words was used. In addition, event-related desynchronization (ERD) and event-related synchronization (ERS) of the EEG alpha-band were calculated as a measure for cortical activation. We did not find any substantial and consistent influence of background music on verbal learning. There was neither an enhancement nor a decrease in verbal learning performance during the background stimulation conditions. We found however a stronger event-related desynchronization around 800 - 1200 ms after word presentation for the group exposed to in-tune fast music while they learned the verbal material. There was also a stronger event-related synchronization for the group exposed to out-of-tune fast music around 1600 - 2000 ms after word presentation. Verbal learning during the exposure to different background music varying in tempo and consonance did not influence learning of verbal material. There was neither an enhancing nor a detrimental effect on verbal learning performance. The EEG data suggest that the different acoustic background conditions evoke different cortical activations. The reason for these different cortical activations is unclear. The most

Music listening while you learn: No influence of background music on verbal learning

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Sandmann Pascale

2010-01-01

Full Text Available Abstract Background Whether listening to background music enhances verbal learning performance is still disputed. In this study we investigated the influence of listening to background music on verbal learning performance and the associated brain activations. Methods Musical excerpts were composed for this study to ensure that they were unknown to the subjects and designed to vary in tempo (fast vs. slow and consonance (in-tune vs. out-of-tune. Noise was used as control stimulus. 75 subjects were randomly assigned to one of five groups and learned the presented verbal material (non-words with and without semantic connotation with and without background music. Each group was exposed to one of five different background stimuli (in-tune fast, in-tune slow, out-of-tune fast, out-of-tune slow, and noise. As dependent variable, the number of learned words was used. In addition, event-related desynchronization (ERD and event-related synchronization (ERS of the EEG alpha-band were calculated as a measure for cortical activation. Results We did not find any substantial and consistent influence of background music on verbal learning. There was neither an enhancement nor a decrease in verbal learning performance during the background stimulation conditions. We found however a stronger event-related desynchronization around 800 - 1200 ms after word presentation for the group exposed to in-tune fast music while they learned the verbal material. There was also a stronger event-related synchronization for the group exposed to out-of-tune fast music around 1600 - 2000 ms after word presentation. Conclusion Verbal learning during the exposure to different background music varying in tempo and consonance did not influence learning of verbal material. There was neither an enhancing nor a detrimental effect on verbal learning performance. The EEG data suggest that the different acoustic background conditions evoke different cortical activations. The reason for

Fuzzy self-learning control for magnetic servo system

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

1994-01-01

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

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.

Comparative Study of Learning Using E-Learning and Printed Materials on Independent Learning and Creativity

Science.gov (United States)

Wahyu Utami, Niken; Aziz Saefudin, Abdul

2018-01-01

This study aims to determine: 1) differences in students taking independent learning by using e-learning and the students who attend the learning by using the print instructional materials ; 2) differences in the creativity of students who follow learning with e-learning and the students who attend the learning by using the print instructional materials ; 3) differences in learning independence and creativity of students attend learning with e-learning and the students who attend lessons using printed teaching materials in the subject of Mathematics Instructional Media Development. This study was a quasi-experimental research design using only posttest control design. The study population was all students who take courses in Learning Mathematics Media Development, Academic Year 2014/2015 100 students and used a random sample (random sampling) is 60 students. To test the hypothesis used multivariate analysis of variance or multivariable analysis of variance (MANOVA) of the track. The results of this study indicate that 1) There is a difference in student learning independence following study using the e-learning and the students who attend lessons using printed teaching materials in the lecture PMPM ( F = 4.177, p = 0.046 0.05) ; No difference learning independence and creativity of students attend learning by using e-learning and the students who attend the learning using printed teaching materials in the lecture PMPM (F = 2.452, p = 0.095 > 0.05). Based on these studies suggested that the learning using e -learning can be used to develop student creativity, while learning to use e -learning and teaching materials can be printed to use to develop students’ independence.

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

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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

Machine learning a probabilistic perspective

CERN Document Server

Murphy, Kevin P

2012-01-01

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic method...

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.

The effect of observational learning on students' performance, processes, and motivation in two creative domains.

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Groenendijk, Talita; Janssen, Tanja; Rijlaarsdam, Gert; van den Bergh, Huub

2013-03-01

Previous research has shown that observation can be effective for learning in various domains, for example, argumentative writing and mathematics. The question in this paper is whether observational learning can also be beneficial when learning to perform creative tasks in visual and verbal arts. We hypothesized that observation has a positive effect on performance, process, and motivation. We expected similarity in competence between the model and the observer to influence the effectiveness of observation. Sample.  A total of 131 Dutch students (10(th) grade, 15 years old) participated. Two experiments were carried out (one for visual and one for verbal arts). Participants were randomly assigned to one of three conditions; two observational learning conditions and a control condition (learning by practising). The observational learning conditions differed in instructional focus (on the weaker or the more competent model of a pair to be observed). We found positive effects of observation on creative products, creative processes, and motivation in the visual domain. In the verbal domain, observation seemed to affect the creative process, but not the other variables. The model similarity hypothesis was not confirmed. Results suggest that observation may foster learning in creative domains, especially in the visual arts. © 2011 The British Psychological Society.

Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis

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Clark, Douglas B.; Tanner-Smith, Emily E.; Killingsworth, Stephen S.

2016-01-01

In this meta-analysis, we systematically reviewed research on digital games and learning for K-16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust…

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

Learning of pitch and time structures in an artificial grammar setting.

Science.gov (United States)

Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Learning stochastic reward distributions in a speeded pointing task.

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Seydell, Anna; McCann, Brian C; Trommershäuser, Julia; Knill, David C

2008-04-23

Recent studies have shown that humans effectively take into account task variance caused by intrinsic motor noise when planning fast hand movements. However, previous evidence suggests that humans have greater difficulty accounting for arbitrary forms of stochasticity in their environment, both in economic decision making and sensorimotor tasks. We hypothesized that humans can learn to optimize movement strategies when environmental randomness can be experienced and thus implicitly learned over several trials, especially if it mimics the kinds of randomness for which subjects might have generative models. We tested the hypothesis using a task in which subjects had to rapidly point at a target region partly covered by three stochastic penalty regions introduced as "defenders." At movement completion, each defender jumped to a new position drawn randomly from fixed probability distributions. Subjects earned points when they hit the target, unblocked by a defender, and lost points otherwise. Results indicate that after approximately 600 trials, subjects approached optimal behavior. We further tested whether subjects simply learned a set of stimulus-contingent motor plans or the statistics of defenders' movements by training subjects with one penalty distribution and then testing them on a new penalty distribution. Subjects immediately changed their strategy to achieve the same average reward as subjects who had trained with the second penalty distribution. These results indicate that subjects learned the parameters of the defenders' jump distributions and used this knowledge to optimally plan their hand movements under conditions involving stochastic rewards and penalties.

Learning to Learn.

Science.gov (United States)

Weiss, Helen; Weiss, Martin

1988-01-01

The article reviews theories of learning (e.g., stimulus-response, trial and error, operant conditioning, cognitive), considers the role of motivation, and summarizes nine research-supported rules of effective learning. Suggestions are applied to teaching learning strategies to learning-disabled students. (DB)

Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis.

Science.gov (United States)

Clark, Douglas B; Tanner-Smith, Emily E; Killingsworth, Stephen S

2016-03-01

In this meta-analysis, we systematically reviewed research on digital games and learning for K-16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions ([Formula: see text] = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value-added comparisons indicated significant learning benefits associated with augmented game designs ([Formula: see text] = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium.

Motor sequence learning occurs despite disrupted visual and proprioceptive feedback

Directory of Open Access Journals (Sweden)

Boyd Lara A

2008-07-01

Full Text Available Abstract Background Recent work has demonstrated the importance of proprioception for the development of internal representations of the forces encountered during a task. Evidence also exists for a significant role for proprioception in the execution of sequential movements. However, little work has explored the role of proprioceptive sensation during the learning of continuous movement sequences. Here, we report that the repeated segment of a continuous tracking task can be learned despite peripherally altered arm proprioception and severely restricted visual feedback regarding motor output. Methods Healthy adults practiced a continuous tracking task over 2 days. Half of the participants experienced vibration that altered proprioception of shoulder flexion/extension of the active tracking arm (experimental condition and half experienced vibration of the passive resting arm (control condition. Visual feedback was restricted for all participants. Retention testing was conducted on a separate day to assess motor learning. Results Regardless of vibration condition, participants learned the repeated segment demonstrated by significant improvements in accuracy for tracking repeated as compared to random continuous movement sequences. Conclusion These results suggest that with practice, participants were able to use residual afferent information to overcome initial interference of tracking ability related to altered proprioception and restricted visual feedback to learn a continuous motor sequence. Motor learning occurred despite an initial interference of tracking noted during acquisition practice.

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

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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.

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

Motor sequence learning-induced neural efficiency in functional brain connectivity.

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Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M

2017-02-15

Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.

Impact of eLearning course on nurses' professional competence in seclusion and restraint practices: a randomized controlled study (ISRCTN32869544).

Science.gov (United States)

Kontio, R; Lahti, M; Pitkänen, A; Joffe, G; Putkonen, H; Hätönen, H; Katajisto, J; Välimäki, M

2011-11-01

Education on the care of aggressive and disturbed patients is fragmentary. eLearning could ensure the quality of such education, but data on its impact on professional competence in psychiatry are lacking. The aim of this study was to explore the impact of ePsychNurse.Net, an eLearning course, on psychiatric nurses' professional competence in seclusion and restraint and on their job satisfaction and general self-efficacy. In a randomized controlled study, 12 wards were randomly assigned to ePsychNurse.Net (intervention) or education as usual (control). Baseline and 3-month follow-up data on nurses' knowledge of coercion-related legislation, physical restraint and seclusion, their attitudes towards physical restraint and seclusion, job satisfaction and general self-efficacy were analysed for 158 completers. Knowledge (primary outcome) of coercion-related legislation improved in the intervention group, while knowledge of physical restraint improved and knowledge of seclusion remained unchanged in both groups. General self-efficacy improved in the intervention group also attitude to seclusion in the control group. In between-group comparison, attitudes to seclusion (one of secondary outcomes) favoured the control group. Although the ePsychNurse.Net demonstrated only slight advantages over conventional learning, it may be worth further development with, e.g. flexible time schedule and individualized content. © 2011 Blackwell Publishing.

Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models

Directory of Open Access Journals (Sweden)

Seyed Mehran Kazemi

2018-02-01

Full Text Available The aim of statistical relational learning is to learn statistical models from relational or graph-structured data. Three main statistical relational learning paradigms include weighted rule learning, random walks on graphs, and tensor factorization. These paradigms have been mostly developed and studied in isolation for many years, with few works attempting at understanding the relationship among them or combining them. In this article, we study the relationship between the path ranking algorithm (PRA, one of the most well-known relational learning methods in the graph random walk paradigm, and relational logistic regression (RLR, one of the recent developments in weighted rule learning. We provide a simple way to normalize relations and prove that relational logistic regression using normalized relations generalizes the path ranking algorithm. This result provides a better understanding of relational learning, especially for the weighted rule learning and graph random walk paradigms. It opens up the possibility of using the more flexible RLR rules within PRA models and even generalizing both by including normalized and unnormalized relations in the same model.

Application of Vector Triggering Random Decrement

DEFF Research Database (Denmark)

Asmussen, J. C.; Ibrahim, S. R.; Brincker, Rune

result is a Random Decrement function from each measurement. In traditional Random Decrement estimation the triggering condition is a scalar condition, which should only be fulfilled in a single measurement. In vector triggering Random Decrement the triggering condition is a vector condition......This paper deals with applications of the vector triggering Random Decrement technique. This technique is new and developed with the aim of minimizing estimation time and identification errors. The theory behind the technique is discussed in an accompanying paper. The results presented...... in this paper should be regarded as a further documentation of the technique. The key point in Random Decrement estimation is the formulation of a triggering condition. If the triggering condition is fulfilled a time segment from each measurement is picked out and averaged with previous time segments. The final...

Application of Vector Triggering Random Decrement

DEFF Research Database (Denmark)

Asmussen, J. C.; Ibrahim, S. R.; Brincker, Rune

1997-01-01

result is a Random Decrement function from each measurement. In traditional Random Decrement estimation the triggering condition is a scalar condition, which should only be fulfilled in a single measurement. In vector triggering Random Decrement the triggering condition is a vector condition......This paper deals with applications of the vector triggering Random Decrement technique. This technique is new and developed with the aim of minimizing estimation time and identification errors. The theory behind the technique is discussed in an accompanying paper. The results presented...... in this paper should be regarded as a further documentation of the technique. The key point in Random Decrement estimation is the formulation of a triggering condition. If the triggering condition is fulfilled a time segment from each measurement is picked out and averaged with previous time segments. The final...

Predicting the dissolution kinetics of silicate glasses using machine learning

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

2018-05-01

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

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.

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

Verbal learning in the context of background music: no influence of vocals and instrumentals on verbal learning.

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Jäncke, Lutz; Brügger, Eliane; Brummer, Moritz; Scherrer, Stephanie; Alahmadi, Nsreen

2014-03-26

Whether listening to background music enhances verbal learning performance is still a matter of dispute. In this study we investigated the influence of vocal and instrumental background music on verbal learning. 226 subjects were randomly assigned to one of five groups (one control group and 4 experimental groups). All participants were exposed to a verbal learning task. One group served as control group while the 4 further groups served as experimental groups. The control group learned without background music while the 4 experimental groups were exposed to vocal or instrumental musical pieces during learning with different subjective intensity and valence. Thus, we employed 4 music listening conditions (vocal music with high intensity: VOC_HIGH, vocal music with low intensity: VOC_LOW, instrumental music with high intensity: INST_HIGH, instrumental music with low intensity: INST_LOW) and one control condition (CONT) during which the subjects learned the word lists. Since it turned out that the high and low intensity groups did not differ in terms of the rated intensity during the main experiment these groups were lumped together. Thus, we worked with 3 groups: one control group and two groups, which were exposed to background music (vocal and instrumental) during verbal learning. As dependent variable, the number of learned words was used. Here we measured immediate recall during five learning sessions (recall 1 - recall 5) and delayed recall for 15 minutes (recall 6) and 14 days (recall 7) after the last learning session. Verbal learning improved during the first 5 recall sessions without any strong difference between the control and experimental groups. Also the delayed recalls were similar for the three groups. There was only a trend for attenuated verbal learning for the group passively listened to vocals. This learning attenuation diminished during the following learning sessions. The exposure to vocal or instrumental background music during encoding did not

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.

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.

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.

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

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

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

Duration of the Unconditioned Stimulus in Appetitive Conditioning of Honeybees Differentially Impacts Learning, Long-Term Memory Strength, and the Underlying Protein Synthesis

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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…

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

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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.

Fault diagnosis in spur gears based on genetic algorithm and random forest

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Cerrada, Mariela; Zurita, Grover; Cabrera, Diego; Sánchez, René-Vinicio; Artés, Mariano; Li, Chuan

2016-03-01

There are growing demands for condition-based monitoring of gearboxes, and therefore new methods to improve the reliability, effectiveness, accuracy of the gear fault detection ought to be evaluated. Feature selection is still an important aspect in machine learning-based diagnosis in order to reach good performance of the diagnostic models. On the other hand, random forest classifiers are suitable models in industrial environments where large data-samples are not usually available for training such diagnostic models. The main aim of this research is to build up a robust system for the multi-class fault diagnosis in spur gears, by selecting the best set of condition parameters on time, frequency and time-frequency domains, which are extracted from vibration signals. The diagnostic system is performed by using genetic algorithms and a classifier based on random forest, in a supervised environment. The original set of condition parameters is reduced around 66% regarding the initial size by using genetic algorithms, and still get an acceptable classification precision over 97%. The approach is tested on real vibration signals by considering several fault classes, one of them being an incipient fault, under different running conditions of load and velocity.

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

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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.

How random are random numbers generated using photons?

International Nuclear Information System (INIS)

Solis, Aldo; Angulo Martínez, Alí M; Ramírez Alarcón, Roberto; Cruz Ramírez, Hector; U’Ren, Alfred B; Hirsch, Jorge G

2015-01-01

Randomness is fundamental in quantum theory, with many philosophical and practical implications. In this paper we discuss the concept of algorithmic randomness, which provides a quantitative method to assess the Borel normality of a given sequence of numbers, a necessary condition for it to be considered random. We use Borel normality as a tool to investigate the randomness of ten sequences of bits generated from the differences between detection times of photon pairs generated by spontaneous parametric downconversion. These sequences are shown to fulfil the randomness criteria without difficulties. As deviations from Borel normality for photon-generated random number sequences have been reported in previous work, a strategy to understand these diverging findings is outlined. (paper)

Repeated testing improves achievement in a blended learning approach for risk competence training of medical students: results of a randomized controlled trial.

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Spreckelsen, C; Juenger, J

2017-09-26

Adequate estimation and communication of risks is a critical competence of physicians. Due to an evident lack of these competences, effective training addressing risk competence during medical education is needed. Test-enhanced learning has been shown to produce marked effects on achievements. This study aimed to investigate the effect of repeated tests implemented on top of a blended learning program for risk competence. We introduced a blended-learning curriculum for risk estimation and risk communication based on a set of operationalized learning objectives, which was integrated into a mandatory course "Evidence-based Medicine" for third-year students. A randomized controlled trial addressed the effect of repeated testing on achievement as measured by the students' pre- and post-training score (nine multiple-choice items). Basic numeracy and statistical literacy were assessed at baseline. Analysis relied on descriptive statistics (histograms, box plots, scatter plots, and summary of descriptive measures), bootstrapped confidence intervals, analysis of covariance (ANCOVA), and effect sizes (Cohen's d, r) based on adjusted means and standard deviations. All of the 114 students enrolled in the course consented to take part in the study and were assigned to either the intervention or control group (both: n = 57) by balanced randomization. Five participants dropped out due to non-compliance (control: 4, intervention: 1). Both groups profited considerably from the program in general (Cohen's d for overall pre vs. post scores: 2.61). Repeated testing yielded an additional positive effect: while the covariate (baseline score) exhibits no relation to the post-intervention score, F(1, 106) = 2.88, p > .05, there was a significant effect of the intervention (repeated tests scenario) on learning achievement, F(1106) = 12.72, p blended learning approach can be improved significantly by implementing a test-enhanced learning design, namely repeated testing. As

Orthopaedic resident preparedness for closed reduction and pinning of pediatric supracondylar fractures is improved by e-learning: a multisite randomized controlled study.

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Hearty, Thomas; Maizels, Max; Pring, Maya; Mazur, John; Liu, Raymond; Sarwark, John; Janicki, Joseph

2013-09-04

There is a need to provide more efficient surgical training methods for orthopaedic residents. E-learning could possibly increase resident surgical preparedness, confidence, and comfort for surgery. Using closed reduction and pinning of pediatric supracondylar humeral fractures as the index case, we hypothesized that e-learning could increase resident knowledge acquisition for case preparation in the operating room. An e-learning surgical training module was created on the Computer Enhanced Visual Learning platform. The module provides a detailed and focused road map of the procedure utilizing a multimedia format. A multisite prospective randomized controlled study design compared residents who used a textbook for case preparation (control group) with residents who used the same textbook plus completed the e-learning module (test group). All subjects completed a sixty-question test on the theory and methods of the case. After completion of the test, the control group then completed the module as well. All subjects were surveyed on their opinion regarding the effectiveness of the module after performing an actual surgical case. Twenty-eight subjects with no previous experience in this surgery were enrolled at four academic centers. Subjects were randomized into two equal groups. The test group scored significantly better (p < 0.001) and demonstrated competence on the test compared with the control group; the mean correct test score (and standard deviation) was 90.9% ± 6.8% for the test group and 73.5% ± 6.4% for the control group. All residents surveyed (n = 27) agreed that the module is a useful supplement to traditional methods for case preparation and twenty-two of twenty-seven residents agreed that it reduced their anxiety during the case and improved their attention to surgical detail. E-learning using the Computer Enhanced Visual Learning platform significantly improved preparedness, confidence, and comfort with percutaneous closed reduction and pinning of a

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

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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%.

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....

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

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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…

Feedback Both Helps and Hinders Learning: The Causal Role of Prior Knowledge

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Fyfe, Emily R.; Rittle-Johnson, Bethany

2016-01-01

Feedback can be a powerful learning tool, but its effects vary widely. Research has suggested that learners' prior knowledge may moderate the effects of feedback; however, no causal link has been established. In Experiment 1, we randomly assigned elementary school children (N = 108) to a condition based on a crossing of 2 factors: induced strategy…

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.

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...

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

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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.

Determinants of Teachers' Attitudes towards E- Learning in Tanzanian Higher Learning Institutions

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Kisanga, Dalton H.

2016-01-01

This survey research study presents the findings on determinants of teachers' attitudes towards e-learning in Tanzanian higher learning institutions. The study involved 258 teachers from 4 higher learning institutions obtained through stratified, simple random sampling. Questionnaires and documentary review were used in data collection. Data were…

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

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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.

Preschool Teachers Can Use a PBS KIDS Transmedia Curriculum Supplement to Support Young Children's Mathematics Learning: Results of a Randomized Controlled Trial

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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…

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.

Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

Science.gov (United States)

Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

Effect of Worksheet Scaffolds on Student Learning in Problem-Based Learning

Science.gov (United States)

Choo, Serene S. Y.; Rotgans, Jerome I.; Yew, Elaine H. J.; Schmidt, Henk G.

2011-01-01

The purpose of this study was to investigate the effect of worksheets as a scaffolding tool on students' learning achievement in a problem-based learning (PBL) environment. Seventeen PBL classes (N = 241) were randomly assigned to two experimental groups--one with a worksheet provided and the other without. Students' learning of the topic at hand…

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…

Lack of interaction between sensing-intuitive learning styles and problem-first versus information-first instruction: a randomized crossover trial.

Science.gov (United States)

Cook, David A; Thompson, Warren G; Thomas, Kris G; Thomas, Matthew R

2009-03-01

Adaptation to learning styles has been proposed to enhance learning. We hypothesized that learners with sensing learning style would perform better using a problem-first instructional method while intuitive learners would do better using an information-first method. Randomized, controlled, crossover trial. Resident ambulatory clinics. 123 internal medicine residents. Four Web-based modules in ambulatory internal medicine were developed in both "didactic" (information first, followed by patient problem and questions) and "problem" (case and questions first, followed by information) format. Knowledge posttest, format preference, learning style (Index of Learning Styles). Knowledge scores were similar between the didactic (mean +/- standard error, 83.0 +/- 0.8) and problem (82.3 +/- 0.8) formats (p = .42; 95% confidence interval [CI] for difference, -2.3 to 0.9). There was no difference between formats in regression slopes of knowledge scores on sensing-intuitive scores (p = .63) or in analysis of knowledge scores by styles classification (sensing 82.5 +/- 1.0, intermediate 83.7 +/- 1.2, intuitive 81.0 +/- 1.5; p = .37 for main effect, p = .59 for interaction with format). Format preference was neutral (3.2 +/- 0.2 [1 strongly prefers didactic, 6 strongly prefers problem], p = .12), and there was no association between learning styles and preference (p = .44). Formats were similar in time to complete modules (43.7 +/- 2.2 vs 43.2 +/- 2.2 minutes, p = .72). Starting instruction with a problem (versus employing problems later on) may not improve learning outcomes. Sensing and intuitive learners perform similarly following problem-first and didactic-first instruction. Results may apply to other instructional media.

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

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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.

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.

Feature selection and classification of mechanical fault of an induction motor using random forest classifier

OpenAIRE

Patel, Raj Kumar; Giri, V.K.

2016-01-01

Fault detection and diagnosis is the most important technology in condition-based maintenance (CBM) system for rotating machinery. This paper experimentally explores the development of a random forest (RF) classifier, a recently emerged machine learning technique, for multi-class mechanical fault diagnosis in bearing of an induction motor. Firstly, the vibration signals are collected from the bearing using accelerometer sensor. Parameters from the vibration signal are extracted in the form of...

Does Fine Color Discrimination Learning in Free-Flying Honeybees Change Mushroom-Body Calyx Neuroarchitecture?

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Sommerlandt, Frank M J; Spaethe, Johannes; Rössler, Wolfgang; Dyer, Adrian G

2016-01-01

Honeybees learn color information of rewarding flowers and recall these memories in future decisions. For fine color discrimination, bees require differential conditioning with a concurrent presentation of target and distractor stimuli to form a long-term memory. Here we investigated whether the long-term storage of color information shapes the neural network of microglomeruli in the mushroom body calyces and if this depends on the type of conditioning. Free-flying honeybees were individually trained to a pair of perceptually similar colors in either absolute conditioning towards one of the colors or in differential conditioning with both colors. Subsequently, bees of either conditioning groups were tested in non-rewarded discrimination tests with the two colors. Only bees trained with differential conditioning preferred the previously learned color, whereas bees of the absolute conditioning group, and a stimuli-naïve group, chose randomly among color stimuli. All bees were then kept individually for three days in the dark to allow for complete long-term memory formation. Whole-mount immunostaining was subsequently used to quantify variation of microglomeruli number and density in the mushroom-body lip and collar. We found no significant differences among groups in neuropil volumes and total microglomeruli numbers, but learning performance was negatively correlated with microglomeruli density in the absolute conditioning group. Based on these findings we aim to promote future research approaches combining behaviorally relevant color learning tests in honeybees under free-flight conditions with neuroimaging analysis; we also discuss possible limitations of this approach.

Enhancing Building, Conversation, and Learning through Caregiver-Child Interactions in a Children's Museum

Science.gov (United States)

Benjamin, Nora; Haden, Catherine A.; Wilkerson, Erin

2010-01-01

The authors adapted an experimental design to examine effects of instruction prior to entry into a children's museum exhibit on caregiver-child interactions and children's learning. One hundred twenty-one children (mean age = 6.6 years) and their caregivers were randomly assigned to 1 of 5 conditions that varied according to what, if any,…

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

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…

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.

Learned Helplessness in Exceptional Children.

Science.gov (United States)

Brock, Herman B.; Kowitz, Gerald T.

The research literature on learned helplessness in exceptional children is reviewed and the authors' efforts to identify and retrain learning disabled (LD) children who have characteristics typical of learned helplessness are reported. Twenty-eight elementary aged LD children viewed as "learned helpless" were randomly assigned to one of four…

Random maintenance policies

CERN Document Server

Nakagawa, Toshio

2014-01-01

Exploring random maintenance models, this book provides an introduction to the implementation of random maintenance, and it is one of the first books to be written on this subject.  It aims to help readers learn new techniques for applying random policies to actual reliability models, and it provides new theoretical analyses of various models including classical replacement, preventive maintenance and inspection policies. These policies are applied to scheduling problems, backup policies of database systems, maintenance policies of cumulative damage models, and reliability of random redundant systems. Reliability theory is a major concern for engineers and managers, and in light of Japan’s recent earthquake, the reliability of large-scale systems has increased in importance. This also highlights the need for a new notion of maintenance and reliability theory, and how this can practically be applied to systems. Providing an essential guide for engineers and managers specializing in reliability maintenance a...

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

New Learning - The IPP Programme: Improvements in Learning and Self Esteem by Changing the Organization of Learning

Science.gov (United States)

Garber, Klaus; Ausserer, Oskar; Giacomuzzi, Salvatore

"New learning" is basically an individualized learning style. "New learning" starts by the individual itself. The individual is the basis for conditions, learning contents, rhythm, duration and intensity of the teaching. The appropriate slogan is: fetch the individual at his personal conditions.

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

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…

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.

Towards the characterization of short-term memory of zebrafish: effect of fixed versus random reward location.

Science.gov (United States)

Fernandes, Yohaan; Talpos, Andrea; Gerlai, Robert

2015-01-02

The zebrafish has been proposed as an efficient tool for the analysis of behavioral and neurobiological mechanisms of learning and memory. However, compared to traditional laboratory rodents, it is a relatively newcomer. In fact, only limited information on its mnemonic and cognitive abilities has been obtained, and only a small number of learning and memory paradigms have been available for its testing. Previously, we have shown that zebrafish are capable of learning the systematic alternating sequence of reward location in a shuttle box task in which we evaluated behavioral responses manually. Here, we employ a computerized, automated version of this task. We study whether zebrafish can remember the prior location of a reward (the sight of conspecifics) when the location is fixed (constant), or when the sequence of the location of presentation randomly changes between the left and the right side of the experimental tank. We also analyze performance features including the swim speed of experimental fish as well as the temporal changes of the position of fish when the reward (stimulus) is not presented. Our results show that under both the fixed and randomly changing reward location conditions zebrafish exhibit a significant preference for the prior location of reward, albeit the preference is stronger under the fixed location condition. We conclude that adult zebrafish have short-term associative memory that can be induced and quantified in an automated manner. Copyright © 2014 Elsevier Inc. All rights reserved.

Online learning from input versus offline memory evolution in adult word learning: effects of neighborhood density and phonologically related practice.

Science.gov (United States)

Storkel, Holly L; Bontempo, Daniel E; Pak, Natalie S

2014-10-01

In this study, the authors investigated adult word learning to determine how neighborhood density and practice across phonologically related training sets influence online learning from input during training versus offline memory evolution during no-training gaps. Sixty-one adults were randomly assigned to learn low- or high-density nonwords. Within each density condition, participants were trained on one set of words and then were trained on a second set of words, consisting of phonological neighbors of the first set. Learning was measured in a picture-naming test. Data were analyzed using multilevel modeling and spline regression. Steep learning during input was observed, with new words from dense neighborhoods and new words that were neighbors of recently learned words (i.e., second-set words) being learned better than other words. In terms of memory evolution, large and significant forgetting was observed during 1-week gaps in training. Effects of density and practice during memory evolution were opposite of those during input. Specifically, forgetting was greater for high-density and second-set words than for low-density and first-set words. High phonological similarity, regardless of source (i.e., known words or recent training), appears to facilitate online learning from input but seems to impede offline memory evolution.

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

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

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…

d-Cycloserine reduces context specificity of sexual extinction learning.

Science.gov (United States)

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

2015-11-01

d-Cycloserine (DCS) enhances extinction processes in animals. Although classical conditioning is hypothesized to play a pivotal role in the aetiology of appetitive motivation problems, no research has been conducted on the effect of DCS on the reduction of context specificity of extinction in human appetitive learning, while facilitation hereof is relevant in the context of treatment of problematic reward-seeking behaviors. Female participants were presented with two conditioned stimuli (CSs) that either predicted (CS+) or did not predict (CS-) a potential sexual reward (unconditioned stimulus (US); genital vibrostimulation). Conditioning took place in context A and extinction in context B. Subjects received DCS (125mg) or placebo directly after the experiment on day 1 in a randomized, double-blind, between-subject fashion (Placebo n=31; DCS n=31). Subsequent testing for CS-evoked conditioned responses (CRs) in both the conditioning (A) and the extinction context (B) took place 24h later on day 2. Drug effects on consolidation were then assessed by comparing the recall of sexual extinction memories between the DCS and the placebo groups. Post learning administration of DCS facilitates sexual extinction memory consolidation and affects extinction's fundamental context specificity, evidenced by reduced conditioned genital and subjective sexual responses, relative to placebo, for presentations of the reward predicting cue 24h later outside the extinction context. DCS makes appetitive extinction memories context-independent and prevents the return of conditioned response. NMDA receptor glycine site agonists may be potential pharmacotherapies for the prevention of relapse of appetitive motivation disorders with a learned component. Copyright © 2015 Elsevier Inc. All rights reserved.

Evolution of individual versus social learning on social networks.

Science.gov (United States)

Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

2015-03-06

A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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...

Random elements on lattices: Review and statistical applications

Science.gov (United States)

Potocký, Rastislav; Villarroel, Claudia Navarro; Sepúlveda, Maritza; Luna, Guillermo; Stehlík, Milan

2017-07-01

We discuss important contributions to random elements on lattices. We relate to both algebraic and probabilistic properties. Several applications and concepts are discussed, e.g. positive dependence, Random walks and distributions on lattices, Super-lattices, learning. The application to Chilean Ecology is given.

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...

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.

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.

Effect of Demographic Factors on E-Learning Effectiveness in a Higher Learning Institution in Malaysia

Science.gov (United States)

Islam, Md. Aminul; Rahim, Noor Asliza Abdul; Liang, Tan Chee; Momtaz, Hasina

2011-01-01

This research attempted to find out the effect of demographic factors on the effectiveness of the e-learning system in a higher learning Institution. The students from this institution were randomly selected in order to evaluate the effectiveness of learning system in student's learning process. The primary data source is the questionnaires that…

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

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.

Dynamic Evolution with Limited Learning Information on a Small-World Network

International Nuclear Information System (INIS)

Dong Linrong

2010-01-01

This paper investigates the dynamic evolution with limited learning information on a small-world network. In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspect the profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one and compare its payoff to copy its strategy. It is assumed that the information acquainted by the player declines in the form of the exponential with the geographical distance between the players, and a parameter V is introduced to denote the inspect-ability about the players. It is found that under the hospitable conditions, cooperation increases with the randomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal at the moderate rewiring probability and is chaos with the connectivity for the snowdrift game. For the two games, the acuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageous to cooperation and cooperation increases with the randomness under the hostile condition. (interdisciplinary physics and related areas of science and technology)

Microcomputer-Assisted Discoveries: Generate Your Own Random Numbers.

Science.gov (United States)

Kimberling, Clark

1984-01-01

Having students try to generate their own random numbers can lead to much discovery learning as one tries to create 'patternlessness' from formulas. Developing an equidistribution test and runs test, plus other ideas for generating random numbers, is discussed, with computer programs given. (MNS)

Learning Performance Enhancement Using Computer-Assisted Language Learning by Collaborative Learning Groups

Directory of Open Access Journals (Sweden)

Ya-huei Wang

2017-08-01

Full Text Available This study attempted to test whether the use of computer-assisted language learning (CALL and innovative collaborative learning could be more effective than the use of traditional collaborative learning in improving students’ English proficiencies. A true experimental design was used in the study. Four randomly-assigned groups participated in the study: a traditional collaborative learning group (TCLG, 34 students, an innovative collaborative learning group (ICLG, 31 students, a CALL traditional collaborative learning group (CALLTCLG, 32 students, and a CALL innovative collaborative learning group (CALLICLG, 31 students. TOEIC (Test of English for International Communication listening, reading, speaking, and writing pre-test and post-test assessments were given to all students at an interval of sixteen weeks. Multivariate analysis of covariance (MANCOVA, multivariate analysis of variance (MANOVA, and analysis of variance (ANOVA were used to analyze the data. The results revealed that students who used CALL had significantly better learning performance than those who did not. Students in innovative collaborative learning had significantly better learning performances than those in traditional collaborative learning. Additionally, students using CALL innovative collaborative learning had better learning performances than those in CALL collaborative learning, those in innovative collaborative learning, and those in traditional collaborative learning.

The better you feel the better you learn: do warm colours and rounded shapes enhance learning outcome in multimedia learning?

OpenAIRE

Münchow, Hannes; Mengelkamp, Christoph; Bannert, Maria

2018-01-01

The aim of the present study was to examine whether fostering positive activating affect during multimedia learning enhances learning outcome. University students were randomly assigned to either a multimedia learning environment designed to induce positive activating affect through the use of “warm” colours and rounded shapes (n=61) or an affectively neutral environment that used achromatic colours and sharp edges (n=50). Participants learned about the topic of functional neuroanatomy for 20...

Effect of worksheet scaffolds on student learning in problem-based learning

NARCIS (Netherlands)

S.S.Y. Choo (Serene); J.I. Rotgans (Jerome); E.H.J. Yew (Elaine); H.G. Schmidt (Henk)

2011-01-01

textabstractThe purpose of this study was to investigate the effect of worksheets as a scaffolding tool on students' learning achievement in a problem-based learning (PBL) environment. Seventeen PBL classes (N = 241) were randomly assigned to two experimental groups-one with a worksheet provided and

Motivation and intelligence drive auditory perceptual learning.

Science.gov (United States)

Amitay, Sygal; Halliday, Lorna; Taylor, Jenny; Sohoglu, Ediz; Moore, David R

2010-03-23

Although feedback on performance is generally thought to promote perceptual learning, the role and necessity of feedback remain unclear. We investigated the effect of providing varying amounts of positive feedback while listeners attempted to discriminate between three identical tones on learning frequency discrimination. Using this novel procedure, the feedback was meaningless and random in relation to the listeners' responses, but the amount of feedback provided (or lack thereof) affected learning. We found that a group of listeners who received positive feedback on 10% of the trials improved their performance on the task (learned), while other groups provided either with excess (90%) or with no feedback did not learn. Superimposed on these group data, however, individual listeners showed other systematic changes of performance. In particular, those with lower non-verbal IQ who trained in the no feedback condition performed more poorly after training. This pattern of results cannot be accounted for by learning models that ascribe an external teacher role to feedback. We suggest, instead, that feedback is used to monitor performance on the task in relation to its perceived difficulty, and that listeners who learn without the benefit of feedback are adept at self-monitoring of performance, a trait that also supports better performance on non-verbal IQ tests. These results show that 'perceptual' learning is strongly influenced by top-down processes of motivation and intelligence.

Does Fine Color Discrimination Learning in Free-Flying Honeybees Change Mushroom-Body Calyx Neuroarchitecture?

Directory of Open Access Journals (Sweden)

Frank M J Sommerlandt

Full Text Available Honeybees learn color information of rewarding flowers and recall these memories in future decisions. For fine color discrimination, bees require differential conditioning with a concurrent presentation of target and distractor stimuli to form a long-term memory. Here we investigated whether the long-term storage of color information shapes the neural network of microglomeruli in the mushroom body calyces and if this depends on the type of conditioning. Free-flying honeybees were individually trained to a pair of perceptually similar colors in either absolute conditioning towards one of the colors or in differential conditioning with both colors. Subsequently, bees of either conditioning groups were tested in non-rewarded discrimination tests with the two colors. Only bees trained with differential conditioning preferred the previously learned color, whereas bees of the absolute conditioning group, and a stimuli-naïve group, chose randomly among color stimuli. All bees were then kept individually for three days in the dark to allow for complete long-term memory formation. Whole-mount immunostaining was subsequently used to quantify variation of microglomeruli number and density in the mushroom-body lip and collar. We found no significant differences among groups in neuropil volumes and total microglomeruli numbers, but learning performance was negatively correlated with microglomeruli density in the absolute conditioning group. Based on these findings we aim to promote future research approaches combining behaviorally relevant color learning tests in honeybees under free-flight conditions with neuroimaging analysis; we also discuss possible limitations of this approach.

Brain Tumor Segmentation Based on Random Forest

Directory of Open Access Journals (Sweden)

László Lefkovits

2016-09-01

Full Text Available In this article we present a discriminative model for tumor detection from multimodal MR images. The main part of the model is built around the random forest (RF classifier. We created an optimization algorithm able to select the important features for reducing the dimensionality of data. This method is also used to find out the training parameters used in the learning phase. The algorithm is based on random feature properties for evaluating the importance of the variable, the evolution of learning errors and the proximities between instances. The detection performances obtained have been compared with the most recent systems, offering similar results.

Learning and Memory

OpenAIRE

1999-01-01

Under various circumstances and in different species the outward expression of learning varies considerably, and this has led to the classification of different categories of learning. Just as there is no generally agreed on definition of learning, there is no one system of classification. Types of learning commonly recognized are: Habituation, sensitization, classical conditioning, operant conditioning, trial and error, taste aversion, latent learning, cultural learning, imprinting, insight ...

Effect of Peer-Led Team Learning (PLTL) on Student Achievement, Attitude, and Self-Concept in College General Chemistry in Randomized and Quasi Experimental Designs

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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…

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

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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.

Quantumness, Randomness and Computability

International Nuclear Information System (INIS)

Solis, Aldo; Hirsch, Jorge G

2015-01-01

Randomness plays a central role in the quantum mechanical description of our interactions. We review the relationship between the violation of Bell inequalities, non signaling and randomness. We discuss the challenge in defining a random string, and show that algorithmic information theory provides a necessary condition for randomness using Borel normality. We close with a view on incomputablity and its implications in physics. (paper)

Pupil dilation indicates the coding of past prediction errors: Evidence for attentional learning theory.

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Koenig, Stephan; Uengoer, Metin; Lachnit, Harald

2018-04-01

The attentional learning theory of Pearce and Hall () predicts more attention to uncertain cues that have caused a high prediction error in the past. We examined how the cue-elicited pupil dilation during associative learning was linked to such error-driven attentional processes. In three experiments, participants were trained to acquire associations between different cues and their appetitive (Experiment 1), motor (Experiment 2), or aversive (Experiment 3) outcomes. All experiments were designed to examine differences in the processing of continuously reinforced cues (consistently followed by the outcome) versus partially reinforced, uncertain cues (randomly followed by the outcome). We measured the pupil dilation elicited by the cues in anticipation of the outcome and analyzed how this conditioned pupil response changed over the course of learning. In all experiments, changes in pupil size complied with the same basic pattern: During early learning, consistently reinforced cues elicited greater pupil dilation than uncertain, randomly reinforced cues, but this effect gradually reversed to yield a greater pupil dilation for uncertain cues toward the end of learning. The pattern of data accords with the changes in prediction error and error-driven attention formalized by the Pearce-Hall theory. © 2017 The Authors. Psychophysiology published by Wiley Periodicals, Inc. on behalf of Society for Psychophysiological Research.

Evaluative Conditioning with Facial Stimuli in Dementia Patients.

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Blessing, Andreas; Zöllig, Jacqueline; Weierstall, Roland; Dammann, Gerhard; Martin, Mike

2013-01-01

We present results of a study investigating evaluative learning in dementia patients with a classic evaluative conditioning paradigm. Picture pairs of three unfamiliar faces with liked, disliked, or neutral faces, that were rated prior to the presentation, were presented 10 times each to a group of dementia patients (N = 15) and healthy controls (N = 14) in random order. Valence ratings of all faces were assessed before and after presentation. In contrast to controls, dementia patients changed their valence ratings of unfamiliar faces according to their pairing with either a liked or disliked face, although they were not able to explicitly assign the picture pairs after the presentation. Our finding suggests preserved evaluative conditioning in dementia patients. However, the result has to be considered preliminary, as it is unclear which factors prevented the predicted rating changes in the expected direction in the control group.

Feedback Valence Affects Auditory Perceptual Learning Independently of Feedback Probability

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Amitay, Sygal; Moore, David R.; Molloy, Katharine; Halliday, Lorna F.

2015-01-01

Previous studies have suggested that negative feedback is more effective in driving learning than positive feedback. We investigated the effect on learning of providing varying amounts of negative and positive feedback while listeners attempted to discriminate between three identical tones; an impossible task that nevertheless produces robust learning. Four feedback conditions were compared during training: 90% positive feedback or 10% negative feedback informed the participants that they were doing equally well, while 10% positive or 90% negative feedback informed them they were doing equally badly. In all conditions the feedback was random in relation to the listeners’ responses (because the task was to discriminate three identical tones), yet both the valence (negative vs. positive) and the probability of feedback (10% vs. 90%) affected learning. Feedback that informed listeners they were doing badly resulted in better post-training performance than feedback that informed them they were doing well, independent of valence. In addition, positive feedback during training resulted in better post-training performance than negative feedback, but only positive feedback indicating listeners were doing badly on the task resulted in learning. As we have previously speculated, feedback that better reflected the difficulty of the task was more effective in driving learning than feedback that suggested performance was better than it should have been given perceived task difficulty. But contrary to expectations, positive feedback was more effective than negative feedback in driving learning. Feedback thus had two separable effects on learning: feedback valence affected motivation on a subjectively difficult task, and learning occurred only when feedback probability reflected the subjective difficulty. To optimize learning, training programs need to take into consideration both feedback valence and probability. PMID:25946173

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...

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

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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.

Contextual Change After Fear Acquisition Affects Conditioned Responding and the Time Course of Extinction Learning-Implications for Renewal Research.

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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.

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

[Effect of 5-HT1A receptors in the hippocampal DG on active avoidance learning in rats].