Promoting learning transfer in preceptor preparation.

Science.gov (United States)

Finn, Frances L; Chesser-Smyth, Patricia

2013-01-01

An understanding of learning transfer principles is essential for professional development educators and managers to ensure that new skills and knowledge learned are applied to practice. This article presents a collaborative project involving the planning, design, and implementation of a preceptor training program for registered nurses. The theories and principles discussed in this article could be applied to a number of different settings and contexts in health care to promote learning transfer in professional development activities.

Telecommuting and Learning Style Preference: An Examination of Learning Transfer in the Workplace

Science.gov (United States)

Schulz, Lisa C.

2010-01-01

Telecommuting learning style preferences were examined in an effort to determine the impact of learning transfer and if employees could benefit from blended training methodologies (i.e., online, face-to-face). Learning style preferences were examined in an effort to promote learning transfer and retention in the workplace. Employees in higher…

Accelerating Multiagent Reinforcement Learning by Equilibrium Transfer.

Science.gov (United States)

Hu, Yujing; Gao, Yang; An, Bo

2015-07-01

An important approach in multiagent reinforcement learning (MARL) is equilibrium-based MARL, which adopts equilibrium solution concepts in game theory and requires agents to play equilibrium strategies at each state. However, most existing equilibrium-based MARL algorithms cannot scale due to a large number of computationally expensive equilibrium computations (e.g., computing Nash equilibria is PPAD-hard) during learning. For the first time, this paper finds that during the learning process of equilibrium-based MARL, the one-shot games corresponding to each state's successive visits often have the same or similar equilibria (for some states more than 90% of games corresponding to successive visits have similar equilibria). Inspired by this observation, this paper proposes to use equilibrium transfer to accelerate equilibrium-based MARL. The key idea of equilibrium transfer is to reuse previously computed equilibria when each agent has a small incentive to deviate. By introducing transfer loss and transfer condition, a novel framework called equilibrium transfer-based MARL is proposed. We prove that although equilibrium transfer brings transfer loss, equilibrium-based MARL algorithms can still converge to an equilibrium policy under certain assumptions. Experimental results in widely used benchmarks (e.g., grid world game, soccer game, and wall game) show that the proposed framework: 1) not only significantly accelerates equilibrium-based MARL (up to 96.7% reduction in learning time), but also achieves higher average rewards than algorithms without equilibrium transfer and 2) scales significantly better than algorithms without equilibrium transfer when the state/action space grows and the number of agents increases.

Learning Transfer: The Missing Link to Learning among School Leaders in Burkina Faso and Ghana

Directory of Open Access Journals (Sweden)

Corinne Brion

2018-01-01

Full Text Available Every year, billions of dollars are spent on development aid and training around the world. However, only 10% of this training results in the transfer of knowledge, skills, or behaviors learned in the training to the work place. Ideally, learning transfer produces effective and continued application by learners of the knowledge and skills they gained through their learning activities. Currently, there is a limited body of research examining the factors that hinder and promote learning transfer in professional development, particularly the professional development of school leaders in developing countries. This qualitative exploratory study sought to address the gap in the literature by examining six schools: three in Burkina Faso and three in Ghana, West Africa. This investigation explored what promoted and hindered learning transfer in both countries. The sample consisted of 13 West-African school leaders (6 in Burkina Faso and 7 in Ghana who attended a 3-day leadership training workshop. Data collection included in-depth interviews, document analysis, post-training site visits, and text messages to ascertain whether this mobile technology intervention enhanced learning transfer. The findings demonstrated that learning transfer occurred in both countries in all six schools. Data indicated that most of the transfer of learning happened in areas not requiring mindset and behavioral changes. Data suggested that the facilities in which the trainings took place, the facilitators’ dispositions and knowledge, the adequacy of the materials as well as the testimonials and certificate of completions enhanced the transfer of learning. Participants also indicated some inhibitors to the transfer of learning, such as financial, cultural, and human behavior constraints. This study helps increase our understanding of what promotes and inhibits learning transfer in educational settings in Burkina Faso and Ghana and provides suggestions for trainers and

[Memory transfer in cerebellar motor learning].

Science.gov (United States)

Nagao, Soichi

2012-01-01

Most of our motor skills are acquired through learning. Experiments of gain adaptation of ocular reflexes have consistently suggested that the memory of adaptation is initially formed in the cerebellar cortex, and is transferred to the cerebellar (vestibular) nuclei for consolidation to long-term memory after repetitions of training. We have recently developed a new system to evaluate the motor learning in human subjects using prism adaptation of hand reaching movement, by referring to the prism adaptation of dart throwing of Martin et al. (1996). In our system, the subject views the small target presented in the touch-panel screen, and touches it with his/her finger without direct visual feedback. After 15-30 trials of touching wearing prisms, an adaptation occurs in healthy subjects: they became able to touch the target correctly. Meanwhile, such an adaptation was impaired in patients of cerebellar disease. We have proposed a model of human prism adaptation that the memory of adaptation is initially encoded in the cerebellar cortex, and is later transferred to the cerebellar nuclei after repetitions of training. The memory in the cerebellar cortex may be formed and extinguished independently of the memory maintained in the cerebellar nuclei, and these two memories work cooperatively.

Leveraging anatomical information to improve transfer learning in brain-computer interfaces

Science.gov (United States)

Wronkiewicz, Mark; Larson, Eric; Lee, Adrian K. C.

2015-08-01

Objective. Brain-computer interfaces (BCIs) represent a technology with the potential to rehabilitate a range of traumatic and degenerative nervous system conditions but require a time-consuming training process to calibrate. An area of BCI research known as transfer learning is aimed at accelerating training by recycling previously recorded training data across sessions or subjects. Training data, however, is typically transferred from one electrode configuration to another without taking individual head anatomy or electrode positioning into account, which may underutilize the recycled data. Approach. We explore transfer learning with the use of source imaging, which estimates neural activity in the cortex. Transferring estimates of cortical activity, in contrast to scalp recordings, provides a way to compensate for variability in electrode positioning and head morphologies across subjects and sessions. Main results. Based on simulated and measured electroencephalography activity, we trained a classifier using data transferred exclusively from other subjects and achieved accuracies that were comparable to or surpassed a benchmark classifier (representative of a real-world BCI). Our results indicate that classification improvements depend on the number of trials transferred and the cortical region of interest. Significance. These findings suggest that cortical source-based transfer learning is a principled method to transfer data that improves BCI classification performance and provides a path to reduce BCI calibration time.

Model Transport: Towards Scalable Transfer Learning on Manifolds

DEFF Research Database (Denmark)

Freifeld, Oren; Hauberg, Søren; Black, Michael J.

2014-01-01

We consider the intersection of two research fields: transfer learning and statistics on manifolds. In particular, we consider, for manifold-valued data, transfer learning of tangent-space models such as Gaussians distributions, PCA, regression, or classifiers. Though one would hope to simply use...... ordinary Rn-transfer learning ideas, the manifold structure prevents it. We overcome this by basing our method on inner-product-preserving parallel transport, a well-known tool widely used in other problems of statistics on manifolds in computer vision. At first, this straightforward idea seems to suffer...... “commutes” with learning. Consequently, our compact framework, applicable to a large class of manifolds, is not restricted by the size of either the training or test sets. We demonstrate the approach by transferring PCA and logistic-regression models of real-world data involving 3D shapes and image...

Auditory temporal perceptual learning and transfer in Chinese-speaking children with developmental dyslexia.

Science.gov (United States)

Zhang, Manli; Xie, Weiyi; Xu, Yanzhi; Meng, Xiangzhi

2018-03-01

Perceptual learning refers to the improvement of perceptual performance as a function of training. Recent studies found that auditory perceptual learning may improve phonological skills in individuals with developmental dyslexia in alphabetic writing system. However, whether auditory perceptual learning could also benefit the reading skills of those learning the Chinese logographic writing system is, as yet, unknown. The current study aimed to investigate the remediation effect of auditory temporal perceptual learning on Mandarin-speaking school children with developmental dyslexia. Thirty children with dyslexia were screened from a large pool of students in 3th-5th grades. They completed a series of pretests and then were assigned to either a non-training control group or a training group. The training group worked on a pure tone duration discrimination task for 7 sessions over 2 weeks with thirty minutes per session. Post-tests immediately after training and a follow-up test 2 months later were conducted. Analyses revealed a significant training effect in the training group relative to non-training group, as well as near transfer to the temporal interval discrimination task and far transfer to phonological awareness, character recognition and reading fluency. Importantly, the training effect and all the transfer effects were stable at the 2-month follow-up session. Further analyses found that a significant correlation between character recognition performance and learning rate mainly existed in the slow learning phase, the consolidation stage of perceptual learning, and this effect was modulated by an individuals' executive function. These findings indicate that adaptive auditory temporal perceptual learning can lead to learning and transfer effects on reading performance, and shed further light on the potential role of basic perceptual learning in the remediation and prevention of developmental dyslexia. Copyright © 2018 Elsevier Ltd. All rights reserved.

Transferring an Outcome-Oriented Learning Architecture to an IT Learning Game

NARCIS (Netherlands)

Schmitz, Birgit; Klemke, Roland; Totschnig, Michael; Czauderna, André; Specht, Marcus

2011-01-01

Schmitz, B., Klemke, R., Totschnig, M., Czauderna, A., & Specht, M. (2011, 23 September). Transferring an outcome-oriented learning architecture to an IT learning game. Presented at the 6th European conference on Technology enhanced learning: towards ubiquitous learning (EC-TEL 2011), Palermo,

Transfer Climate and EAP Education: Students Perceptions of Challenges to Learning Transfer

Science.gov (United States)

James, Mark Andrew

2010-01-01

This study examined the applicability of the construct transfer climate in EAP education. In an EAP setting, transfer climate can be viewed as the support for learning transfer from an EAP course that students perceive in mainstream academic courses. The research question was as follows: What can a transfer climate perspective reveal about…

Organizational Learning Culture, Transfer Climate and Perceived Innovation in Jordan

Science.gov (United States)

Bates, Reid; Khasawneh, Samer

2004-01-01

This paper examined the relationship between organizational learning culture, learning transfer climate, and organizational innovation. The objective was to test the ability of learning organization culture to account for variance in learning transfer climate and subsequent organizational innovation, and to examine the role of learning transfer…

Applying a Danish version of the Learning Transfer System Inventory and testing it for different types of education

DEFF Research Database (Denmark)

Sørensen, Peter; Stegeager, Nikolaj W.M.; Bates, Reid

2017-01-01

in the original American LTSI. The study also found that the mean score differs in a statistically significant way between the different types of education. Specifically, LTSI may be more suitable in measuring transfer systems and therefore promoting transfer in relation to short courses offering training......The purpose of this study was to answer two research questions. First, will an exploratory factor analysis of a Danish version of the Learning Transfer System Inventory (LTSI) result in a factor structure which is consistent with the original American LTSI factor structure? Second, does the mean...... score in the factor analysis vary in a statistically significant way across different types of education, suggesting that the LTSI may be more suitable a measure in some educational contexts than others? To answer these questions survey data from 411 students following four different types of formal...

Aligning Needs, Expectations, and Learning Outcomes to Sustain Self-Efficacy through Transfer Learning Community Programs

Science.gov (United States)

Leptien, Jennifer R.

2015-01-01

This chapter addresses strengths and difficulties encountered in implementing transfer learning community models and how efficacy is supported through transfer learning community programming. Transfer programming best practices and recommendations for program improvements are presented.

Negative Transfer of L1 on English Grammar Learning in SLA

Institute of Scientific and Technical Information of China (English)

马秀琳

2015-01-01

At present,many scholars pay more attention to the positive transfer of native language on the English learning,while ignoring the negative transfer of L1 on English grammar learning.Therefore native transfer of L1 often appears on English grammar learning.This paper aims to point out that the negative transfer of L1 has a profound and vast influence on the English grammar learning,to find out the countermeasures to reduce the influence of negative transfer of L1 and finally to bring the benefits to the following relative studies.

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface.

Science.gov (United States)

Waytowich, Nicholas R; Lawhern, Vernon J; Bohannon, Addison W; Ball, Kenneth R; Lance, Brent J

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry, STIG), which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIG method is validated in both off-line and real-time feedback analysis during a rapid serial visual presentation task (RSVP). For detection of single-trial, event-related potentials (ERPs), the proposed method can significantly outperform existing calibration-free techniques as well as outperform traditional within-subject calibration techniques when limited data is available. This method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system.

Transfer learning improves supervised image segmentation across imaging protocols.

Science.gov (United States)

van Opbroek, Annegreet; Ikram, M Arfan; Vernooij, Meike W; de Bruijne, Marleen

2015-05-01

The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

Individual learning effects on knowledge transfer in international joint ventures

DEFF Research Database (Denmark)

Dao, Li Thuy; Napier, Nancy

2016-01-01

This paper examines micro (individual-level) aspects of knowledge transfer and learning in international joint ventures in an emerging economy context. Learning by expatriate and local managers appears far more complex, mutually dependent, and significant to the knowledge transfer process than...... suggested in existing literature. Building upon conceptualizations of individual learning and cognitive – behavioural effects in an organisational context while drawing evidence from two cases of Danish – Vietnamese joint ventures, we propose a model of individual-level knowledge transfer and learning...

Time course influences transfer of visual perceptual learning across spatial location.

Science.gov (United States)

Larcombe, S J; Kennard, C; Bridge, H

2017-06-01

Visual perceptual learning describes the improvement of visual perception with repeated practice. Previous research has established that the learning effects of perceptual training may be transferable to untrained stimulus attributes such as spatial location under certain circumstances. However, the mechanisms involved in transfer have not yet been fully elucidated. Here, we investigated the effect of altering training time course on the transferability of learning effects. Participants were trained on a motion direction discrimination task or a sinusoidal grating orientation discrimination task in a single visual hemifield. The 4000 training trials were either condensed into one day, or spread evenly across five training days. When participants were trained over a five-day period, there was transfer of learning to both the untrained visual hemifield and the untrained task. In contrast, when the same amount of training was condensed into a single day, participants did not show any transfer of learning. Thus, learning time course may influence the transferability of perceptual learning effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets

Science.gov (United States)

Voß, Lydia; Schatten, Carlotta; Mazziotti, Claudia; Schmidt-Thieme, Lars

2015-01-01

Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition

Science.gov (United States)

Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang

2018-03-01

Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.

Supporting Transfer of Learning: Practice-based considerations on the applicability of transfer literature in online design

DEFF Research Database (Denmark)

Noesgaard, Signe Schack

2014-01-01

for school teachers. The PhD-project is inspired by design-based research and the research into learning transfer. It aims to evaluate if, how, and why an online facilitated, collaborative learning solution can improve the teaching practices of science teachers in Danish elementary schools. Based...... on the ethnographic study, this paper attempts to answer the following questions: what characterizes the work environment at the schools, specifically in regards to collegial support, organizational support, and manager support? How does the empirical research relate to the learning transfer literature? Do...... these characteristics give rise to reconsiderations of applying learning transfer research when designing for competence development?...

Classroom Strategies That Facilitate Transfer of Learning to the Workplace.

Science.gov (United States)

Gardner, Brenda S.; Korth, Sharon J.

1997-01-01

Describes a master's program in human resource development that uses experiential learning, transfer of learning, and team learning theories to maximize students' transfer of their formal training to the workplace. Activities include individual and group analysis papers and a team project. Students have found the group and experiential practice…

Computer-based learning in neuroanatomy: A longitudinal study of learning, transfer, and retention

Science.gov (United States)

Chariker, Julia H.

A longitudinal experiment was conducted to explore computer-based learning of neuroanatomy. Using a realistic 3D graphical model of neuroanatomy, and sections derived from the model, exploratory graphical tools were integrated into interactive computer programs so as to allow adaptive exploration. 72 participants learned either sectional anatomy alone or learned whole anatomy followed by sectional anatomy. Sectional anatomy was explored either in perceptually continuous animation or discretely, as in the use of an anatomical atlas. Learning was measured longitudinally to a high performance criterion. After learning, transfer to biomedical images and long-term retention was tested. Learning whole anatomy prior to learning sectional anatomy led to a more efficient learning experience. Learners demonstrated high levels of transfer from whole anatomy to sectional anatomy and from sectional anatomy to complex biomedical images. All learning groups demonstrated high levels of retention at 2--3 weeks.

Spectral Transfer Learning using Information Geometry for a User-Independent Brain-Computer Interface

Directory of Open Access Journals (Sweden)

Nicholas Roy Waytowich

2016-09-01

Full Text Available Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI technologies to fields such as medicine, industry and recreation. However, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter- individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this paper, we present an unsupervised transfer method (spectral transfer using information geometry, STIG, which ranks and combines unlabeled predictions from an ensemble of information geometry classifiers built on data from individual training subjects. The STIG method is validated in both offline and real-time feedback analysis during a rapid serial visual presentation task (RSVP. For detection of single-trial, event-related potentials (ERPs, the proposed method can significantly outperform existing calibration-free techniques as well as outperform traditional within-subject calibration techniques when limited data is available. This method demonstrates that unsupervised transfer learning for single-trial detection in ERP-based BCIs can be achieved without the requirement of costly training data, representing a step-forward in the overall goal of achieving a practical user-independent BCI system.

Action Learning: How Learning Transfers from Entrepreneurs to Small Firms

Science.gov (United States)

Jones, Karen; Sambrook, Sally A.; Pittaway, Luke; Henley, Andrew; Norbury, Heather

2014-01-01

This paper presents research with small- and medium-sized enterprise (SME) owners who have participated in a leadership development programme. The primary focus of this paper is on learning transfer and factors affecting it, arguing that entrepreneurs must engage in "action" in order to "learn" and that under certain conditions…

An Evaluation of Effective Factors in Learning Transfer of Nursing On-the-Job Training Courses in Work-Environment Based on Holton’s Transfer Model

Directory of Open Access Journals (Sweden)

mehdi mohammadi

2017-06-01

Full Text Available Background of Objective: Nursing is one of the health care jobs. In addition to health care, they need to continue education for individual development and be aware of the latest medical science achievements. The main purpose of this study was an evaluation of effective factors in learning transfer of nursing on the job training courses in work environment based on Holton’s transfer model. Materials and Methods: This was a descriptive, cross-sectional study in which the population was all of Jahrom University of Medical Sciences nurses. Passing on-the-job training courses in 2015 was inclusion criterion. Using random sampling method and Cocran formula, 95 nurses were selected. Research instrument was learning transfer system inventory that was distributed after its validity and reliability were calculated. Data was analyzed by inferential statistical methods and SPSS21. Results: The results showed that effective individual, organizational and educational factors in learning transfer of on-the-job training courses in work environment are important. Also, they showed that individual was the most dominant effective factor (P< 0.05. Conclusion: With special attention to the nurse's on- the -job training courses, it is possible to transfer learning to work environment.

Mobile Learning Via SMS Among Distance Learners: Does Learning Transfer Occur?

Directory of Open Access Journals (Sweden)

Aznarahayu Ramli

2010-07-01

Full Text Available The purpose of this study is to determine whether learners are willing to transfer learning in this mobile learning environment via SMS. The reason for this is to measure the effectiveness of the new method used in learning and education especially in distance education field. For this reason, students’ responses are gathered which looked at three factors namely learner characteristic, learning design and learning environment. The data are gathered through a survey research design with questionnaires using five-point likert scale. The questionnaires was administered for 105 distance education students from four courses including Bachelor of Science, Bachelor of Arts, Bachelor of Social Science and Bachelor of Management. The Rasch Model Analysis was used to measure these dimensions. Rasch Model is a one-parameter logistic model within item response theory (IRT whereby the amount of a given latent trait in a person and the amount of that same latent trait reflected in various items can be estimated independently yet still compared explicitly to one another. The result of the study showed that learning transfer occurred and being influenced most by learner’s characteristics especially in term of their motivation as well as their perceive utility/value of the SMS learning to their job and academic performances.

Transfer of tactile perceptual learning to untrained neighboring fingers reflects natural use relationships.

Science.gov (United States)

Dempsey-Jones, Harriet; Harrar, Vanessa; Oliver, Jonathan; Johansen-Berg, Heidi; Spence, Charles; Makin, Tamar R

2016-03-01

Tactile learning transfers from trained to untrained fingers in a pattern that reflects overlap between the representations of fingers in the somatosensory system (e.g., neurons with multifinger receptive fields). While physical proximity on the body is known to determine the topography of somatosensory representations, tactile coactivation is also an established organizing principle of somatosensory topography. In this study we investigated whether tactile coactivation, induced by habitual inter-finger cooperative use (use pattern), shapes inter-finger overlap. To this end, we used psychophysics to compare the transfer of tactile learning from the middle finger to its adjacent fingers. This allowed us to compare transfer to two fingers that are both physically and cortically adjacent to the middle finger but have differing use patterns. Specifically, the middle finger is used more frequently with the ring than with the index finger. We predicted this should lead to greater representational overlap between the former than the latter pair. Furthermore, this difference in overlap should be reflected in differential learning transfer from the middle to index vs. ring fingers. Subsequently, we predicted temporary learning-related changes in the middle finger's representation (e.g., cortical magnification) would cause transient interference in perceptual thresholds of the ring, but not the index, finger. Supporting this, longitudinal analysis revealed a divergence where learning transfer was fast to the index finger but relatively delayed to the ring finger. Our results support the theory that tactile coactivation patterns between digits affect their topographic relationships. Our findings emphasize how action shapes perception and somatosensory organization. Copyright © 2016 the American Physiological Society.

Transfer of learning between 2D and 3D sources during infancy: Informing theory and practice.

Science.gov (United States)

Barr, Rachel

2010-06-01

The ability to transfer learning across contexts is an adaptive skill that develops rapidly during early childhood. Learning from television is a specific instance of transfer of learning between a 2-Dimensional (2D) representation and a 3-Dimensional (3D) object. Understanding the conditions under which young children might accomplish this particular kind of transfer is important because by 2 years of age 90% of US children are viewing television on a daily basis. Recent research shows that children can imitate actions presented on television using the corresponding real-world objects, but this same research also shows that children learn less from television than they do from live demonstrations until they are at least 3 years old; termed the video deficit effect. At present, there is no coherent theory to account for the video deficit effect; how learning is disrupted by this change in context is poorly understood. The aims of the present review are (1) to review the conditions under which children transfer learning between 2D images and 3D objects during early childhood, and (2) to integrate developmental theories of memory processing into the transfer of learning from media literature using Hayne's (2004) developmental representational flexibility account. The review will conclude that studies on the transfer of learning between 2D and 3D sources have important theoretical implications for general developmental theories of cognitive development, and in particular the development of a flexible representational system, as well as policy implications for early education regarding the potential use and limitations of media as effective teaching tools during early childhood.

Transfer learning improves supervised image segmentation across imaging protocols

DEFF Research Database (Denmark)

van Opbroek, Annegreet; Ikram, M. Arfan; Vernooij, Meike W.

2015-01-01

with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two MRI brain-segmentation tasks with multi-site data: white matter, gray matter, and CSF segmentation; and white-matter- /MS-lesion segmentation......The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform...... well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore...

Learning Transferable Features with Deep Adaptation Networks

OpenAIRE

Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

2015-01-01

Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

Back-dropout Transfer Learning for Action Recognition

DEFF Research Database (Denmark)

Ren, Huamin; Kanhabua, Nattiya; Møgelmose, Andreas

2018-01-01

transfer learning being a promising approach, it is still an open question how to adapt the model learned from the source dataset to the target dataset. One big challenge is to prevent the impact of category bias on classification performance. Dataset bias exists when two images from the same category...

Discriminative Transfer Learning for General Image Restoration

KAUST Repository

Xiao, Lei; Heide, Felix; Heidrich, Wolfgang; Schö lkopf, Bernhard; Hirsch, Michael

2018-01-01

Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

Discriminative Transfer Learning for General Image Restoration

KAUST Repository

Xiao, Lei

2018-04-30

Recently, several discriminative learning approaches have been proposed for effective image restoration, achieving convincing trade-off between image quality and computational efficiency. However, these methods require separate training for each restoration task (e.g., denoising, deblurring, demosaicing) and problem condition (e.g., noise level of input images). This makes it time-consuming and difficult to encompass all tasks and conditions during training. In this paper, we propose a discriminative transfer learning method that incorporates formal proximal optimization and discriminative learning for general image restoration. The method requires a single-pass discriminative training and allows for reuse across various problems and conditions while achieving an efficiency comparable to previous discriminative approaches. Furthermore, after being trained, our model can be easily transferred to new likelihood terms to solve untrained tasks, or be combined with existing priors to further improve image restoration quality.

The Learning Transfer Approach To Estimating the Benefits of Training: Empirical Evidence.

Science.gov (United States)

Donovan, Paul; Hannigan, Kevin; Crowe, Deirdre

2001-01-01

The Learning Transfer Systems Inventory provides a systematic approach for predicting training effectiveness through needs assessment, organizational analysis to determine issues affecting training outcomes, and assessment of needed resources. Data from 158 management trainers demonstrated its effectiveness in assessing how well an organization…

Toward A Dual-Learning Systems Model of Speech Category Learning

Directory of Open Access Journals (Sweden)

Bharath eChandrasekaran

2014-07-01

Full Text Available More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article we describe a neurobiologically-constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. We find an age related deficit in reflective-optimal but not reflexive-optimal auditory category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, uni-dimensional rules to more complex, reflexive, multi-dimensional rules. In a second application we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

Process Systems Engineering Education: Learning by Research

Science.gov (United States)

Abbas, A.; Alhammadi, H. Y.; Romagnoli, J. A.

2009-01-01

In this paper, we discuss our approach in teaching the final-year course Process Systems Engineering. Students are given ownership of the course by transferring to them the responsibility of learning. A project-based group environment stimulates learning while solving a real engineering problem. We discuss postgraduate student involvement and how…

Transfer of test-enhanced learning: Meta-analytic review and synthesis.

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Pan, Steven C; Rickard, Timothy C

2018-05-07

Attempting recall of information from memory, as occurs when taking a practice test, is one of the most potent training techniques known to learning science. However, does testing yield learning that transfers to different contexts? In the present article, we report the findings of the first comprehensive meta-analytic review into that question. Our review encompassed 192 transfer effect sizes extracted from 122 experiments and 67 published and unpublished articles (N = 10,382) that together comprise more than 40 years of research. A random-effects model revealed that testing can yield transferrable learning as measured relative to a nontesting reexposure control condition (d = 0.40, 95% CI [0.31, 0.50]). That transfer of learning is greatest across test formats, to application and inference questions, to problems involving medical diagnoses, and to mediator and related word cues; it is weakest to rearranged stimulus-response items, to untested materials seen during initial study, and to problems involving worked examples. Moderator analyses further indicated that response congruency and elaborated retrieval practice, as well as initial test performance, strongly influence the likelihood of positive transfer. In two assessments for publication bias using PET-PEESE and various selection methods, the moderator effect sizes were minimally affected. However, the intercept predictions were substantially reduced, often indicating no positive transfer when none of the aforementioned moderators are present. Overall, our results motivate a three-factor framework for transfer of test-enhanced learning and have practical implications for the effective use of practice testing in educational and other training contexts. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Weighted Domain Transfer Extreme Learning Machine and Its Online Version for Gas Sensor Drift Compensation in E-Nose Systems

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Zhiyuan Ma

2018-01-01

Full Text Available Machine learning approaches have been widely used to tackle the problem of sensor array drift in E-Nose systems. However, labeled data are rare in practice, which makes supervised learning methods hard to be applied. Meanwhile, current solutions require updating the analytical model in an offline manner, which hampers their uses for online scenarios. In this paper, we extended Target Domain Adaptation Extreme Learning Machine (DAELM_T to achieve high accuracy with less labeled samples by proposing a Weighted Domain Transfer Extreme Learning Machine, which uses clustering information as prior knowledge to help select proper labeled samples and calculate sensitive matrix for weighted learning. Furthermore, we converted DAELM_T and the proposed method into their online learning versions under which scenario the labeled data are selected beforehand. Experimental results show that, for batch learning version, the proposed method uses around 20% less labeled samples while achieving approximately equivalent or better accuracy. As for the online versions, the methods maintain almost the same accuracies as their offline counterparts do, but the time cost remains around a constant value while that of offline versions grows with the number of samples.

The relationship between learning styles and motivation to transfer of learning in a vocational training programme

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Pablo Olivos

2016-01-01

Full Text Available Although there is ample research about Kolb's learning styles, few studies have examined their relationship with motivations to transfer, a concept used to assess whether the content and competencies learned through professional training activities are transferred to the workplace context. Ninety-six students (M = 24.58 years old; 99% males from three vocational training institutes participated in laboratory activities at the Renewable Energy Research Institute of the University of Castilla-La Mancha, Spain. They completed a self-administered questionnaire that included the Kolb's Learning Styles Inventory; two scales adapted to measure student motivation to transfer their learning from training experiences; and a scale of satisfaction with the activities. A correlation analysis showed positive and moderately strong correlations (r = .708; p < .01 between motivations to transfer and “the relevance of the activities to academic performance”. A discriminant analysis between transfer and learning styles revealed that the “Student training motivation” item resulted in a distinct difference between assimilators and convergers, explaining 97.1% of the model variance (Wilks’ λ = .459; χ2 = 21.028; Sig. = .002 and classifying 56.4% of the cases. A discussion is presented as to the implications of these results for the theory of learning styles and the ways in which the design of the educational activities described in the study can be improved.

Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

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YiNan Zhang

2017-01-01

Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

Spatial parameters at the basis of social transfer of learning.

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Lugli, Luisa; Iani, Cristina; Milanese, Nadia; Sebanz, Natalie; Rubichi, Sandro

2015-06-01

Recent research indicates that practicing on a joint spatial compatibility task with an incompatible stimulus-response mapping affects subsequent joint Simon task performance, eliminating the social Simon effect. It has been well established that in individual contexts, for transfer of learning to occur, participants need to practice an incompatible association between stimulus and response positions. The mechanisms underlying transfer of learning in joint task performance are, however, less well understood. The present study was aimed at assessing the relative contribution of 3 different spatial relations characterizing the joint practice context: stimulus-response, stimulus-participant, and participant-response relations. In 3 experiments, the authors manipulated the stimulus-response, stimulus-participant, and response-participant associations. We found that learning from the practice task did not transfer to the subsequent task when during practice stimulus-response associations were spatially incompatible and stimulus-participant associations were compatible (Experiment 1). However, a transfer of learning was evident when stimulus-participant associations were spatially incompatible. This occurred both when response-participant associations were incompatible (Experiment 2) and when they were compatible (Experiment 3). These results seem to support an agent corepresentation account of correspondence effects emerging in joint settings since they suggest that, in social contexts, critical to obtain transfer-of-learning effects is the spatial relation between stimulus and participant positions while the spatial relation between stimulus and response positions is irrelevant. (c) 2015 APA, all rights reserved).

Gene ontology based transfer learning for protein subcellular localization

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Zhou Shuigeng

2011-02-01

Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

High fidelity simulation effectiveness in nursing students' transfer of learning.

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Kirkman, Tera R

2013-07-13

Members of nursing faculty are utilizing interactive teaching tools to improve nursing student's clinical judgment; one method that has been found to be potentially effective is high fidelity simulation (HFS). The purpose of this time series design study was to determine whether undergraduate nursing students were able to transfer knowledge and skills learned from classroom lecture and a HFS clinical to the traditional clinical setting. Students (n=42) were observed and rated on their ability to perform a respiratory assessment. The observations and ratings took place at the bedside, prior to a respiratory lecture, following the respiratory lecture, and following simulation clinical. The findings indicated that there was a significant difference (p=0.000) in transfer of learning demonstrated over time. Transfer of learning was demonstrated and the use of HFS was found to be an effective learning and teaching method. Implications of results are discussed.

Reciprocal Trust Mediates Deep Transfer of Learning between Games of Strategic Interaction

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Juvina, Ion; Saleem, Muniba; Martin, Jolie M.; Gonzalez, Cleotilde; Lebiere, Christian

2013-01-01

We studied transfer of learning across two games of strategic interaction. We found that the interpersonal relation between two players during and across two games influence development of reciprocal trust and transfer of learning from one game to another. We show that two types of similarities between the games affect transfer: (1) deep…

Spectral Transfer Learning using Information Geometry for a User-Independent Brain-Computer Interface

OpenAIRE

Nicholas Roy Waytowich; Nicholas Roy Waytowich; Vernon Lawhern; Vernon Lawhern; Addison Bohannon; Addison Bohannon; Kenneth Ball; Brent Lance

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry and recreation. However, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter- individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this p...

Spectral Transfer Learning Using Information Geometry for a User-Independent Brain-Computer Interface

OpenAIRE

Waytowich, Nicholas R.; Lawhern, Vernon J.; Bohannon, Addison W.; Ball, Kenneth R.; Lance, Brent J.

2016-01-01

Recent advances in signal processing and machine learning techniques have enabled the application of Brain-Computer Interface (BCI) technologies to fields such as medicine, industry, and recreation; however, BCIs still suffer from the requirement of frequent calibration sessions due to the intra- and inter-individual variability of brain-signals, which makes calibration suppression through transfer learning an area of increasing interest for the development of practical BCI systems. In this p...

Successful Transfer of a Motor Learning Strategy to a Novel Sport.

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Kearney, Philip E; Judge, Phil

2017-10-01

This study investigated whether secondary school students who were taught a motor learning strategy could transfer their knowledge of the strategy to learning a novel task. Twenty adolescents were randomly allocated to a strategy or control group. The strategy group was taught Singer's five-step learning strategy, while the control group received information on the evolution and biomechanics of the basketball free throw. Both groups received three 1-hour practice sessions on a modified basketball shooting task. After one month, participants were introduced to the transfer task, golf putting. Performance accuracy was recorded for all tasks, and participants completed questionnaires regarding strategy use during practice. Participants taught the five-step learning strategy successfully recalled and applied it after a 1-month interval, and they demonstrated superior performance on both acquisition and transfer tasks, relative to the control group. Physical education teachers and coaches should consider using this learning strategy to enhance the learning of closed motor skills.

Case-Based Reasoning in Transfer Learning

Science.gov (United States)

2009-01-01

study of transfer in psychology and education (e.g., Thorndike & Woodworth, 1901; Perkins & Salomon, 1994; Bransford et al., 2000), among other...Sutton, R., & Barto, A. (1998). Reinforcement learning: An introduction. Cambridge, MA: MIT Press. Thorndike , E.L., & Woodworth, R.S. (1901). The

From learning science to teaching science: What transfers?

Science.gov (United States)

Harlow, Danielle Boyd

As educational researchers and teacher educators, we have the responsibility to help teachers gain the skills and knowledge necessary to provide meaningful learning activities for their students. For elementary school science, this means helping teachers create situations in which children can participate in the practices associated with scientific inquiry. Through the framework of transfer I investigated how a professional development course based on an inquiry-based physics curriculum influenced five elementary teachers teaching practices and identified the factors that led to or hindered this transfer. In this study, evidence of transfer consisted of episodes where the teachers used the ideas learned in the physics course to solve new problems such as transforming activities to be appropriate for their students and responding to unexpected students' ideas. The findings of this study highlight the many different ways that teachers use what they learn in content courses to teach science to elementary children. While some teachers transferred pedagogical practices along with the content, others transformed the content to be useful in already existing pedagogical frameworks, and still others show little or no evidence of transfer. What the teachers transferred depended upon their existing teaching context as well as their prior ideas about teaching science and physics content. Specifically, the findings of this study suggest that the teachers transferred only what they sought from the course. One implication of this study is that the sort of science training we provide teachers can affect far more than just the teachers' conceptual understanding of science and performance on written conceptual exams. Science courses have the potential to impact the sort of science education that K-5 children receive in elementary classrooms in terms of the topics taught but the way that science is represented. An additional implication is that teaching science to teachers in ways

Conversation and Silence: Transfer of Learning through the Arts

Science.gov (United States)

Catterall, James S.

2005-01-01

This article explores transfer of learning in the arts to non-arts learning. The analysis is presented in the context of theories of knowledge acquisition more generally. Behavioral and neuro-function processes are discussed.

Promoting learning transfer in post registration education: a collaborative approach.

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Finn, Frances L; Fensom, Sue A; Chesser-Smyth, Patricia

2010-01-01

Pre-registration nurse education in Ireland became a four year undergraduate honors degree programme in 2002 (Government of Ireland, 2000. The Nursing Education Forum Report. Dublin, Dublin Stationary Office.). Consequently, the Irish Government invested significant resources in post registration nursing education in order to align certificate and diploma trained nurses with the qualification levels of new graduates. However, a general concern amongst academic and clinical staff in the South East of Ireland was that there was limited impact of this initiative on practice. These concerns were addressed through a collaborative approach to the development and implementation of a new part-time post registration degree that incorporated an enquiry and practice based learning philosophy. The principles of learning transfer (Ford, K., 1994. Defining transfer of learning the meaning is in the answers. Adult Learning 5 (4), p. 2214.) underpinned the curriculum development and implementation process with the goal of reducing the theory practice gap. This paper reports on all four stages of the curriculum development process: exploration, design, implementation and evaluation (Quinn, F.M., 2002. Principles and Practices of Nurse Education, fourth ed. Nelson Thornes, Cheltenham), and the subsequent impact of learning transfer on practice development. Eclectic approaches of quantitative and qualitative data collection techniques were utilised in the evaluation. The evaluation of this project to date supports our view that this practice based enquiry curriculum promotes the transfer of learning in the application of knowledge to practice, impacting both student and service development.

Learning, Motivation, and Transfer: Successful Teacher Professional Development

Science.gov (United States)

McDonald, Lex

2012-01-01

In this article, I am concerned with three key issues of teacher professional development--teacher learning, motivation, and transfer of learning. Each issue has received minimal attention in teacher professional development literature. The three issues are discussed, and a model of an integrative professional development approach is outlined,…

Examining the Role of Manipulatives and Metacognition on Engagement, Learning, and Transfer

OpenAIRE

Belenky, Daniel M.; Nokes, Timothy J.

2009-01-01

How does the type of learning material impact what is learned? The current research investigates the nature of students’ learning of math concepts when using manipulatives (Uttal, Scudder, & DeLoache, 1997). We examined how the type of manipulative (concrete, abstract, none) and problem-solving prompt (metacognitive or problem-focused) affect student learning, engagement, and knowledge transfer. Students who were given concrete manipulatives with metacognitive prompts showed better transfer o...

Deep transfer learning for automatic target classification: MWIR to LWIR

Science.gov (United States)

Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

2016-05-01

Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

Visual Perceptual Learning and its Specificity and Transfer: A New Perspective

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Cong Yu

2011-05-01

Full Text Available Visual perceptual learning is known to be location and orientation specific, and is thus assumed to reflect the neuronal plasticity in the early visual cortex. However, in recent studies we created “Double training” and “TPE” procedures to demonstrate that these “fundamental” specificities of perceptual learning are in some sense artifacts and that learning can completely transfer to a new location or orientation. We proposed a rule-based learning theory to reinterpret perceptual learning and its specificity and transfer: A high-level decision unit learns the rules of performing a visual task through training. However, the learned rules cannot be applied to a new location or orientation automatically because the decision unit cannot functionally connect to new visual inputs with sufficient strength because these inputs are unattended or even suppressed during training. It is double training and TPE training that reactivate these new inputs, so that the functional connections can be strengthened to enable rule application and learning transfer. Currently we are investigating the properties of perceptual learning free from the bogus specificities, and the results provide some preliminary but very interesting insights into how training reshapes the functional connections between the high-level decision units and sensory inputs in the brain.

Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

Science.gov (United States)

2016-06-01

computational complexity and exhibits sublinear regret , thus providing strong theoretical guarantees [Bou Ammar et al., 2015b] (see Appendix C for details...transferred knowledge, providing a potential mechanism for predicting the effectiveness of transfer learning (and thereby avoiding negative transfer). One...learning from demonstration. We theoretically and empirically analyze the performance of the proposed method and derive, for the first time, regret

Stimulating the cerebellum affects visuomotor adaptation but not intermanual transfer of learning.

Science.gov (United States)

Block, Hannah; Celnik, Pablo

2013-12-01

When systematic movement errors occur, the brain responds with a systematic change in motor behavior. This type of adaptive motor learning can transfer intermanually; adaptation of movements of the right hand in response to training with a perturbed visual signal (visuomotor adaptation) may carry over to the left hand. While visuomotor adaptation has been studied extensively, it is unclear whether the cerebellum, a structure involved in adaptation, is important for intermanual transfer as well. We addressed this question with three experiments in which subjects reached with their right hands as a 30° visuomotor rotation was introduced. Subjects received anodal or sham transcranial direct current stimulation on the trained (experiment 1) or untrained (experiment 2) hemisphere of the cerebellum, or, for comparison, motor cortex (M1). After the training period, subjects reached with their left hand, without visual feedback, to assess intermanual transfer of learning aftereffects. Stimulation of the right cerebellum caused faster adaptation, but none of the stimulation sites affected transfer. To ascertain whether cerebellar stimulation would increase transfer if subjects learned faster as well as a larger amount, in experiment 3 anodal and sham cerebellar groups experienced a shortened training block such that the anodal group learned more than sham. Despite the difference in adaptation magnitude, transfer was similar across these groups, although smaller than in experiment 1. Our results suggest that intermanual transfer of visuomotor learning does not depend on cerebellar activity and that the number of movements performed at plateau is an important predictor of transfer.

Selective transfer of visual working memory training on Chinese character learning.

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Opitz, Bertram; Schneiders, Julia A; Krick, Christoph M; Mecklinger, Axel

2014-01-01

Previous research has shown a systematic relationship between phonological working memory capacity and second language proficiency for alphabetic languages. However, little is known about the impact of working memory processes on second language learning in a non-alphabetic language such as Mandarin Chinese. Due to the greater complexity of the Chinese writing system we expect that visual working memory rather than phonological working memory exerts a unique influence on learning Chinese characters. This issue was explored in the present experiment by comparing visual working memory training with an active (auditory working memory training) control condition and a passive, no training control condition. Training induced modulations in language-related brain networks were additionally examined using functional magnetic resonance imaging in a pretest-training-posttest design. As revealed by pre- to posttest comparisons and analyses of individual differences in working memory training gains, visual working memory training led to positive transfer effects on visual Chinese vocabulary learning compared to both control conditions. In addition, we found sustained activation after visual working memory training in the (predominantly visual) left infero-temporal cortex that was associated with behavioral transfer. In the control conditions, activation either increased (active control condition) or decreased (passive control condition) without reliable behavioral transfer effects. This suggests that visual working memory training leads to more efficient processing and more refined responses in brain regions involved in visual processing. Furthermore, visual working memory training boosted additional activation in the precuneus, presumably reflecting mental image generation of the learned characters. We, therefore, suggest that the conjoint activity of the mid-fusiform gyrus and the precuneus after visual working memory training reflects an interaction of working memory and

Evaluation of knowledge transfer in an immersive virtual learning environment for the transportation community.

Science.gov (United States)

2014-05-01

Immersive Virtual Learning Environments (IVLEs) are extensively used in training, but few rigorous scientific investigations regarding the : transfer of learning have been conducted. Measurement of learning transfer through evaluative methods is key ...

Gas transfer system

International Nuclear Information System (INIS)

Oberlin, J.C.; Frick, G.; Kempfer, C.; North, C.

1988-09-01

The state of work on the Vivitron gas transfer system and the system functions are summarized. The system has to: evacuate the Vivitron reservoir; transfer gas from storage tanks to the Vivitron; recirculate gas during operation; transfer gas from the Vivitron to storage tanks; and assure air input. The system is now being installed. Leak alarms are given by SF6 detectors, which set off a system of forced ventilation. Another system continuously monitors the amount of SF6 in the tanks [fr

Transfer learning for bimodal biometrics recognition

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Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

2013-10-01

Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

A Qualitative Exploration of Multiple Perspectives on Transfer of Learning Between Classroom and Clinical Workplace.

Science.gov (United States)

Peters, Sanne; Clarebout, Geraldine; van Nuland, Marc; Aertgeerts, Bert; Roex, Ann

2018-01-01

Phenomenon: Transfer of learning between classroom and workplace appears to be difficult. Various conceptions about learning in either the classroom or the workplace exist among stakeholders, yet little is known about their conceptions of the transfer of learning between both settings. This study explored stakeholders' conceptions about transfer of learning between classroom-based learning and workplace practice. Homogeneous focus groups with students, medical teachers, and workplace supervisors were conducted using a constructivist grounded theory approach. The 54 participants' conceptions mainly related to their beliefs about who was responsible for (a) preparing for transfer of learning, (b) being at the workplace and connecting back to classroom-based learning, and (c) reflecting on transfer of learning and continuing the process. A continuum was recognized between those who held medical teachers/workplace supervisors responsible and those who held students responsible. Insights: There appears to be a variety of conceptions about who is responsible for enabling the transfer process. These conceptions may influence learning and instructional activities. Hence, it may be necessary to make these beliefs explicit in order to better align stakeholders' conceptions. To this end, the conceptual framework created in this study may be a useful tool.

Research on the transfer learning of the vehicle logo recognition

Science.gov (United States)

Zhao, Wei

2017-08-01

The Convolutional Neural Network of Deep Learning has been a huge success in the field of image intelligent transportation system can effectively solve the traffic safety, congestion, vehicle management and other problems of traffic in the city. Vehicle identification is a vital part of intelligent transportation, and the effective information in vehicles is of great significance to vehicle identification. With the traffic system on the vehicle identification technology requirements are getting higher and higher, the vehicle as an important type of vehicle information, because it should not be removed, difficult to change and other features for vehicle identification provides an important method. The current vehicle identification recognition (VLR) is mostly used to extract the characteristics of the method of classification, which for complex classification of its generalization ability to be some constraints, if the use of depth learning technology, you need a lot of training samples. In this paper, the method of convolution neural network based on transfer learning can solve this problem effectively, and it has important practical application value in the task of vehicle mark recognition.

Impact of Individual Perception of Organizational Culture on the Learning Transfer Environment

Science.gov (United States)

Chatterjee, Aindrila; Pereira, Arun; Bates, Reid

2018-01-01

This research is an empirical study of the relationship between organization culture, as perceived by employees, and the work-environment-related learning transfer factors in organizations, which we call learning transfer environment (LTE). To measure perceptions of organization culture, we use the Organizational Culture Assessment Instrument and…

A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

Science.gov (United States)

Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L

2016-03-01

Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015

Mining for preparatory processes of transfer learning in a blended course

Science.gov (United States)

Ng, K.; Hartman, K.; Goodkin, N.; Wai Hoong Andy, K.

2017-12-01

585 undergraduate science students enrolled in a multidisciplinary environmental sustainability course. Each week, students were given the opportunity to read online materials, answer multiple choice and short answer questions, and attend a three-hour lecture. The online materials and questions were released one week prior to the lecture. After each week, we mined the student data logs exported from the course learning management system and used a model-based clustering algorithm to divide the class into six groups according to resource access patterns. The patterns were mostly based on the frequency with which a student accessed the items in the growing set of online resources and whether those resources were relevant to the upcoming exam. Each exam was self-contained—meaning the second exam did not reference content taught during the first half of the course. The exam items themselves were intentionally designed to provide a mix of recall, application, and transfer items. Recall items referenced facts and examples provided during the lectures and course materials. Application items asked students to solve problems using the methods shown during lecture. Transfer items asked students to use what they had learned to analyze new data sets and unfamiliar problems. We then used a log-likelihood analysis to determine if there were differences in item accuracy on the exams by resource pattern clusters. We found students who deviated from the majority of student access patterns by accessing prior material during the recess break before new material had been assigned and introduced performed significantly more accurately on the transfer items than the other cluster groups. This finding fits with the concept of Preparation for Future Learning (Bransford & Schwartz, 1999) which suggests learners can be strategic about their learning to prepare themselves to complete new tasks in the future. Our findings also suggest that using learning analytics to call attention activity

Finding the Intersection of the Learning Organization and Learning Transfer: The Significance of Leadership

Science.gov (United States)

Kim, Jun Hee; Callahan, Jamie L.

2013-01-01

Purpose: This article aims to develop a conceptual framework delineating the key dimension of the learning organization which significantly influences learning transfer. Design/methodology/approach: The conceptual framework was developed by analyzing previous studies and synthesizing the results associated with the following four relationships:…

Game based learning for 21st century transferable skills: challenges and opportunities

NARCIS (Netherlands)

Bellotti, Francesco; Bottino, Rosa Maria; Nadolski, Rob; Fernández Manjón, Baltasar

2012-01-01

Bellotti, F., Bottino, R. M., Nadolski, R. J., & Fernández Manjón, B. (2012, 4-6 July). Game based learning for 21st century transferable skills: challenges and opportunities. Presentation at the Workshop Game based learning for 21st century transferable skills: challenges and opportunities, 12th

Challenge of Helping Introductory Physics Students Transfer Their Learning by Engaging with a Self-Paced Learning Tutorial

Directory of Open Access Journals (Sweden)

Emily Megan Marshman

2018-03-01

Full Text Available With advances in digital technology, research-validated self-paced learning tools can play an increasingly important role in helping students with diverse backgrounds become good problem solvers and independent learners. Thus, it is important to ensure that all students engage with self-paced learning tools effectively in order to learn the content deeply, develop good problem-solving skills, and transfer their learning from one context to another. Here, we first provide an overview of a holistic framework for engaging students with self-paced learning tools so that they can transfer their learning to solve novel problems. The framework not only takes into account the features of the self-paced learning tools but also how those tools are implemented, the extent to which the tools take into account student characteristics, and whether factors related to students’ social environments are accounted for appropriately in the implementation of those tools. We then describe an investigation in which we interpret the findings using the framework. In this study, a research-validated self-paced physics tutorial was implemented in both controlled one-on-one interviews and in large enrollment, introductory calculus-based physics courses as a self-paced learning tool. We find that students who used the tutorial in a controlled one-on-one interview situation performed significantly better on transfer problems than those who used it as a self-paced learning tool in the large-scale implementation. The findings suggest that critically examining and taking into account how the self-paced tools are implemented and incentivized, student characteristics including their self-regulation and time-management skills, and social and environmental factors can greatly impact the extent and manner in which students engage with these learning tools. Getting buy in from students about the value of these tools and providing appropriate support while implementing them is

A transfer learning framework for traffic video using neuro-fuzzy ...

Indian Academy of Sciences (India)

P M Ashok Kumar

2017-08-04

Aug 4, 2017 ... The proposed ANFIS-LCTE transfer learning model consists of four steps. (1) Low level visual items .... algorithm clusters object trajectories based on the distance parameters like Euclidean ..... Machine Learning, pp. 113–120.

Nuclear Knowledge Creation and Transfer in Enriched Learning Environments: A Practical Approach

International Nuclear Information System (INIS)

Ruiz, F.; Gonzalez, J.; Delgado, J.L.

2016-01-01

Full text: Technology, the social nature of learning and the generational learning style are conforming new models of training that are changing the roles of the instructors, the channels of communication and the proper learning content of the knowledge to be transferred. New training methodologies are being using in the primary and secondary education and “Vintage” classroom learning does not meet the educational requirements of these methodologies; therefore, it’s necessary to incorporate them in the Knowledge Management processes used in the nuclear industry. This paper describes a practical approach of an enriched learning environment with the purpose of creating and transferring nuclear knowledge. (author

Examining factors affecting beginning teachers' transfer of learning of ICT-enhanced learning activities in their teaching practice

NARCIS (Netherlands)

Agyei, D.D.; Voogt, J.

2014-01-01

This study examined 100 beginning teachers’ transfer of learning when utilising Information Communication Technology-enhanced activity-based learning activities. The beginning teachers had participated in a professional development program that was characterised by ‘learning technology by

Technology Transfer, Labour and Local Learning Processes in Malaysian Industry

DEFF Research Database (Denmark)

Wangel, Arne

1999-01-01

The transfer of technologies by the foreign electronic industries operating in Malaysia involves training of workers for various purposes. The upgrading of skills to assimilate the transferred technology aims at increasing productivity and product quality. Communicating awareness about work hazards...... is meant to reduce breakdowns in production and workers' accidents. How do the training paradigms, which transnationals introduce in their subsidiaries in Malaysia, interact with the preconditions of learning with the local labour force? In shaping local learning processes, what is the scope for workers...

E-Learning Barriers and Solutions to Knowledge Management and Transfer

Science.gov (United States)

Oye, Nathaniel David; Salleh, Mazleena

2013-01-01

This paper present a systematic overview of barriers and solutions of e-learning in knowledge management (KM) and knowledge transfer (KT) with more focus on organizations. The paper also discusses KT in organizational settings and KT in the field of e-learning. Here, an e-learning initiative shows adaptive solutions to overcome knowledge transfer…

Episodic Feelings and Transfer of Learning

Science.gov (United States)

Nemirovsky, Ricardo

2011-01-01

The goal of this article is to develop a new perspective on transfer of learning integrating cognition, emotion, and bodily experience. It is based on a case study with a 10-year-old girl as she explored the use of a motion detector, allowing for the simultaneous graphing of the position versus time of 2 moving points. The paper elaborates on the…

The Transfer of Learning Associated with Audio Feedback on Written Work

Directory of Open Access Journals (Sweden)

Tanya Martini

2014-11-01

Full Text Available This study examined whether audio feedback provided to undergraduates (N=51 about one paper would prove beneficial in terms of improving their grades on another, unrelated paper of the same type. We examined this issue both in terms of student beliefs about learning transfer, as well as their actual ability to transfer what had been learned on one assignment to another, subsequent assignment. Results indicated that students believed that they would be able to transfer what they had learned via audio feedback. Moreover, results also suggested that students actually did generalize the overarching comments about content and structure made in the audio files to a subsequent paper, the content of which differed substantially from the initial one. Both students and teaching assistants demonstrated very favourable responses to this type of feedback, suggesting that it was both clear and comprehensive.

IMPROVEMENT EFFORTS TO LEARN LESSONS ACTIVITIES CHASSIS POWER TRANSFER STANDARD COMPETENCE AND CORRECT STEERING SYSTEM WITH LEARNING METHOD DISCOVERY INQUIRY CLASS XIB SMK MUHAMMADIYAH GAMPING ACADEMIC YEAR 2013/2014

Directory of Open Access Journals (Sweden)

Harry Suharto

2013-12-01

Full Text Available The purpose of the study to determine the increase learners' learning activities subjects chassis and power transfer competency standard steering system repair discovery learning through the implementation of class XI inquiry Lightweight Vehicle Technology SMK Muhammadiyah Gamping, Sleman academic year 2013/2014. This research including action research   Research conducted at SMK Muhammadiyah Gamping XIB class academic year 2013/2014 with a sample of 26 students. Techniques of data collection using questionnaire sheet, observation sheets and documentation to determine the increase in student activity. Instrument validation study using experts judgment. Analysis using descriptive statistics using the technique .   The results showed that the increased activity of the first cycle to the second cycle include an increase of 57.7 % Visual activities; Oral activities amounted to 61.6 %; Listening activities amounted to 23.04 %; Writing activities by 8.7 %; Mental activities of 73.1 %; Emotional activities of 42.3 % ( for the spirit of the students in learning activities ; Motor activities amounted to -7.7 % ( decrease negative activity . Based on these results can be known to most students in SMK Muhammadiyah Gamping gave a positive opinion on the use of inquiry and discovery learning method has a view that the use of inquiry discovery learning methods can be useful for students and schools themselves. Learners who have a good perception of the use of discovery learning method of inquiry he has known and fully aware of the standards of achievement of competence theory fix the steering system. Learning discovery learning methods on achievement of competency standards inquiry repair steering systems theory pleased with the learning process, they are also able to: 1 increase the motivation to learn, 2 improving learning achievement; 3 enhancing creativity; 4 listen, respect, and accept the opinion of the participants other students; 5 reduce boredom

Transfer of learning: Radiographers' perceptions of simulation-based educational intervention

International Nuclear Information System (INIS)

Aura, S.; Jordan, S.; Saano, S.; Tossavainen, K.; Turunen, H.

2016-01-01

Aim: The aims of this qualitative descriptive study were to 1) explore and define radiographers' competence in intravenous pharmacotherapy before and after a simulation-based education, 2) examine radiographer's perceptions of transfer of learning into clinical practice. Method: Sixteen diagnostic radiographers in one hospitals' Clinical Radiology Unit were individually interviewed before a multidisciplinary simulation-based pharmacotherapy education intervention in 2012 and fourteen were re-interviewed after the intervention 6–7 months later. Data were analyzed using qualitative content analysis. Results: Before education the participants reported uncertain competence in pain management during imaging procedures and acute situations. These weak competence areas identified were strengthened and self-confidence grew. The intervention improved the domains of pharmacotherapy-related patient safety; teamwork development and communication skills. In addition, the radiographers indicated that the iv. pharmacotherapy knowledge from simulation learning was transferred to routine work. Conclusion: The results of this study suggest simulation-based education is suitable for radiographers' pharmacotherapy learning. Adequate pain measurement and management are essential during invasive procedures and these skills can be realistically learned in simulations and transferred to clinical practice. - Highlights: • Simulation education is suitable for professionals' pharmacotherapy education. • Radiographers felt education empowered them to manage acute situations. • Skills in pain measurement, analgesia and patient monitoring enhanced. • Communication and teamwork skills were enhanced. • Simulation-based learning was transferred to clinical practice.

Online Learning of Safe Patient Transfers in Occupational Therapy Education

Directory of Open Access Journals (Sweden)

Cynthia L. Hayden D. H. Ed., OTR/L, CHT

2013-02-01

Full Text Available Online higher education is steadily increasing. For programs in allied health to be offered effectively in an elearning format, clinical psychomotor skills need to be addressed. The aim of this research was to design, implement, and evaluate an online safe patient transfers module for occupational therapy assistant (OTAstudents. The efficacy of teaching safe patient transfers in an e-learning environment was appraised using both quantitative and qualitative analysis. The applied research project was completed at a Tennessee community college. A convenience sample of eighteen students participated in the pilot study. Twenty-five studentsparticipated in the subsequent study. The instructional design of the course was based on Mager’s CriterionReferenced Instruction model. Streaming video was used as the delivery method for course material. A pretest/posttest evaluated the students’ cognitive knowledge of safe patient transfers. A behavioral transferscompetency checklist was used to rate videotapes of students’ performance of assisted stand pivot and dependent sliding board transfers. Research findings indicated students were able to learn this psychomotor clinical skill online with beginning proficiency. A paired t-test showed marked improvement of cognitive knowledge. A student learning survey revealed the majority of students preferred at least one hands-on classroom session where instructor feedback and interaction with classmates confirmed safe and effectiveclinical technique.

A Novel Transfer Learning Method Based on Common Space Mapping and Weighted Domain Matching

KAUST Repository

Liang, Ru-Ze; Xie, Wei; Li, Weizhi; Wang, Hongqi; Wang, Jim Jing-Yan; Taylor, Lisa

2017-01-01

In this paper, we propose a novel learning framework for the problem of domain transfer learning. We map the data of two domains to one single common space, and learn a classifier in this common space. Then we adapt the common classifier to the two domains by adding two adaptive functions to it respectively. In the common space, the target domain data points are weighted and matched to the target domain in term of distributions. The weighting terms of source domain data points and the target domain classification responses are also regularized by the local reconstruction coefficients. The novel transfer learning framework is evaluated over some benchmark cross-domain data sets, and it outperforms the existing state-of-the-art transfer learning methods.

A Novel Transfer Learning Method Based on Common Space Mapping and Weighted Domain Matching

KAUST Repository

Liang, Ru-Ze

2017-01-17

In this paper, we propose a novel learning framework for the problem of domain transfer learning. We map the data of two domains to one single common space, and learn a classifier in this common space. Then we adapt the common classifier to the two domains by adding two adaptive functions to it respectively. In the common space, the target domain data points are weighted and matched to the target domain in term of distributions. The weighting terms of source domain data points and the target domain classification responses are also regularized by the local reconstruction coefficients. The novel transfer learning framework is evaluated over some benchmark cross-domain data sets, and it outperforms the existing state-of-the-art transfer learning methods.

White blood cells identification system based on convolutional deep neural learning networks.

Science.gov (United States)

Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

2017-11-16

White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

Do semantic contextual cues facilitate transfer learning from video in toddlers?

Science.gov (United States)

Zimmermann, Laura; Moser, Alecia; Grenell, Amanda; Dickerson, Kelly; Yao, Qianwen; Gerhardstein, Peter; Barr, Rachel

2015-01-01

Young children typically demonstrate a transfer deficit, learning less from video than live presentations. Semantically meaningful context has been demonstrated to enhance learning in young children. We examined the effect of a semantically meaningful context on toddlers' imitation performance. Two- and 2.5-year-olds participated in a puzzle imitation task to examine learning from either a live or televised model. The model demonstrated how to assemble a three-piece puzzle to make a fish or a boat, with the puzzle demonstration occurring against a semantically meaningful background context (ocean) or a yellow background (no context). Participants in the video condition performed significantly worse than participants in the live condition, demonstrating the typical transfer deficit effect. While the context helped improve overall levels of imitation, especially for the boat puzzle, only individual differences in the ability to self-generate a stimulus label were associated with a reduction in the transfer deficit.

Cross-Cultural Learning and Knowledge Transfer between Wetern and African Firms

DEFF Research Database (Denmark)

Kuada, John

2006-01-01

: (1) cultural sensitivity, (2) transfer and learning capacity of partners, and (3) the strategic importance and uniqueness of the relationships. The evidence also highlights the importance of inter-cultural communication skills in the knowledge transfer process...

Transfer Learning for Class Imbalance Problems with Inadequate Data.

Science.gov (United States)

Al-Stouhi, Samir; Reddy, Chandan K

2016-07-01

A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

Analysis of Student Service-Learning Reflections for the Assessment of Transferable-Skills Development

Science.gov (United States)

Rizzo, D. M.; Dewoolkar, M.; Hayden, N.; Oka, L.; Pearce, A. R.

2010-12-01

The civil and environmental engineering (CEE) programs at the University of Vermont (UVM) incorporate systems thinking and a systems approach to sustainable engineering problem solving. A systems approach considers long-term social, environmental and economic factors within the context of the engineering problem solution and encompasses sustainable engineering solutions. Our goal is to prepare students to become leaders in their chosen field who can anticipate co-products associated with forecasted solutions. As a way of practicing the systems approach, we include service-learning projects in many of our undergraduate engineering courses, culminating with the senior capstone design course. We use a variety of formative and summative assessment methods to gage student understanding and attitudes including student surveys, focus groups, assessment of student projects, and student reflections. Student reflections from two courses -Modeling Environmental and Transportation Systems (31 juniors) and Senior Design Project (30 seniors) are compared. Of these, 25 students were common to both courses. The focus of the systems modeling service-learning project involved mentoring home-schooled children (11-14 yrs old) to solve problems of mobility, using the fun and inspiration of biomimicry. Students were required to invent innovative methods to move people or goods that improve associated constraints (i.e., minimize congestion, reduce pollution, increase safety), or reduce the need for transportation altogether. The capstone design project required a comprehensive engineering design involving two or more CEE sub-disciplines. Both service-learning projects were intended to enhance students’ academic learning experience, attain civic engagement and reinforce transferable skills (written and oral communication, teamwork, leadership and mentoring skills). The student course reflections were not guided; yet they provided valuable data to assess commonalities and differences in

Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture.

Science.gov (United States)

Chen, C L Philip; Liu, Zhulin

2018-01-01

Broad Learning System (BLS) that aims to offer an alternative way of learning in deep structure is proposed in this paper. Deep structure and learning suffer from a time-consuming training process because of a large number of connecting parameters in filters and layers. Moreover, it encounters a complete retraining process if the structure is not sufficient to model the system. The BLS is established in the form of a flat network, where the original inputs are transferred and placed as "mapped features" in feature nodes and the structure is expanded in wide sense in the "enhancement nodes." The incremental learning algorithms are developed for fast remodeling in broad expansion without a retraining process if the network deems to be expanded. Two incremental learning algorithms are given for both the increment of the feature nodes (or filters in deep structure) and the increment of the enhancement nodes. The designed model and algorithms are very versatile for selecting a model rapidly. In addition, another incremental learning is developed for a system that has been modeled encounters a new incoming input. Specifically, the system can be remodeled in an incremental way without the entire retraining from the beginning. Satisfactory result for model reduction using singular value decomposition is conducted to simplify the final structure. Compared with existing deep neural networks, experimental results on the Modified National Institute of Standards and Technology database and NYU NORB object recognition dataset benchmark data demonstrate the effectiveness of the proposed BLS.

DO SEMANTIC CONTEXTUAL CUES FACILITATE TRANSFER LEARNING FROM VIDEO IN TODDLERS?

Directory of Open Access Journals (Sweden)

Laura eZimmermann

2015-05-01

Full Text Available Young children typically demonstrate a transfer deficit, learning less from video than live presentations. Semantically meaningful context has been demonstrated to enhance learning in young children. We examined the effect of a semantically meaningful context on toddlers’ imitation performance. Two- and 2.5-year-olds participated in a puzzle imitation task to examine learning from either a live or televised model. The model demonstrated how to assemble a three-piece puzzle to make a fish or a boat, with the puzzle demonstration occurring against a semantically meaningful background context (ocean or a yellow background (no context. Participants in the video condition performed significantly worse than participants in the live condition, demonstrating the typical transfer deficit effect. While the context helped improve overall levels of imitation, especially for the boat puzzle, only individual differences in the ability to self-generate a stimulus label were related to a reduction in the transfer deficit.

Shared acoustic codes underlie emotional communication in music and speech-Evidence from deep transfer learning.

Science.gov (United States)

Coutinho, Eduardo; Schuller, Björn

2017-01-01

Music and speech exhibit striking similarities in the communication of emotions in the acoustic domain, in such a way that the communication of specific emotions is achieved, at least to a certain extent, by means of shared acoustic patterns. From an Affective Sciences points of view, determining the degree of overlap between both domains is fundamental to understand the shared mechanisms underlying such phenomenon. From a Machine learning perspective, the overlap between acoustic codes for emotional expression in music and speech opens new possibilities to enlarge the amount of data available to develop music and speech emotion recognition systems. In this article, we investigate time-continuous predictions of emotion (Arousal and Valence) in music and speech, and the Transfer Learning between these domains. We establish a comparative framework including intra- (i.e., models trained and tested on the same modality, either music or speech) and cross-domain experiments (i.e., models trained in one modality and tested on the other). In the cross-domain context, we evaluated two strategies-the direct transfer between domains, and the contribution of Transfer Learning techniques (feature-representation-transfer based on Denoising Auto Encoders) for reducing the gap in the feature space distributions. Our results demonstrate an excellent cross-domain generalisation performance with and without feature representation transfer in both directions. In the case of music, cross-domain approaches outperformed intra-domain models for Valence estimation, whereas for Speech intra-domain models achieve the best performance. This is the first demonstration of shared acoustic codes for emotional expression in music and speech in the time-continuous domain.

Energy transfer in plasmonic systems

International Nuclear Information System (INIS)

Pustovit, Vitaliy N; Urbas, Augustine M; Shahbazyan, Tigran V

2014-01-01

We present our results on energy transfer between donor and acceptor molecules or quantum dots near a plasmonic nanoparticle. In such systems, the Förster resonance energy transfer is strongly modified due to plasmon-mediated coupling between donors and acceptors. The transfer efficiency is determined by a competition between transfer, radiation and dissipation that depends sensitively on system parameters. When donor and accepror spectral bands overlap with dipole surface plasmon resonance, the dominant transfer mechanism is through plasmon-enhanced radiative coupling. When transfer takes place from an ensemble of donors to an acceptor, a cooperative amplification of energy transfer takes place in a wide range of system parameters. (paper)

Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms

Science.gov (United States)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.

2017-12-01

Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p  =  0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.

Heat transfer system

Science.gov (United States)

Not Available

1980-03-07

A heat transfer system for a nuclear reactor is described. Heat transfer is accomplished within a sealed vapor chamber which is substantially evacuated prior to use. A heat transfer medium, which is liquid at the design operating temperatures, transfers heat from tubes interposed in the reactor primary loop to spaced tubes connected to a steam line for power generation purposes. Heat transfer is accomplished by a two-phase liquid-vapor-liquid process as used in heat pipes. Condensible gases are removed from the vapor chamber through a vertical extension in open communication with the chamber interior.

Shared acoustic codes underlie emotional communication in music and speech-Evidence from deep transfer learning.

Directory of Open Access Journals (Sweden)

Eduardo Coutinho

Full Text Available Music and speech exhibit striking similarities in the communication of emotions in the acoustic domain, in such a way that the communication of specific emotions is achieved, at least to a certain extent, by means of shared acoustic patterns. From an Affective Sciences points of view, determining the degree of overlap between both domains is fundamental to understand the shared mechanisms underlying such phenomenon. From a Machine learning perspective, the overlap between acoustic codes for emotional expression in music and speech opens new possibilities to enlarge the amount of data available to develop music and speech emotion recognition systems. In this article, we investigate time-continuous predictions of emotion (Arousal and Valence in music and speech, and the Transfer Learning between these domains. We establish a comparative framework including intra- (i.e., models trained and tested on the same modality, either music or speech and cross-domain experiments (i.e., models trained in one modality and tested on the other. In the cross-domain context, we evaluated two strategies-the direct transfer between domains, and the contribution of Transfer Learning techniques (feature-representation-transfer based on Denoising Auto Encoders for reducing the gap in the feature space distributions. Our results demonstrate an excellent cross-domain generalisation performance with and without feature representation transfer in both directions. In the case of music, cross-domain approaches outperformed intra-domain models for Valence estimation, whereas for Speech intra-domain models achieve the best performance. This is the first demonstration of shared acoustic codes for emotional expression in music and speech in the time-continuous domain.

Shared acoustic codes underlie emotional communication in music and speech—Evidence from deep transfer learning

Science.gov (United States)

Schuller, Björn

2017-01-01

Music and speech exhibit striking similarities in the communication of emotions in the acoustic domain, in such a way that the communication of specific emotions is achieved, at least to a certain extent, by means of shared acoustic patterns. From an Affective Sciences points of view, determining the degree of overlap between both domains is fundamental to understand the shared mechanisms underlying such phenomenon. From a Machine learning perspective, the overlap between acoustic codes for emotional expression in music and speech opens new possibilities to enlarge the amount of data available to develop music and speech emotion recognition systems. In this article, we investigate time-continuous predictions of emotion (Arousal and Valence) in music and speech, and the Transfer Learning between these domains. We establish a comparative framework including intra- (i.e., models trained and tested on the same modality, either music or speech) and cross-domain experiments (i.e., models trained in one modality and tested on the other). In the cross-domain context, we evaluated two strategies—the direct transfer between domains, and the contribution of Transfer Learning techniques (feature-representation-transfer based on Denoising Auto Encoders) for reducing the gap in the feature space distributions. Our results demonstrate an excellent cross-domain generalisation performance with and without feature representation transfer in both directions. In the case of music, cross-domain approaches outperformed intra-domain models for Valence estimation, whereas for Speech intra-domain models achieve the best performance. This is the first demonstration of shared acoustic codes for emotional expression in music and speech in the time-continuous domain. PMID:28658285

Transferring managerial learning back to the workplace : the influence of personality and the workplace environment

OpenAIRE

Belling, Ruth

2000-01-01

This thesis identifies the influences of individual characteristics, particularly psychological type preferences, and workplace environment features, on managers’ perceptions of the barriers and facilitators to transferring their learning from management development programmes. In doing so, it provides information and insights to help increase understanding of the transfer of learning process through the building of a model of transfer. Guided by a Realist perspective, this ...

Substructural Regularization With Data-Sensitive Granularity for Sequence Transfer Learning.

Science.gov (United States)

Sun, Shichang; Liu, Hongbo; Meng, Jiana; Chen, C L Philip; Yang, Yu

2018-06-01

Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy. STLM can achieve the competing goals of preserving the target domain substructure and utilizing the observations from both the target and source domains simultaneously. The estimation of STLM is very efficient since an analytical solution can be derived as a necessary and sufficient condition. The relative usability of substructures to act as regularization parameters and the time complexity of STLM are also analyzed and discussed. Comprehensive experiments of part-of-speech tagging with both Brown and Twitter corpora fully justify that our model can make improvements on all the combinations of source and target domains.

CANISTER TRANSFER SYSTEM DESCRIPTION DOCUMENT

International Nuclear Information System (INIS)

B. Gorpani

2000-01-01

The Canister Transfer System receives transportation casks containing large and small disposable canisters, unloads the canisters from the casks, stores the canisters as required, loads them into disposal containers (DCs), and prepares the empty casks for re-shipment. Cask unloading begins with cask inspection, sampling, and lid bolt removal operations. The cask lids are removed and the canisters are unloaded. Small canisters are loaded directly into a DC, or are stored until enough canisters are available to fill a DC. Large canisters are loaded directly into a DC. Transportation casks and related components are decontaminated as required, and empty casks are prepared for re-shipment. One independent, remotely operated canister transfer line is provided in the Waste Handling Building System. The canister transfer line consists of a Cask Transport System, Cask Preparation System, Canister Handling System, Disposal Container Transport System, an off-normal canister handling cell with a transfer tunnel connecting the two cells, and Control and Tracking System. The Canister Transfer System operating sequence begins with moving transportation casks to the cask preparation area with the Cask Transport System. The Cask Preparation System prepares the cask for unloading and consists of cask preparation manipulator, cask inspection and sampling equipment, and decontamination equipment. The Canister Handling System unloads the canister(s) and places them into a DC. Handling equipment consists of a bridge crane hoist,; DC--loading manipulator, lifting fixtures, and small canister staging racks. Once the cask has been unloaded, the Cask Preparation System decontaminates the cask exterior and returns it to the Carrier/Cask Handling System via the Cask Transport System. After the; DC--is fully loaded, the Disposal Container Transport System moves the; DC--to the Disposal Container Handling System for welding. To handle off-normal canisters, a separate off-normal canister

Canister Transfer System Description Document

International Nuclear Information System (INIS)

2000-01-01

The Canister Transfer System receives transportation casks containing large and small disposable canisters, unloads the canisters from the casks, stores the canisters as required, loads them into disposal containers (DCs), and prepares the empty casks for re-shipment. Cask unloading begins with cask inspection, sampling, and lid bolt removal operations. The cask lids are removed and the canisters are unloaded. Small canisters are loaded directly into a DC, or are stored until enough canisters are available to fill a DC. Large canisters are loaded directly into a DC. Transportation casks and related components are decontaminated as required, and empty casks are prepared for re-shipment. One independent, remotely operated canister transfer line is provided in the Waste Handling Building System. The canister transfer line consists of a Cask Transport System, Cask Preparation System, Canister Handling System, Disposal Container Transport System, an off-normal canister handling cell with a transfer tunnel connecting the two cells, and Control and Tracking System. The Canister Transfer System operating sequence begins with moving transportation casks to the cask preparation area with the Cask Transport System. The Cask Preparation System prepares the cask for unloading and consists of cask preparation manipulator, cask inspection and sampling equipment, and decontamination equipment. The Canister Handling System unloads the canister(s) and places them into a DC. Handling equipment consists of a bridge crane/hoist, DC loading manipulator, lifting fixtures, and small canister staging racks. Once the cask has been unloaded, the Cask Preparation System decontaminates the cask exterior and returns it to the Carrier/Cask Handling System via the Cask Transport System. After the DC is fully loaded, the Disposal Container Transport System moves the DC to the Disposal Container Handling System for welding. To handle off-normal canisters, a separate off-normal canister handling

A study of student perceptions of learning transfer from a human anatomy and physiology course in an allied health program

Science.gov (United States)

Harrell, Leigh S.

The purpose of this study was two-fold. First the study was designed to determine student perceptions regarding the perceived degree of original learning from a human anatomy and physiology course, and the student perception of the use of the knowledge in an allied health program. Second, the intention of the study was to establish student beliefs on the characteristics of the transfer of learning including those factors which enhance learning transfer and those that serve as barriers to learning transfer. The study participants were those students enrolled in any allied health program at a community college in a Midwest state, including: nursing, radiology, surgical technology, health information technology, and paramedic. Both quantitative and qualitative data were collected and analyzed from the responses to the survey. A sub-group of participants were chosen to participate in semi-structured formal interviews. From the interviews, additional qualitative data were gathered. The data collected through the study demonstrated student perception of successful transfer experiences. The students in the study were able to provide specific examples of learning transfer experienced from the human anatomy and physiology course in their allied health program. Findings also suggested students who earned higher grades in the human anatomy and physiology course perceived greater understanding and greater use of the course's learning objectives in their allied health program. The study found the students believed the following learning activities enhances the transfer of learning: (1) Providing application of the information or skills being learned during the instruction of the course content enhances the transfer of learning. (2) Providing resource materials and activities which allow the students to practice the content being taught facilitates the transfer of learning. The students made the following recommendations to remove barriers to the transfer of learning: (1

Classification and unsupervised clustering of LIGO data with Deep Transfer Learning

Science.gov (United States)

George, Daniel; Shen, Hongyu; Huerta, E. A.

2018-05-01

Gravitational wave detection requires a detailed understanding of the response of the LIGO and Virgo detectors to true signals in the presence of environmental and instrumental noise. Of particular interest is the study of anomalous non-Gaussian transients, such as glitches, since their occurrence rate in LIGO and Virgo data can obscure or even mimic true gravitational wave signals. Therefore, successfully identifying and excising these anomalies from gravitational wave data is of utmost importance for the detection and characterization of true signals and for the accurate computation of their significance. To facilitate this work, we present the first application of deep learning combined with transfer learning to show that knowledge from pretrained models for real-world object recognition can be transferred for classifying spectrograms of glitches. To showcase this new method, we use a data set of twenty-two classes of glitches, curated and labeled by the Gravity Spy project using data collected during LIGO's first discovery campaign. We demonstrate that our Deep Transfer Learning method enables an optimal use of very deep convolutional neural networks for glitch classification given small and unbalanced training data sets, significantly reduces the training time, and achieves state-of-the-art accuracy above 98.8%, lowering the previous error rate by over 60%. More importantly, once trained via transfer learning on the known classes, we show that our neural networks can be truncated and used as feature extractors for unsupervised clustering to automatically group together new unknown classes of glitches and anomalous signals. This novel capability is of paramount importance to identify and remove new types of glitches which will occur as the LIGO/Virgo detectors gradually attain design sensitivity.

Revisiting the Personal Transferable Skills Debate - an eLearning Pedagogical Perspective

DEFF Research Database (Denmark)

Gyamfi, Samuel Adu; Sørensen, Lene Tolstrup; Ryberg, Thomas

2011-01-01

where three broad approaches for developing PTS within the curriculum have been experimented with. To date, progress so far has been patchy. The paper is in two theoretical parts. The first part seeks to advance the theoretical framework of REALs as the better approach to teaching and learning in our......Personal Transferable Skills (PTS) are essential work skills which are not specific to any subject or profession, and which, though learned in one context may be successfully transferred to and applied in many other contexts. They are skills that enable people to acquire, structure, interpret...... universities. The second part of the paper argues that theoretically, communication theory (which draws on contemporary rhetorical theory) and social informatics theory provide important perspective for the application of eLearning based on REALs in the development of PTS for university graduates. The paper...

Pedagogy and Transference: Casting the Past of Learning into the Presence of Teaching.

Science.gov (United States)

Britzman, Deborah P.; Pitt, Alice J.

1996-01-01

Teaching must allow teachers to learn from students' learning. Anna Freud's approach emphasizes the psychoanalytical concept of transference. The paper describes the logic behind an undergraduate foundations of education course that examined whether study of the self studying education could create new conditions of learning and creating…

Social learning within and across species: information transfer in mouse-eared bats

DEFF Research Database (Denmark)

Clarin, T. M. A.; Borissov, I.; Page, R. A.

2014-01-01

of observation versus interaction in intraspecific social learning and by considering interspecific social learning in sympatric bat species. Observers learned from demonstrators to identify food sources using a light cue. We show that intraspecific social learning exists in the greater mouse-eared bat (Myotis......). Additionally, we opportunistically retested one individual that we recaptured from the wild 1 year after initial learning and found long-term memory of the trained association. Our study adds to the understanding of learning, information transfer, and long-term memory in wild-living animals....

Pneumatic transfer systems

International Nuclear Information System (INIS)

Bichler, H.; Boeck, H.; Hammer, J.; Buchtela, K.

1988-11-01

A pneumatic transfer system for research reactors, including a sample changer system and to be used for neutron activation analysis, is described. The system can be obtained commercially from the Atominstitut. 2 figs. (qui)

Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.

Science.gov (United States)

Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A; Wei, Jun; Cha, Kenny

2016-12-01

Develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) volume using a deep convolutional neural network (DCNN) with transfer learning from mammograms. A data set containing 2282 digitized film and digital mammograms and 324 DBT volumes were collected with IRB approval. The mass of interest on the images was marked by an experienced breast radiologist as reference standard. The data set was partitioned into a training set (2282 mammograms with 2461 masses and 230 DBT views with 228 masses) and an independent test set (94 DBT views with 89 masses). For DCNN training, the region of interest (ROI) containing the mass (true positive) was extracted from each image. False positive (FP) ROIs were identified at prescreening by their previously developed CAD systems. After data augmentation, a total of 45 072 mammographic ROIs and 37 450 DBT ROIs were obtained. Data normalization and reduction of non-uniformity in the ROIs across heterogeneous data was achieved using a background correction method applied to each ROI. A DCNN with four convolutional layers and three fully connected (FC) layers was first trained on the mammography data. Jittering and dropout techniques were used to reduce overfitting. After training with the mammographic ROIs, all weights in the first three convolutional layers were frozen, and only the last convolution layer and the FC layers were randomly initialized again and trained using the DBT training ROIs. The authors compared the performances of two CAD systems for mass detection in DBT: one used the DCNN-based approach and the other used their previously developed feature-based approach for FP reduction. The prescreening stage was identical in both systems, passing the same set of mass candidates to the FP reduction stage. For the feature-based CAD system, 3D clustering and active contour method was used for segmentation; morphological, gray level, and texture features were extracted and merged with a

Using E-Learning for Skills Transfer, Motivation and Retention of ...

African Journals Online (AJOL)

Using E-Learning for Skills Transfer, Motivation and Retention of Health Workers in Zambia. JK Chime, P Munyati, M Katepa-Bwalya, M Musumali, B Mweetwa, S Kagulura, JS Kachimba, B Vwalika, J Mufunda ...

The Influence of Supervisor's Transformational Leadership on Learning Culture and Learning Transfer of Nuclear R and D Personnel

International Nuclear Information System (INIS)

Min, Sang-Ki; Hwang, Hye-Seon; Jin, You-Rim; Lee, Eui-Jin; Lee, Soo-Jin

2017-01-01

Transformational leadership means that supervisors try to support the members individually, and encourage them to find new methods and approaches. In this study, it was identified empirically that a supervisor's transformational leadership has a strong influence on the learning culture and learning transfer of nuclear R and D personnel. To develop the competency of R and D personnel, not only formal education programs but also informal learning such as workplace learning have been carried out in the nuclear R and D organization. In this situation, transformational leadership has an effect on willingness and behavior of nuclear R and D personnel on the formal and informal learning. Therefore, transformational leadership is crucial factor in the human resource development system. The leadership required by them is not a one-sided order, but rather individual consideration, charisma, and intellectual stimulation for their nuclear R and D members. As a point of nuclear training and education, it is necessary to consider the operation of leadership programs that strengthen the transformational leadership of the project managers.

Hold design supports learning and transfer of climbing fluency

NARCIS (Netherlands)

Orth, Dominic; Davids, Keith; Seifert, Ludovic

2014-01-01

Being a discipline with a broad range of genres, rock climbing is an activity where participants seek to generalize the skills they learn in different performance contexts. A training strategy for achieving skill transfer was explored in a group of experienced climbers. Specifically, we tested the

Learning a Transferable Change Rule from a Recurrent Neural Network for Land Cover Change Detection

Directory of Open Access Journals (Sweden)

Haobo Lyu

2016-06-01

Full Text Available When exploited in remote sensing analysis, a reliable change rule with transfer ability can detect changes accurately and be applied widely. However, in practice, the complexity of land cover changes makes it difficult to use only one change rule or change feature learned from a given multi-temporal dataset to detect any other new target images without applying other learning processes. In this study, we consider the design of an efficient change rule having transferability to detect both binary and multi-class changes. The proposed method relies on an improved Long Short-Term Memory (LSTM model to acquire and record the change information of long-term sequence remote sensing data. In particular, a core memory cell is utilized to learn the change rule from the information concerning binary changes or multi-class changes. Three gates are utilized to control the input, output and update of the LSTM model for optimization. In addition, the learned rule can be applied to detect changes and transfer the change rule from one learned image to another new target multi-temporal image. In this study, binary experiments, transfer experiments and multi-class change experiments are exploited to demonstrate the superiority of our method. Three contributions of this work can be summarized as follows: (1 the proposed method can learn an effective change rule to provide reliable change information for multi-temporal images; (2 the learned change rule has good transferability for detecting changes in new target images without any extra learning process, and the new target images should have a multi-spectral distribution similar to that of the training images; and (3 to the authors’ best knowledge, this is the first time that deep learning in recurrent neural networks is exploited for change detection. In addition, under the framework of the proposed method, changes can be detected under both binary detection and multi-class change detection.

THE IMPACT OF TRUST ON KNOWLEDGE TRANSFER IN INTERNATIONAL BUSINESS SYSTEMS

Directory of Open Access Journals (Sweden)

Konstantinos P. ROTSIOS

2012-12-01

Full Text Available Over the last decade, international business alliances have emerged as one of the most important strategies for firms to expand in international markets. In addition, knowledge transfer has been determined as one of the key factors that lead to the creation of sustainable competitive advantage for firms and to the success of learning alliances. Furthermore, trust enhances the effectiveness of this process. The growing volume of published research in recent years has indubitably revealed the significant role of trust on knowledge transfer in International Business (IB Systems and in particular in International Strategic Alliances (ISAs and International Joint Ventures (IJVs. This paper consists of an in depth review of the most recent literature about the impact of trust on transfer of various types of knowledge in IB Systems with reference to the relevant theoretical models and the applications in the international context. The first section contains the theoretical background of the concept of trust, the different types of knowledge and the process of knowledge transfer. The main section refers to a few contemporary and distinguished scientific articles about the impact of trust as a determinant factor of knowledge transfer from the most recent international literature. The conclusions of the literature review and testable propositions related to the creation of trust among IJV partners and their impact on knowledge transfer are presented at the final section of the paper.

Named Entity Recognition for Novel Types by Transfer Learning

OpenAIRE

Qu, Lizhen; Ferraro, Gabriela; Zhou, Liyuan; Hou, Weiwei; Baldwin, Timothy

2016-01-01

In named entity recognition, we often don't have a large in-domain training corpus or a knowledge base with adequate coverage to train a model directly. In this paper, we propose a method where, given training data in a related domain with similar (but not identical) named entity (NE) types and a small amount of in-domain training data, we use transfer learning to learn a domain-specific NE model. That is, the novelty in the task setup is that we assume not just domain mismatch, but also labe...

In Light of Visual Arts – A knowledge transfer partnership project as experiential learning

Directory of Open Access Journals (Sweden)

Ming-hoi Lai

2013-10-01

Full Text Available Knowledge transfer between universities and the commercial sector is becoming more prevalent, and different processes have been adopted to facilitate the transfer of knowledge. The ‘In Light of Visual Arts’ project aimed to facilitate knowledge exchange in relation to an innovative concept, the ‘eco-philosophy of light’, between the lighting industry and the arts and cultural sector through an Informal Learning approach. Young visual artists, light designers and lighting technicians were encouraged to explore and exchange experiences in the areas of visual communication, art appreciation and art archiving to create practical lighting solutions. This project offers a feasible framework for the enhancement of artistic training through knowledge sharing, for the benefit of the participants themselves and, in turn, academia, industry and the community. Keywords: informal learning, experiential learning, knowledge transfer, art education, interdisciplinary study

Constraints on the Transfer of Perceptual Learning in Accented Speech

Science.gov (United States)

Eisner, Frank; Melinger, Alissa; Weber, Andrea

2013-01-01

The perception of speech sounds can be re-tuned through a mechanism of lexically driven perceptual learning after exposure to instances of atypical speech production. This study asked whether this re-tuning is sensitive to the position of the atypical sound within the word. We investigated perceptual learning using English voiced stop consonants, which are commonly devoiced in word-final position by Dutch learners of English. After exposure to a Dutch learner’s productions of devoiced stops in word-final position (but not in any other positions), British English (BE) listeners showed evidence of perceptual learning in a subsequent cross-modal priming task, where auditory primes with devoiced final stops (e.g., “seed”, pronounced [si:th]), facilitated recognition of visual targets with voiced final stops (e.g., SEED). In Experiment 1, this learning effect generalized to test pairs where the critical contrast was in word-initial position, e.g., auditory primes such as “town” facilitated recognition of visual targets like DOWN. Control listeners, who had not heard any stops by the speaker during exposure, showed no learning effects. The generalization to word-initial position did not occur when participants had also heard correctly voiced, word-initial stops during exposure (Experiment 2), and when the speaker was a native BE speaker who mimicked the word-final devoicing (Experiment 3). The readiness of the perceptual system to generalize a previously learned adjustment to other positions within the word thus appears to be modulated by distributional properties of the speech input, as well as by the perceived sociophonetic characteristics of the speaker. The results suggest that the transfer of pre-lexical perceptual adjustments that occur through lexically driven learning can be affected by a combination of acoustic, phonological, and sociophonetic factors. PMID:23554598

A study of the transferability of influenza case detection systems between two large healthcare systems.

Science.gov (United States)

Ye, Ye; Wagner, Michael M; Cooper, Gregory F; Ferraro, Jeffrey P; Su, Howard; Gesteland, Per H; Haug, Peter J; Millett, Nicholas E; Aronis, John M; Nowalk, Andrew J; Ruiz, Victor M; López Pineda, Arturo; Shi, Lingyun; Van Bree, Rudy; Ginter, Thomas; Tsui, Fuchiang

2017-01-01

This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases. A BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance. Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, pdetection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the accuracy of the NLP parser.

The CANDU 9 fuel transfer system

International Nuclear Information System (INIS)

Keszthelyi, Z.G.; Morikawa, D.T.

1996-01-01

The CANDU 9 fuel transfer system is based on the CANDU 6 and the Ontario Hydro Darlington NGD designs, modified to suit the CANDU 9 requirements. The CANDU 9 new fuel transfer system is very similar to the CANDU 6, with modifications to allow new fuel loading from outside containment, similar to Darlington. The CANDU 9 irradiated fuel transfer system is based on the Darlington irradiated fuel transfer system, with modifications to meet the more stringent containment requirements, improve performance, and match station layout. (author). 2 refs., 6 figs

The CANDU 9 fuel transfer system

Energy Technology Data Exchange (ETDEWEB)

Keszthelyi, Z G [Canadian General Electric Co. Ltd., Peterborough, ON (Canada); Morikawa, D T [Atomic Energy of Canada Ltd., Mississauga, ON (Canada)

1997-12-31

The CANDU 9 fuel transfer system is based on the CANDU 6 and the Ontario Hydro Darlington NGD designs, modified to suit the CANDU 9 requirements. The CANDU 9 new fuel transfer system is very similar to the CANDU 6, with modifications to allow new fuel loading from outside containment, similar to Darlington. The CANDU 9 irradiated fuel transfer system is based on the Darlington irradiated fuel transfer system, with modifications to meet the more stringent containment requirements, improve performance, and match station layout. (author). 2 refs., 6 figs.

Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club.

Science.gov (United States)

Chan, Tak-Wai

1996-01-01

Describes the development of learning companion systems and their contributions to the class of social learning systems that integrate artificial intelligence agents and use machine learning to tutor and interact with students. Outlines initial social learning projects, their programming languages, and weakness. Future improvements will include…

Orbital Express fluid transfer demonstration system

Science.gov (United States)

Rotenberger, Scott; SooHoo, David; Abraham, Gabriel

2008-04-01

Propellant resupply of orbiting spacecraft is no longer in the realm of high risk development. The recently concluded Orbital Express (OE) mission included a fluid transfer demonstration that operated the hardware and control logic in space, bringing the Technology Readiness Level to a solid TRL 7 (demonstration of a system prototype in an operational environment). Orbital Express (funded by the Defense Advanced Research Projects Agency, DARPA) was launched aboard an Atlas-V rocket on March 9th, 2007. The mission had the objective of demonstrating technologies needed for routine servicing of spacecraft, namely autonomous rendezvous and docking, propellant resupply, and orbital replacement unit transfer. The demonstration system used two spacecraft. A servicing vehicle (ASTRO) performed multiple dockings with the client (NextSat) spacecraft, and performed a variety of propellant transfers in addition to exchanges of a battery and computer. The fluid transfer and propulsion system onboard ASTRO, in addition to providing the six degree-of-freedom (6 DOF) thruster system for rendezvous and docking, demonstrated autonomous transfer of monopropellant hydrazine to or from the NextSat spacecraft 15 times while on orbit. The fluid transfer system aboard the NextSat vehicle was designed to simulate a variety of client systems, including both blowdown pressurization and pressure regulated propulsion systems. The fluid transfer demonstrations started with a low level of autonomy, where ground controllers were allowed to review the status of the demonstration at numerous points before authorizing the next steps to be performed. The final transfers were performed at a full autonomy level where the ground authorized the start of a transfer sequence and then monitored data as the transfer proceeded. The major steps of a fluid transfer included the following: mate of the coupling, leak check of the coupling, venting of the coupling, priming of the coupling, fluid transfer, gauging

TRANSFER PRICING AS A SYSTEM-FACTOR

Directory of Open Access Journals (Sweden)

L. M. Guisin

2011-01-01

Full Text Available It is proposed that transfer pricing plays a system-building role for multi-profile commercial banks of today. Bank transfer pricing system properties are outlined. Examples of practical implementation of the transfer pricing to bank activities are brought about. Impact of transferprices on key aspects of the bank management and control system is discussed.

Waste Feed Delivery Transfer System Analysis

Energy Technology Data Exchange (ETDEWEB)

JULYK, L.J.

2000-05-05

This document provides a documented basis for the required design pressure rating and pump pressure capacity of the Hanford Site waste-transfer system in support of the waste feed delivery to the privatization contractor for vitrification. The scope of the analysis includes the 200 East Area double-shell tank waste transfer pipeline system and the associated transfer system pumps for a11 Phase 1B and Phase 2 waste transfers from AN, AP, AW, AY, and A2 Tank Farms.

Waste Feed Delivery Transfer System Analysis

International Nuclear Information System (INIS)

JULYK, L.J.

2000-01-01

This document provides a documented basis for the required design pressure rating and pump pressure capacity of the Hanford Site waste-transfer system in support of the waste feed delivery to the privatization contractor for vitrification. The scope of the analysis includes the 200 East Area double-shell tank waste transfer pipeline system and the associated transfer system pumps for a11 Phase 1B and Phase 2 waste transfers from AN, AP, AW, AY, and A2 Tank Farms

Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

Science.gov (United States)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-02-01

We propose a cross-domain, multi-task transfer learning framework to transfer knowledge learned from non-medical images by a deep convolutional neural network (DCNN) to medical image recognition task while improving the generalization by multi-task learning of auxiliary tasks. A first stage cross-domain transfer learning was initiated from ImageNet trained DCNN to mammography trained DCNN. 19,632 regions-of-interest (ROI) from 2,454 mass lesions were collected from two imaging modalities: digitized-screen film mammography (SFM) and full-field digital mammography (DM), and split into training and test sets. In the multi-task transfer learning, the DCNN learned the mass classification task simultaneously from the training set of SFM and DM. The best transfer network for mammography was selected from three transfer networks with different number of convolutional layers frozen. The performance of single-task and multitask transfer learning on an independent SFM test set in terms of the area under the receiver operating characteristic curve (AUC) was 0.78+/-0.02 and 0.82+/-0.02, respectively. In the second stage cross-domain transfer learning, a set of 12,680 ROIs from 317 mass lesions on DBT were split into validation and independent test sets. We first studied the data requirements for the first stage mammography trained DCNN by varying the mammography training data from 1% to 100% and evaluated its learning on the DBT validation set in inference mode. We found that the entire available mammography set provided the best generalization. The DBT validation set was then used to train only the last four fully connected layers, resulting in an AUC of 0.90+/-0.04 on the independent DBT test set.

Casual Games and Casual Learning About Human Biological Systems

Science.gov (United States)

Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia

2016-02-01

Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human biological systems. Two hundred and forty-two children were given pretests at a Museum and posttests at home after playing either a treatment or control game. Also, 41 children were interviewed to explore deeper meanings behind the test results. Results show modest improvement in scientific attitudes, ability to identify human biological systems and in the children's ability to describe how those systems work together in real-world scenarios. Interviews reveal that children drew upon their prior school learning as they played the game. Also, on the surface they perceived the game as mainly entertainment but were easily able to discern learning outcomes when prompted. Implications for the design of casual games and how they can be used to enhance transfer of knowledge from the classroom to everyday life are discussed.

MOODLE XML TO IMS QTI ASSESSMENT TEST PORTABILITY ON LEARNING MANAGEMENT SYSTEM

OpenAIRE

Kautsar, Irwan Alnarus; Kubota, Shin-Ichiro; Musashi, Yasuo; Sugitani, Kenichi

2013-01-01

Learning Management Systems (i.e. LMS) is one of the most popular solutions towards the e-Learning objective in different universities all around the world, where this environments are used to not only deliver contents but to perform assessments, tests and other tasks related to learning. Although, there are popular LMS such as Moodle, and more developed, such as Chamilo, there is no assessment/test portability among their LMS. Each assessment export formats make difficult to transfer well do...

Teaching Personal and Social Responsibility and Transfer of Learning: Opportunities and Challenges for Teachers and Coaches

Science.gov (United States)

Gordon, Barrie; Doyle, Stephanie

2015-01-01

The transfer of learning from the gym to other areas of participants' lives has always been a core component of the Teaching Personal and Social Responsibility Model. The degree to which transfer of learning is successfully facilitated in the reality of Teaching Personal and Social Responsibility Model-based teaching and coaching is, however,…

Transferences of Purkinje systems

Directory of Open Access Journals (Sweden)

W. F. Harris

2011-12-01

Full Text Available The transferences of heterocentric astigmatic Purkinje systems are special: submatrices B and C, that is, the disjugacy and the divergence of the system, are symmetric and submatrix D (the divarication is the transpose of submatrix A (the dilation.  It is the primary purpose of this paper to provide a proof.  The paper also derives other relationships among the fundamental properties and compact expressions for the transference and optical axis locator of a Purkinje system. (S Afr Optom 2011 70(2 57-60

Prediction for flow boiling heat transfer in small diameter tube using deep learning

International Nuclear Information System (INIS)

Enoki, Koji; Sei, Yuichi; Okawa, Tomio; Saito, Kiyoshi

2017-01-01

The applications of Artificial Intelligence ie AI show diversity in any fields. On the other hand, research of the predicting heat transfer regardless of single-phase or two-phase flow is still untouched. Therefore, we have confirmed usefulness using AI's deep learning function on horizontal flow boiling heat transfer in flowing mini-channel that is actively researched. The effect of the surface tension in the mini-channel is large compared with conventional large tubes, and then the heat transfer mechanism is very complicated. For this reason, the numerical correlations of many existing researchers the prediction result is not good. However, the mechanistic correlation based on the visualization experiment, which the authors' research group published several years ago has very high precision. Therefore, in this research paper, we confirmed the effectiveness of using deep learning for predicting of the boiling heat transfer in mini-channel while comparing our correlation. (author)

Toddlers' word learning and transfer from electronic and print books.

Science.gov (United States)

Strouse, Gabrielle A; Ganea, Patricia A

2017-04-01

Transfer from symbolic media to the real world can be difficult for young children. A sample of 73 toddlers aged 17 to 23months were read either an electronic book displayed on a touchscreen device or a traditional print book in which a novel object was paired with a novel label. Toddlers in both conditions learned the label within the context of the book. However, only those who read the traditional format book generalized and transferred the label to other contexts. An older group of 28 toddlers aged 24 to 30months did generalize and transfer from the electronic book. Across ages, those children who primarily used screens to watch prerecorded video at home transferred less from the electronic book than those with more diverse home media experiences. Copyright © 2016 Elsevier Inc. All rights reserved.

The Analysis of Interactivity in a Teaching and Learning Sequence of Rugby: The Transfer of Control and Learning Responsibility

Science.gov (United States)

Llobet-Martí, Bernat; López-Ros, Víctor; Vila, Ignasi

2018-01-01

Background: The social constructivist perspective emphasises that learning is a process of self-construction of knowledge in a social context. Game-centred approaches, such as teaching games for understanding, have been used in accordance with this perspective. The process of transferring learning responsibility takes place when the learner is…

Saturn facility oil transfer automation system

Energy Technology Data Exchange (ETDEWEB)

Joseph, Nathan R.; Thomas, Rayburn Dean; Lewis, Barbara Ann; Malagon, Hector Ricardo.

2014-02-01

The Saturn accelerator, owned by Sandia National Laboratories, has been in operation since the early 1980s and still has many of the original systems. A critical legacy system is the oil transfer system which transfers 250,000 gallons of transformer oil from outside storage tanks to the Saturn facility. The oil transfer system was iden- ti ed for upgrade to current technology standards. Using the existing valves, pumps, and relay controls, the system was automated using the National Instruments cRIO FGPA platform. Engineered safety practices, including a failure mode e ects analysis, were used to develop error handling requirements. The uniqueness of the Saturn Oil Automated Transfer System (SOATS) is in the graphical user interface. The SOATS uses an HTML interface to communicate to the cRIO, creating a platform independent control system. The SOATS was commissioned in April 2013.

Ship Detection Using Transfer Learned Single Shot Multi Box Detector

Directory of Open Access Journals (Sweden)

Nie Gu-Hong

2017-01-01

Full Text Available Ship detection in satellite images is a challenging task. In this paper, we introduce a transfer learned Single Shot MultiBox Detector (SSD for ship detection. To this end, a state-of-the-art object detection model pre-trained from a large number of natural images was transfer learned for ship detection with limited labeled satellite images. To the best of our knowledge, this could be one of the first studies which introduce SSD into ship detection on satellite images. Experiments demonstrated that our method could achieve 87.9% AP at 47 FPS using NVIDIA TITAN X. In comparison with Faster R-CNN, 6.7% AP improvement could be achieved. Effects of the observation resolution has also been studied with the changing input sizes among 300 × 300, 600 × 600 and 900 × 900. It has been noted that the detection accuracy declined sharply with the decreasing resolution that is mainly caused by the missing small ships.

First-Year Mathematics and Its Application to Science: Evidence of Transfer of Learning to Physics and Engineering

Science.gov (United States)

Nakakoji, Yoshitaka; Wilson, Rachel

2018-01-01

Transfer of mathematical learning to science is seen as critical to the development of education and industrial societies, yet it is rarely interrogated in applied research. We present here research looking for evidence of transfer from university mathematics learning in semester one to second semester sciences/engineering courses (n = 1125). A…

Transfer function analysis of radiographic imaging systems

International Nuclear Information System (INIS)

Metz, C.E.; Doi, K.

1979-01-01

The theoretical and experimental aspects of the techniques of transfer function analysis used in radiographic imaging systems are reviewed. The mathematical principles of transfer function analysis are developed for linear, shift-invariant imaging systems, for the relation between object and image and for the image due to a sinusoidal plane wave object. The other basic mathematical principle discussed is 'Fourier analysis' and its application to an input function. Other aspects of transfer function analysis included are alternative expressions for the 'optical transfer function' of imaging systems and expressions are derived for both serial and parallel transfer image sub-systems. The applications of transfer function analysis to radiographic imaging systems are discussed in relation to the linearisation of the radiographic imaging system, the object, the geometrical unsharpness, the screen-film system unsharpness, other unsharpness effects and finally noise analysis. It is concluded that extensive theoretical, computer simulation and experimental studies have demonstrated that the techniques of transfer function analysis provide an accurate and reliable means for predicting and understanding the effects of various radiographic imaging system components in most practical diagnostic medical imaging situations. (U.K.)

ASSEMBLY TRANSFER SYSTEM DESCRIPTION DOCUMENT

International Nuclear Information System (INIS)

Gorpani, B.

2000-01-01

The Assembly Transfer System (ATS) receives, cools, and opens rail and truck transportation casks from the Carrier/Cask Handling System (CCHS). The system unloads transportation casks consisting of bare Spent Nuclear Fuel (SNF) assemblies, single element canisters, and Dual Purpose Canisters (DPCs). For casks containing DPCs, the system opens the DPCs and unloads the SNF. The system stages the assemblies, transfer assemblies to and from fuel-blending inventory pools, loads them into Disposal Containers (DCs), temporarily seals and inerts the DC, decontaminates the DC and transfers it to the Disposal Container Handling System. The system also prepares empty casks and DPCs for off-site shipment. Two identical Assembly Transfer System lines are provided in the Waste Handling Building (WHB). Each line operates independently to handle the waste transfer throughput and to support maintenance operations. Each system line primarily consists of wet and dry handling areas. The wet handling area includes a cask transport system, cask and DPC preparation system, and a wet assembly handling system. The basket transport system forms the transition between the wet and dry handling areas. The dry handling area includes the dry assembly handling system, assembly drying system, DC preparation system, and DC transport system. Both the wet and dry handling areas are controlled by the control and tracking system. The system operating sequence begins with moving transportation casks to the cask preparation area. The cask preparation operations consist of cask cavity gas sampling, cask venting, cask cool-down, outer lid removal, and inner shield plug lifting fixture attachment. Casks containing bare SNF (no DPC) are filled with water and placed in the cask unloading pool. The inner shield plugs are removed underwater. For casks containing a DPC, the cask lid(s) is removed, and the DPC is penetrated, sampled, vented, and cooled. A DPC lifting fixture is attached and the cask is placed

Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

Directory of Open Access Journals (Sweden)

HU Gensheng

2018-03-01

Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

Science.gov (United States)

Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

2016-07-01

Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

The role of emotion in the learning and transfer of clinical skills and knowledge.

Science.gov (United States)

McConnell, Meghan M; Eva, Kevin W

2012-10-01

Medical school and residency are emotional experiences for trainees. Most research examining emotion in medicine has focused on negative moods associated with physician burnout and poor quality of life. However, positive emotional states also may have important influences on student learning and performance. The authors present a review of the literature on the influence of emotion on cognition, specifically how individuals learn complex skills and knowledge and how they transfer that information to new scenarios. From September 2011 to February 2012, the authors searched Medline, PsycInfo, GoogleScholar, ERIC, and Web of Science, as well as the reference lists of relevant articles, for research on the interaction between emotion, learning, and knowledge transfer. They extracted representative themes and noted particularly relevant empirical findings. The authors found articles that show that emotion influences various cognitive processes that are involved in the acquisition and transfer of knowledge and skills. More specifically, emotion influences how individuals identify and perceive information, how they interpret it, and how they act on the information available in learning and practice situations. There are many ways in which emotions may influence medical education. Researchers must further explore the implications of these findings to ensure that learning is not treated simply as a rational, mechanistic process but that trainees are effectively prepared to perform under a wide range of emotional conditions.

Indirect Measures of Learning Transfer between Real and Virtual Environments

Science.gov (United States)

Garrett, Michael; McMahon, Mark

2013-01-01

This paper reports on research undertaken to determine the effectiveness of a 3D simulation environment used to train mining personnel in emergency evacuation procedures, designated the Fires in Underground Mines Evacuation Simulator (FUMES). Owing to the operational constraints of the mining facility, methods for measuring learning transfer were…

Making Learning Meaningful: Facilitating Interest Development and Transfer in At-Risk College Students

Science.gov (United States)

Heddy, Benjamin C.; Sinatra, Gale M.; Seli, Helena; Taasoobshirazi, Gita; Mukhopadhyay, Ananya

2017-01-01

The Teaching for Transformative Experience in Science (TTES) model has shown to be a useful tool to generate learning and engagement in science. We investigated the effectiveness of TTES for facilitating transformative experience (TE), learning, the development of topic interest and transfer of course concepts to other courses employing a…

Knowledge transfer isn’t simply transfer

DEFF Research Database (Denmark)

Dao, Li; Napier, Nancy

2012-01-01

This paper examines micro dynamic aspects of knowledge sharing and learning in international joint venture settings. Learning of expatriate and local managers appears far more complex and mutually dependent than conventionally speculated in existing literature. The paper proposes that the effect ...... Danish and Vietnamese firms. The paper suggests that learning in IJVs, even in the context of one-way knowledge transfer from the foreign parent, should be managed in a mutual perspective and with thoughtful coordination of individual learning....... and outcome of knowledge transfer from joint venture parents and learning in IJVs are dependent on how individual managers (including both expatriate and local) learn, perceive their learning roles, and enact a learning agenda. Empirical evidence is drawn from two cases of international joint ventures between...

A study of the transferability of influenza case detection systems between two large healthcare systems.

Directory of Open Access Journals (Sweden)

Ye Ye

Full Text Available This study evaluates the accuracy and transferability of Bayesian case detection systems (BCD that use clinical notes from emergency department (ED to detect influenza cases.A BCD uses natural language processing (NLP to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN to infer patients' diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC and Intermountain Healthcare in Utah (BCDIH. At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source institution, development parser, application (target institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance.Both BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92. When tested for transferability using the other institution's cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p<0.01, and BCDIH discriminations declined more (from 0.93 to 0.87, p<0.0001. We attributed the BCDIH decline to the lower recall of the IH parser on UPMC notes. The ANOVA analysis showed five significant factors: development parser, application institution, application parser, BN transfer, and classification task.We demonstrated high influenza case detection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the

On-campus or online: examining self-regulation and cognitive transfer skills in different learning settings

Directory of Open Access Journals (Sweden)

Miri Barak

2016-11-01

Full Text Available Abstract This study was set to identify self-regulation skills required for online learning and to characterize cognitive transfer of on-campus and online students. The study included two groups of undergraduate students who studied the same course, but in different settings: online and on-campus. Data collected via an online survey and semi-structured interviews indicated that cognitive strategies and regulation of cognition are significant for successful online learning. Findings also indicated that the online students were more aware of mastery learning and information processing strategies than the on-campus peers. The online students specified the importance of planning, controlling, and evaluation skills for meaningful learning; whereas the on-campus students asserted lack of self-discipline and limited communication skills as barriers for distance learning. Near- and far-transfer components were identified, showing a significant positive correlation with self-regulation skills for both groups of learners.

Informed Systems: Enabling Collaborative Evidence Based Organizational Learning

Directory of Open Access Journals (Sweden)

Mary M. Somerville

2015-12-01

Full Text Available Objective – In response to unrelenting disruptions in academic publishing and higher education ecosystems, the Informed Systems approach supports evidence based professional activities to make decisions and take actions. This conceptual paper presents two core models, Informed Systems Leadership Model and Collaborative Evidence-Based Information Process Model, whereby co-workers learn to make informed decisions by identifying the decisions to be made and the information required for those decisions. This is accomplished through collaborative design and iterative evaluation of workplace systems, relationships, and practices. Over time, increasingly effective and efficient structures and processes for using information to learn further organizational renewal and advance nimble responsiveness amidst dynamically changing circumstances. Methods – The integrated Informed Systems approach to fostering persistent workplace inquiry has its genesis in three theories that together activate and enable robust information usage and organizational learning. The information- and learning-intensive theories of Peter Checkland in England, which advance systems design, stimulate participants’ appreciation during the design process of the potential for using information to learn. Within a co-designed environment, intentional social practices continue workplace learning, described by Christine Bruce in Australia as informed learning enacted through information experiences. In addition, in Japan, Ikujiro Nonaka’s theories foster information exchange processes and knowledge creation activities within and across organizational units. In combination, these theories promote the kind of learning made possible through evolving and transferable capacity to use information to learn through design and usage of collaborative communication systems with associated professional practices. Informed Systems therein draws from three antecedent theories to create an original

CURRENT TRANSFER SYSTEMS

Science.gov (United States)

Watt, D.A.

1956-07-01

A current transfer system is described for transferring current between a rotating member and a co-axial stationary member. The particular area of application for the invention is in connection with homopolar generators where a low voltage and high current are generated. The current tramsfer system of the invention comprises a rotor member and a co-axial stator member wherein one of the members is shaped to provide a circumferential surface concave in section and the other member is shaped to have a peripheral portion in close proximity to the surface, whereby a liquid metal can be stably supported between the two members when they are moving relative to one another to establish an electrical conducting path between the members.

Dry Transfer Systems for Used Nuclear Fuel

Energy Technology Data Exchange (ETDEWEB)

Brett W. Carlsen; Michaele BradyRaap

2012-05-01

The potential need for a dry transfer system (DTS) to enable retrieval of used nuclear fuel (UNF) for inspection or repackaging will increase as the duration and quantity of fuel in dry storage increases. This report explores the uses for a DTS, identifies associated general functional requirements, and reviews existing and proposed systems that currently perform dry fuel transfers. The focus of this paper is on the need for a DTS to enable transfer of bare fuel assemblies. Dry transfer systems for UNF canisters are currently available and in use for transferring loaded canisters between the drying station and storage and transportation casks.

Improving accuracy and power with transfer learning using a meta-analytic database.

Science.gov (United States)

Schwartz, Yannick; Varoquaux, Gaël; Pallier, Christophe; Pinel, Philippe; Poline, Jean-Baptiste; Thirion, Bertrand

2012-01-01

Typical cohorts in brain imaging studies are not large enough for systematic testing of all the information contained in the images. To build testable working hypotheses, investigators thus rely on analysis of previous work, sometimes formalized in a so-called meta-analysis. In brain imaging, this approach underlies the specification of regions of interest (ROIs) that are usually selected on the basis of the coordinates of previously detected effects. In this paper, we propose to use a database of images, rather than coordinates, and frame the problem as transfer learning: learning a discriminant model on a reference task to apply it to a different but related new task. To facilitate statistical analysis of small cohorts, we use a sparse discriminant model that selects predictive voxels on the reference task and thus provides a principled procedure to define ROIs. The benefits of our approach are twofold. First it uses the reference database for prediction, i.e., to provide potential biomarkers in a clinical setting. Second it increases statistical power on the new task. We demonstrate on a set of 18 pairs of functional MRI experimental conditions that our approach gives good prediction. In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts.

Interorganizational learning systems

DEFF Research Database (Denmark)

Hjalager, Anne-Mette

1999-01-01

The occurrence of organizational and interorganizational learning processes is not only the result of management endeavors. Industry structures and market related issues have substantial spill-over effects. The article reviews literature, and it establishes a learning model in which elements from...... organizational environments are included into a systematic conceptual framework. The model allows four types of learning to be identified: P-learning (professional/craft systems learning), T-learning (technology embedded learning), D-learning (dualistic learning systems, where part of the labor force is exclude...... from learning), and S-learning (learning in social networks or clans). The situation related to service industries illustrates the typology....

Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

Science.gov (United States)

Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

2018-01-01

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.

A method for medulloblastoma tumor differentiation based on convolutional neural networks and transfer learning

Science.gov (United States)

Cruz-Roa, Angel; Arévalo, John; Judkins, Alexander; Madabhushi, Anant; González, Fabio

2015-12-01

Convolutional neural networks (CNN) have been very successful at addressing different computer vision tasks thanks to their ability to learn image representations directly from large amounts of labeled data. Features learned from a dataset can be used to represent images from a different dataset via an approach called transfer learning. In this paper we apply transfer learning to the challenging task of medulloblastoma tumor differentiation. We compare two different CNN models which were previously trained in two different domains (natural and histopathology images). The first CNN is a state-of-the-art approach in computer vision, a large and deep CNN with 16-layers, Visual Geometry Group (VGG) CNN. The second (IBCa-CNN) is a 2-layer CNN trained for invasive breast cancer tumor classification. Both CNNs are used as visual feature extractors of histopathology image regions of anaplastic and non-anaplastic medulloblastoma tumor from digitized whole-slide images. The features from the two models are used, separately, to train a softmax classifier to discriminate between anaplastic and non-anaplastic medulloblastoma image regions. Experimental results show that the transfer learning approach produce competitive results in comparison with the state of the art approaches for IBCa detection. Results also show that features extracted from the IBCa-CNN have better performance in comparison with features extracted from the VGG-CNN. The former obtains 89.8% while the latter obtains 76.6% in terms of average accuracy.

Improving Students' Transfer of Learning among Subject Areas through the Use of an Integrated Curriculum and Alternative Assessment.

Science.gov (United States)

Boidy, Tish; Moran, Michelle

An intervention program sought to improve third- and fifth- grade students' ability to transfer learning among subject areas and to apply their learning to everyday occurrences. Surveys and interviews revealed the lack of student transference of knowledge among subject areas; teacher surveys and an interview with the curriculum director provided…

Transfer of learning in binary decision making problems.

OpenAIRE

Robotti, O. P.

2007-01-01

Transfer, the use of acquired knowledge, skills and abilities across tasks and contexts, is a key and elusive goal of learning. Most evidence available in literature is based on a limited number of tasks, predominantly open-ended problems, game-like problems and taught school subjects (e.g. maths, physics, algebra). It is not obvious that findings from this work can be extended to the domain of decision making problems. This thesis, which aims to broaden the understanding of enhancing and lim...

Touchscreen Facilitates Young Children’s Transfer of Learning to Tell Time

Directory of Open Access Journals (Sweden)

Fuxing Wang

2016-11-01

Full Text Available Young children are devoting increasing time to playing on handheld touchscreen devices (e.g., iPads. Though thousands of touchscreen apps are claimed to be educational, there is a lack of sufficient evidence examining the impact of touchscreens on children’s learning outcomes. In the present study, the two questions we focused on were (a whether using a touchscreen was helpful in teaching children to tell time, and (b to what extent young children could transfer what they had learned on the touchscreen to other media. A pre- and posttest design was adopted. After learning to read the time on the iPad touchscreen for 10 minutes, three groups of 5- to 6-year-old children (N = 65 were respectively tested with an iPad touchscreen, a toy clock or a drawing of a clock on paper. The results revealed that posttest scores in the iPad touchscreen test group were significantly higher than those at pretest, indicating that the touchscreen itself could provide support for young children’s learning. Similarly, regardless of being tested with a toy clock or paper drawing, children’s posttest performance was also better than pretest, suggesting that children could transfer what they had learned on an iPad touchscreen to other media. However, comparison among groups showed that children tested with the paper drawing underperformed those tested with the other two media. The theoretical and practical implications of the results, as well as limitations of the present study, are discussed.

Design Criteria for Bagless Transfer System (BTS) Packaging System

International Nuclear Information System (INIS)

RISENMAY, H.R.

2000-01-01

This document provides the criteria for the design and installation of a Bagless Transfer System (BTS); Blend, Sieve and Balance Equipment; and Supercritical Fluid Extraction System (SFE). The project consists of 3 major modules: (1) Bagless Transfer System (BTS) Module; (2) Blend, Sieve and Balance Equipment; and (3) Supercritical Fluid Extraction (SFE) Module

Learning Electrical Circuits: The Effects of the 4C-ID Instructional Approach in the Acquisition and Transfer of Knowledge

Directory of Open Access Journals (Sweden)

Mario Melo

2015-07-01

Full Text Available This study was designed to investigate the effects of two instructional approaches (4C-ID versus conventional on learners’ knowledge-acquisition and learning transfer of the electrical circuits content in Physics. Participants were 129 9th graders from a secondary school in Lisbon, M = 14.3 years, SD = 0.54. The participants were divided in two groups: an experimental group constituted three intact classes (n = 78; and a control group constituted two intact classes (n = 51. The experimental group was taught using a digital learning environment designed with the 4C-ID model principles while the control group learned the same contents through a conventional method. We assessed the students’ performance (knowledge-acquisition and transfer, the perceived cognitive load, and the instructional efficiency. Results indicated that the experimental group performed significantly better than the control group on a knowledge-acquisition test and in a learning transfer test. They also perceived a less cognitive load in the transfer test and the learning environment developed with the 4C-ID model proved to be more instructional efficient than the conventional method.

Effects of creating video-based modeling examples on learning and transfer

NARCIS (Netherlands)

Hoogerheide, Vincent; Loyens, Sofie M M; van Gog, Tamara

2014-01-01

Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study

LESSONS LEARNED IN OPERATING THE HOSE-IN-HOSE SYSTEM FOR TRANSFSERRING SLUDGE AT HANFORD'S K BASINS

International Nuclear Information System (INIS)

PERES MW

2008-01-01

In May 2007, the Department of Energy and the Fluor Hanford K Basin Closure Project completed transferring sludge from the K East Basin to new containers in the K West Basin using a Hose-in-Hose system. This project presented a number of complex and unique technical, operational, and management challenges that had to be resolved to complete the required transfers and satisfy project milestones. The project team (including DOE; regulators; and Fluor management, operations, maintenance, engineering and all other support organizations) found innovative solutions to each challenge. This paper records lessons learned during the operational phase of the sludge transfer via the Hose-In-Hose system. The subject is limited to the operational phase and does not cover design, development, testing or turnover. A discussion of the situation or problem encountered is provided, along with the lesson learned as applicable to a future program or project

Folding Membrane Proteins by Deep Transfer Learning

KAUST Repository

Wang, Sheng

2017-08-29

Computational elucidation of membrane protein (MP) structures is challenging partially due to lack of sufficient solved structures for homology modeling. Here, we describe a high-throughput deep transfer learning method that first predicts MP contacts by learning from non-MPs and then predicts 3D structure models using the predicted contacts as distance restraints. Tested on 510 non-redundant MPs, our method has contact prediction accuracy at least 0.18 better than existing methods, predicts correct folds for 218 MPs, and generates 3D models with root-mean-square deviation (RMSD) less than 4 and 5 Å for 57 and 108 MPs, respectively. A rigorous blind test in the continuous automated model evaluation project shows that our method predicted high-resolution 3D models for two recent test MPs of 210 residues with RMSD ∼2 Å. We estimated that our method could predict correct folds for 1,345–1,871 reviewed human multi-pass MPs including a few hundred new folds, which shall facilitate the discovery of drugs targeting at MPs.

LEARNING FROM PARTICIPATION IN CREATIVE ACTVITIES TRANSFERRED T0 EVERYDAY LIFE

DEFF Research Database (Denmark)

Hansen, Bodil Winther; Pedersen, Helle Andrea

Creative activities have traditionally been used in psychiatric occupational therapy. However, there is a lack of research on how creative activities influence everyday life; especially with a learning perspective. The aim of the study is to develop and qualify the use of creative activities...... offer a learning perspective on developing and qualifying the use of creative activities.Application to Practice:Implementing the use of creative activities has a potential to qualify and expand occupational therapy rehabilitation regarding coping with everyday life.References:(1) Wahlgren, B. & Aarkrog......, V. (2012) Transfer, Aarhus: Aarhus Universitetsforlag.(2) Brinkmann, S. & Kvale, S. (2015) InterViews – Learning the Craft of Qualitative Research Interviewing (Third Edition), Los Angeles, Sage Publication. Inc.Financially supported by the Danish Federation of Occupational Therapy, the Metropolitan...

Ichthyoplankton Classification Tool using Generative Adversarial Networks and Transfer Learning

KAUST Repository

Aljaafari, Nura

2018-04-15

The study and the analysis of marine ecosystems is a significant part of the marine science research. These systems are valuable resources for fisheries, improving water quality and can even be used in drugs production. The investigation of ichthyoplankton inhabiting these ecosystems is also an important research field. Ichthyoplankton are fish in their early stages of life. In this stage, the fish have relatively similar shape and are small in size. The currently used way of identifying them is not optimal. Marine scientists typically study such organisms by sending a team that collects samples from the sea which is then taken to the lab for further investigation. These samples need to be studied by an expert and usually end needing a DNA sequencing. This method is time-consuming and requires a high level of experience. The recent advances in AI have helped to solve and automate several difficult tasks which motivated us to develop a classification tool for ichthyoplankton. We show that using machine learning techniques, such as generative adversarial networks combined with transfer learning solves such a problem with high accuracy. We show that using traditional machine learning algorithms fails to solve it. We also give a general framework for creating a classification tool when the dataset used for training is a limited dataset. We aim to build a user-friendly tool that can be used by any user for the classification task and we aim to give a guide to the researchers so that they can follow in creating a classification tool.

Match properties of heat transfer and coupled heat and mass transfer processes in air-conditioning system

International Nuclear Information System (INIS)

Zhang Tao; Liu Xiaohua; Zhang Lun; Jiang Yi

2012-01-01

Highlights: ► Investigates match properties of heat or mass transfer processes in HVAC system. ► Losses are caused by limited transfer ability, flow and parameter mismatching. ► Condition of flow matching is the same heat capacity of the fluids. ► Parameter matching is only reached along the saturation line in air–water system. ► Analytical solutions of heat and mass transfer resistance are derived. - Abstract: Sensible heat exchangers and coupled heat and mass transfer devices between humid air and water/desiccant are commonly used devices in air-conditioning systems. This paper focuses on the match properties of sensible heat transfer processes and coupled heat and mass transfer processes in an effort to understand the reasons for performance limitations in order to optimize system performance. Limited heat transfer capability and flow mismatching resulted in heat resistance of the sensible heat transfer process. Losses occurred during the heat and mass transfer processes due to limited transfer capability, flow mismatching, and parameter mismatching. Flow matching was achieved when the heat capacities of the fluids were identical, and parameter matching could only be reached along the saturation line in air–water systems or the iso-concentration line in air–desiccant systems. Analytical solutions of heat transfer resistance and mass transfer resistance were then derived. The heat and mass transfer process close to the saturation line is recommended, and heating sprayed water resulted in better humidification performance than heating inlet air in the air humidifier.

The Transfer of Learning Associated with Audio Feedback on Written Work

Science.gov (United States)

Martini, Tanya; DiBattista, David

2014-01-01

This study examined whether audio feedback provided to undergraduates (N=51) about one paper would prove beneficial in terms of improving their grades on another, unrelated paper of the same type. We examined this issue both in terms of student "beliefs" about learning transfer, as well as their "actual ability" to transfer…

Social software: E-learning beyond learning management systems

DEFF Research Database (Denmark)

Dalsgaard, Christian

2006-01-01

The article argues that it is necessary to move e-learning beyond learning management systems and engage students in an active use of the web as a resource for their self-governed, problem-based and collaborative activities. The purpose of the article is to discuss the potential of social software...... to move e-learning beyond learning management systems. An approach to use of social software in support of a social constructivist approach to e-learning is presented, and it is argued that learning management systems do not support a social constructivist approach which emphasizes self-governed learning...... activities of students. The article suggests a limitation of the use of learning management systems to cover only administrative issues. Further, it is argued that students' self-governed learning processes are supported by providing students with personal tools and engaging them in different kinds of social...

On knowledge transfer management as a learning process for ad hoc teams

Science.gov (United States)

Iliescu, D.

2017-08-01

Knowledge management represents an emerging domain becoming more and more important. Concepts like knowledge codification and personalisation, knowledge life-cycle, social and technological dimensions, knowledge transfer and learning management are integral parts. Focus goes here in the process of knowledge transfer for the case of ad hoc teams. The social dimension of knowledge transfer plays an important role. No single individual actors involved in the process, but a collective one, representing the organisation. It is critically important for knowledge to be managed from the life-cycle point of view. A complex communication network needs to be in place to supports the process of knowledge transfer. Two particular concepts, the bridge tie and transactive memory, would eventually enhance the communication. The paper focuses on an informational communication platform supporting the collaborative work on knowledge transfer. The platform facilitates the creation of a topic language to be used in knowledge modelling, storage and reuse, by the ad hoc teams.

Differences in perceptual learning transfer as a function of training task.

Science.gov (United States)

Green, C Shawn; Kattner, Florian; Siegel, Max H; Kersten, Daniel; Schrater, Paul R

2015-01-01

A growing body of research--including results from behavioral psychology, human structural and functional imaging, single-cell recordings in nonhuman primates, and computational modeling--suggests that perceptual learning effects are best understood as a change in the ability of higher-level integration or association areas to read out sensory information in the service of particular decisions. Work in this vein has argued that, depending on the training experience, the "rules" for this read-out can either be applicable to new contexts (thus engendering learning generalization) or can apply only to the exact training context (thus resulting in learning specificity). Here we contrast learning tasks designed to promote either stimulus-specific or stimulus-general rules. Specifically, we compare learning transfer across visual orientation following training on three different tasks: an orientation categorization task (which permits an orientation-specific learning solution), an orientation estimation task (which requires an orientation-general learning solution), and an orientation categorization task in which the relevant category boundary shifts on every trial (which lies somewhere between the two tasks above). While the simple orientation-categorization training task resulted in orientation-specific learning, the estimation and moving categorization tasks resulted in significant orientation learning generalization. The general framework tested here--that task specificity or generality can be predicted via an examination of the optimal learning solution--may be useful in building future training paradigms with certain desired outcomes.

TRANSFER RESERVOIR AS A RAINWATER DRAINAGE SYSTEM

Directory of Open Access Journals (Sweden)

Robert Malmur

2016-06-01

Full Text Available Intensive rainfalls and snow melting often cause floods in protected areas and overflow the existing sewage systems. Such cases are particularly burdensome for the inhabitants and cause considerable physical losses. One of the possible constructional solutions to ensure the effective outflow of stormwater are transfer reservoirs located between the draining system and a receiver set discussed in this paper. If gravity outflow of sewage is impossible, the initial part of sewage volume is accumulated in the transfer reservoir and then it is transferred into the water receiver set. However, gravity discharge of sewage to the water receiver set occurs through transfer chambers in the transfer reservoir.

New designing of E-Learning systems with using network learning

OpenAIRE

Malayeri, Amin Daneshmand; Abdollahi, Jalal

2010-01-01

One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new methodology of E-Learning systems entitle "Network Learning" with review of another aspects of E-Learning systems. Also, we present benefits and advantages of using these systems in educating and fast learning programs. Network Learning can be programmable...

Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges

Directory of Open Access Journals (Sweden)

Rodolfo S. Simões

2018-02-01

Full Text Available Medicinal chemistry projects involve some steps aiming to develop a new drug, such as the analysis of biological targets related to a given disease, the discovery and the development of drug candidates for these targets, performing parallel biological tests to validate the drug effectiveness and side effects. Approaches as quantitative study of activity-structure relationships (QSAR involve the construction of predictive models that relate a set of descriptors of a chemical compound series and its biological activities with respect to one or more targets in the human body. Datasets used to perform QSAR analyses are generally characterized by a small number of samples and this makes them more complex to build accurate predictive models. In this context, transfer and multi-task learning techniques are very suitable since they take information from other QSAR models to the same biological target, reducing efforts and costs for generating new chemical compounds. Therefore, this review will present the main features of transfer and multi-task learning studies, as well as some applications and its potentiality in drug design projects.

Modelling Digital Knowledge Transfer: Nurse Supervisors Transforming Learning at Point of Care to Advance Nursing Practice

Directory of Open Access Journals (Sweden)

Carey Mather

2017-05-01

Full Text Available Limited adoption of mobile technology for informal learning and continuing professional development within Australian healthcare environments has been explained primarily as an issue of insufficient digital and ehealth literacy of healthcare professionals. This study explores nurse supervisors’ use of mobile technology for informal learning and continuing professional development both for their own professional practice, and in their role in modelling digital knowledge transfer, by facilitating the learning and teaching of nursing students in the workplace. A convenience sample of 27 nurse supervisors involved with guiding and supporting undergraduate nurses participated in one of six focus groups held in two states of Australia. Expanding knowledge emerged as the key theme of importance to this group of clinicians. Although nurse supervisors regularly browsed Internet sources for learning and teaching purposes, a mixed understanding of the mobile learning activities that could be included as informal learning or part of formal continuing professional development was detected. Participants need educational preparation and access to mobile learning opportunities to improve and maintain their digital and ehealth literacy to appropriately model digital professionalism with students. Implementation of mobile learning at point of care to enable digital knowledge transfer, augment informal learning for students and patients, and support continuing professional development opportunities is necessary. Embedding digital and ehealth literacy within nursing curricula will promote mobile learning as a legitimate nursing function and advance nursing practice.

The Transfer of Learning from Play Practices to Game Play in Young Adult Soccer Players

Science.gov (United States)

Holt, Josh E.; Ward, Phillip; Wallhead, Tristan L.

2006-01-01

Background: Physical educators and coaches face an ongoing problem of presenting fun and enjoyable practices that also provide efficient learning of technical and tactical sports skills. Effective instruction also promotes the transfer of learning from practice tasks to the real game. Play Practice (PP) describes a structure for teaching sports…

Visual prosthesis wireless energy transfer system optimal modeling.

Science.gov (United States)

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Combining brain stimulation and video game to promote long-term transfer of learning and cognitive enhancement.

Science.gov (United States)

Looi, Chung Yen; Duta, Mihaela; Brem, Anna-Katharine; Huber, Stefan; Nuerk, Hans-Christoph; Cohen Kadosh, Roi

2016-02-23

Cognitive training offers the potential for individualised learning, prevention of cognitive decline, and rehabilitation. However, key research challenges include ecological validity (training design), transfer of learning and long-term effects. Given that cognitive training and neuromodulation affect neuroplasticity, their combination could promote greater, synergistic effects. We investigated whether combining transcranial direct current stimulation (tDCS) with cognitive training could further enhance cognitive performance compared to training alone, and promote transfer within a short period of time. Healthy adults received real or sham tDCS over their dorsolateral prefrontal cortices during two 30-minute mathematics training sessions involving body movements. To examine the role of training, an active control group received tDCS during a non-mathematical task. Those who received real tDCS performed significantly better in the game than the sham group, and showed transfer effects to working memory, a related but non-numerical cognitive domain. This transfer effect was absent in active and sham control groups. Furthermore, training gains were more pronounced amongst those with lower baseline cognitive abilities, suggesting the potential for reducing cognitive inequalities. All effects associated with real tDCS remained 2 months post-training. Our study demonstrates the potential benefit of this approach for long-term enhancement of human learning and cognition.

NASA Technology Transfer System

Science.gov (United States)

Tran, Peter B.; Okimura, Takeshi

2017-01-01

NTTS is the IT infrastructure for the Agency's Technology Transfer (T2) program containing 60,000+ technology portfolio supporting all ten NASA field centers and HQ. It is the enterprise IT system for facilitating the Agency's technology transfer process, which includes reporting of new technologies (e.g., technology invention disclosures NF1679), protecting intellectual properties (e.g., patents), and commercializing technologies through various technology licenses, software releases, spinoffs, and success stories using custom built workflow, reporting, data consolidation, integration, and search engines.

E-learning modules for nuclear reactor heat transfer

Science.gov (United States)

Jayaram, Praveen Bharadwaj

E learning in engineering education is becoming popular at several universities as it allows instructors to create content that the students may view and interact with at his/her own convenience. Web-based simulation and what-if analysis are examples of such educational content and has proved to be extremely beneficial for engineering students. Such pedagogical content promote active learning and encourage students to experiment and be more creative. The main objective of this project is to develop web based learning modules, in the form of analytical simulations, for the Reactor Thermal Hydraulics course offered by the College of Engineering at UT Arlington. These modules seek to comprehensively transform the traditional education structure. The simulations are built to supplement the class lectures and are divided into categories like Fundamentals, Heat generation, Heat transfer and Heat removal categories. Each category contains modules which are sub-divided chapter wise and further into section wise. Some of the important sections from the text book are taken and calculations for a particular functionality are implemented. Since it is an interactive tool, it allows user to input certain values, which are then processed with the traditional equations, and output results either in the form of a number or graphs.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis.

Science.gov (United States)

Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir M; Helvie, Mark A; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

Evolutionary pruning of transfer learned deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

Science.gov (United States)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-05-01

Deep learning models are highly parameterized, resulting in difficulty in inference and transfer learning for image recognition tasks. In this work, we propose a layered pathway evolution method to compress a deep convolutional neural network (DCNN) for classification of masses in digital breast tomosynthesis (DBT). The objective is to prune the number of tunable parameters while preserving the classification accuracy. In the first stage transfer learning, 19 632 augmented regions-of-interest (ROIs) from 2454 mass lesions on mammograms were used to train a pre-trained DCNN on ImageNet. In the second stage transfer learning, the DCNN was used as a feature extractor followed by feature selection and random forest classification. The pathway evolution was performed using genetic algorithm in an iterative approach with tournament selection driven by count-preserving crossover and mutation. The second stage was trained with 9120 DBT ROIs from 228 mass lesions using leave-one-case-out cross-validation. The DCNN was reduced by 87% in the number of neurons, 34% in the number of parameters, and 95% in the number of multiply-and-add operations required in the convolutional layers. The test AUC on 89 mass lesions from 94 independent DBT cases before and after pruning were 0.88 and 0.90, respectively, and the difference was not statistically significant (p  >  0.05). The proposed DCNN compression approach can reduce the number of required operations by 95% while maintaining the classification performance. The approach can be extended to other deep neural networks and imaging tasks where transfer learning is appropriate.

Wireless power transfer system

Science.gov (United States)

Wu, Hunter; Sealy, Kylee; Gilchrist, Aaron

2016-02-23

A system includes a first stage of an inductive power transfer system with an LCL load resonant converter with a switching section, an LCL tuning circuit, and a primary receiver pad. The IPT system includes a second stage with a secondary receiver pad, a secondary resonant circuit, a secondary rectification circuit, and a secondary decoupling converter. The secondary receiver pad connects to the secondary resonant circuit. The secondary resonant circuit connects to the secondary rectification circuit. The secondary rectification circuit connects to the secondary decoupling converter. The second stage connects to a load. The load includes an energy storage element. The second stage and load are located on a vehicle and the first stage is located at a fixed location. The primary receiver pad wirelessly transfers power to the secondary receiver pad across a gap when the vehicle positions the secondary receiver pad with respect to the primary receiver pad.

The new CIEMAT strategies for learning and knowledge transfer

International Nuclear Information System (INIS)

Marco Arboli, M.

2008-01-01

Educational and training systems are a determining factor in the potential for excellence, innovation and competitiveness in the framework of research as a means to improve know-how, capabilities and skills. In recent years, the EU has supported open and distance education through its innovation, education, training and research programs. The European initiatives promote efficiency by improving quality and occupational training in different sectors and by fostering the use of the information technologies. Having followed the new trends in training and the advantages obtained by using the net in training, the CIEMAT has also taken an interest in improving the learning and knowledge transfer environments through its virtual center. It is a space for developing online educational activities in certain areas, in which the center can be considered as expert, such as all subjects related to energy and environment: renewable, radiological protection, atmospheric contamination, fusion, nuclear power, etc. This virtual space includes a Virtual Classroom and a specialized Thematic Portals, and it aims to be a place of reference for the areas of knowledge related to energy and environment. (Author) 5 refs

Supervised Learning for Dynamical System Learning.

Science.gov (United States)

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

2015-01-01

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

Ex-vessel nuclear fuel transfer system

International Nuclear Information System (INIS)

Wade, E.E.

1978-01-01

A system for transferring fuel assemblies between a fuel transfer area and a fuel storage area while the fuel assemblies remain completely submerged in a continuous body of coolant is described. A fuel transfer area filled with reactor coolant communicating with the reactor vessel below the reactor coolant level provides a transfer area for fuel assemblies in transit to and from the reactor vessel. A positioning mechanism comprising at least one rotatable plug disposed on a fuel transfer tank located outside the reactor vessel cooperates with either the fuel transfer area or the fuel storage area to position a fuel assembly in transit. When in position, a transporting mechanism cooperating with the positioning mechanism lifts or lowers a chosen fuel assembly. The transporting mechanism together with the positioning mechanism are capable of transferring a fuel assembly between the fuel transfer area and the fuel storage area

46 CFR 153.430 - Heat transfer systems; general.

Science.gov (United States)

2010-10-01

... 46 Shipping 5 2010-10-01 2010-10-01 false Heat transfer systems; general. 153.430 Section 153.430... Temperature Control Systems § 153.430 Heat transfer systems; general. Each cargo cooling system required by... separated from all other cooling and heating systems; and (c) Allow manual regulation of the system's heat...

A Case Study to Evaluate Balance Training with Movement Test Items and through Teaching Observation: Beyond Specificity and Transfer of Learning

Science.gov (United States)

Kluwe, Margret; Miyahara, Motohide; Heveldt, Kate

2012-01-01

Background: Specificity and transfer of learning have been examined in experimental studies. However, their findings may not be relevant to practitioners because of the difference between the experiment conditions and teaching situations. This case study investigates the theoretical issue of specificity vs. transfer of learning by conducting…

Learning Content Management Systems

Directory of Open Access Journals (Sweden)

Tache JURUBESCU

2008-01-01

Full Text Available The paper explains the evolution of e-Learning and related concepts and tools and its connection with other concepts such as Knowledge Management, Human Resources Management, Enterprise Resource Planning, and Information Technology. The paper also distinguished Learning Content Management Systems from Learning Management Systems and Content Management Systems used for general web-based content. The newest Learning Content Management System, very expensive and yet very little implemented is one of the best tools that helps us to cope with the realities of the 21st Century in what learning concerns. The debates over how beneficial one or another system is for an organization, can be driven by costs involved, efficiency envisaged, and availability of the product on the market.

Sustained transfer of knowledge to practice in long-term care: facilitators and barriers of a mental health learning initiative.

Science.gov (United States)

Stolee, Paul; McAiney, Carrie A; Hillier, Loretta M; Harris, Diane; Hamilton, Pam; Kessler, Linda; Madsen, Victoria; Le Clair, J Kenneth

2009-01-01

This article explores facilitators and barriers to the impact and sustainability of a learning initiative to increase capacity of long-term care (LTC) homes to manage the mental health needs of older persons, through development of in-house Psychogeriatric Resource Persons (PRPs). Twenty interviews were conducted with LTC staff. Management support, particularly designation of time for PRP activities, development of PRP teams, and supportive learning strategies were significant factors affecting sustained knowledge transfer. Continuing education that is provided and evaluated on an ongoing basis, secures management commitment, is integrated within a broader system strategy, and provides on-the-job support has the greatest potential to affect care.

HRM Practices and MNC knowledge Transfer

DEFF Research Database (Denmark)

Minbaeva, Dana

2004-01-01

and support organizational learning environment, is positively related to the degree ofknowledge transfer to the subsidiary. Moreover, the higher degree of knowledge transfer isexpected when human resource management practices are applied as an integrated system ofinterdependent practices. Hypotheses derived......The purpose of the paper is to determine and empirically examine the effect of human resourcemanagement practices on knowledge transfer within multinational corporations. It is suggested thatthe employment of human resource practices, which affect absorptive capacity of knowledgereceivers...

Ex-vessel nuclear fuel transfer system

International Nuclear Information System (INIS)

1977-01-01

A system is described for transferring reactor fuel assemblies between a fuel storage area and a fuel transfer area while the fuel assemblies remain completely submerged in a continuous body of coolant. The invention relates particularly to sodium cooled fast breeder reactors. (UK)

Heat Transfer Phenomena in Concentrating Solar Power Systems.

Energy Technology Data Exchange (ETDEWEB)

Armijo, Kenneth Miguel; Shinde, Subhash L.

2016-11-01

Concentrating solar power (CSP) utilizes solar thermal energy to drive a thermal power cycle for the generation of electricity. CSP systems are facilitated as large, centralized power plants , such as power towers and trough systems, to take advantage of ec onomies of scale through dispatchable thermal energy storage, which is a principle advantage over other energy generation systems . Additionally, the combination of large solar concentration ratios with high solar conversion efficiencies provides a strong o pportunity of employment of specific power cycles such as the Brayton gas cycle that utilizes super critical fluids such as supercritical carbon dioxide (s CO 2 ) , compared to other sola r - fossil hybrid power plants. A comprehensive thermal - fluids examination is provided by this work of various heat transfer phenomena evident in CSP technologies. These include sub - systems and heat transfer fundamental phenomena evident within CSP systems , which include s receivers, heat transfer fluids (HTFs), thermal storage me dia and system designs , thermodynamic power block systems/components, as well as high - temperature materials. This work provides literature reviews, trade studies, and phenomenological comparisons of heat transfer media (HTM) and components and systems, all for promotion of high performance and efficient CSP systems. In addition, f urther investigations are also conducted that provide advanced heat transfer modeling approaches for gas - particle receiver systems , as well as performance/efficiency enhancement re commendations, particularly for solarized supercritical power systems .

The information system of learning quality control in higher education institutions: achievements and problems of European universities

Directory of Open Access Journals (Sweden)

Orekhova Elena

2016-01-01

Full Text Available The article deals with the main trends in the development of the system of learning quality control connected with the European integration of higher education and the democratization of education. The authors analyze the state of information systems of learning quality control existing in European higher education and identify their strong and weak points. The authors show that in the learning process universities actively use innovative analytic methods as well as modern means of collecting, storing and transferring information that ensure the successful management of such a complex object as the university of the 21st century.

The transfer of category knowledge by macaques (Macaca mulatta) and humans (Homo sapiens).

Science.gov (United States)

Zakrzewski, Alexandria C; Church, Barbara A; Smith, J David

2018-02-01

Cognitive psychologists distinguish implicit, procedural category learning (stimulus-response associations learned outside declarative cognition) from explicit-declarative category learning (conscious category rules). These systems are dissociated by category learning tasks with either a multidimensional, information-integration (II) solution or a unidimensional, rule-based (RB) solution. In the present experiments, humans and two monkeys learned II and RB category tasks fostering implicit and explicit learning, respectively. Then they received occasional transfer trials-never directly reinforced-drawn from untrained regions of the stimulus space. We hypothesized that implicit-procedural category learning-allied to associative learning-would transfer weakly because it is yoked to the training stimuli. This result was confirmed for humans and monkeys. We hypothesized that explicit category learning-allied to abstract category rules-would transfer robustly. This result was confirmed only for humans. That is, humans displayed explicit category knowledge that transferred flawlessly. Monkeys did not. This result illuminates the distinctive abstractness, stimulus independence, and representational portability of humans' explicit category rules. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

Science.gov (United States)

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

2017-02-01

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

Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness

NARCIS (Netherlands)

Klemke, Roland; Kurapati, Shalini; Kolfschoten, Gwendolyn

2013-01-01

Klemke, R., Kurapati, S., & Kolfschoten, G. (2013, 6 June). Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness. Presentation at the 3rd Irish Symposium on Game Based Learning, Dublin, Ireland. Please see also

Transfer of Learning in Management Training: Building the Payoff Into the Instructional Design.

Science.gov (United States)

Kruger, Michael J.; May, Gregory D.

1986-01-01

Describes two reinforcement techniques designed to ensure transfer of learning from management training courses to the workplace: (1) participant journal writing to capture management insights occurring during training and (2) support groups providing encouragement, feedback, and accountability. Results of an evaluation of the techniques'…

Attitudes towards transferable skills in medical undergraduates.

Science.gov (United States)

Whittle, S R; Eaton, D G

2001-02-01

Changes to the style of medical teaching will place a greater responsibility on individual medical students to manage their own learning, highlighting the need for students to develop good so-called 'transferable' skills at an early stage in their undergraduate career. To assess the attitudes of first year undergraduates towards transferable skills, and investigate the gender difference in these attitudes. To assess the contribution of their first year course to skills development. First year students, enrolled on a traditional-style course. A questionnaire asking the students to consider: (a) the importance of named transferable skills for medicine; (b) their own ability in these areas; and (c) the influence of their first year course. All students, irrespective of gender, regarded transferable skills as very important to medicine, rating organizational skills and self-learning skills as most important. Overall, students have a high level of confidence in their own skills. Male students rated their overall level of skills more highly than women. In particular they rated their information handling, managing self-learning and technical skills more highly. Students feel that their first year course has enhanced their skills in most areas. Our results suggest that students will feel equipped to succeed in a learning system which places the onus on them to take responsibility for their own learning. They clearly believe that they have the necessary skills for independent learning. The study highlights the need to enhance students' self-evaluation skills.

Entanglement transfer between bipartite systems

International Nuclear Information System (INIS)

Bougouffa, Smail; Ficek, Zbigniew

2012-01-01

The problem of a controlled transfer of an entanglement initially encoded into two two-level atoms that are successively sent through two single-mode cavities is investigated. The atoms and the cavity modes form a four-qubit system and we demonstrate the conditions under which the initial entanglement encoded into the atoms can be completely transferred to other pairs of qubits. We find that in the case of non-zero detuning between the atomic transition frequencies and the cavity mode frequencies, no complete transfer of the initial entanglement is possible to any of the other pairs of qubits. In the case of exact resonance and equal coupling strengths of the atoms to the cavity modes, an initial maximally entangled state of the atoms can be completely transferred to the cavity modes. Complete transfer of the entanglement is restricted to the cavity modes, with transfer to the other pairs being limited to 50%. We find that complete transfer of an initial entanglement to other pairs of qubits may take place if the initial state is not the maximally entangled state and the atoms couple to the cavity modes with unequal strengths. Depending on the ratio between the coupling strengths, optimal entanglement can be created between the atoms and one of the cavity modes.

Evolution of PHWR fuel transfer system based on operating experience

International Nuclear Information System (INIS)

Parvatikar, R.S.; Singh, Jaipal; Chaturvedi, P.C.; Bhambra, H.S.

2006-01-01

Fuel Transfer System facilitates loading of new fuel into Fuelling Machine, receipt of spent fuel from Fuelling Machine and its further transportation to Storage Bay. To overcome the limitations of transferring a pair of bundles in the single tube Airlock and Transfer Arm in RAPS-1 and 2/MAPS, a new concept of six tube Transfer Magazine was introduced in NAPS. This resulted in simultaneous loading of new fuel from Transfer Magazine into the Fuelling Machine and unloading of spent fuel from the Fuelling Machine through the exchange mode. It further facilitated the parallel/simultaneous operation of refuelling by Fuelling Machines on the reactor and transferring of spent fuel bundles from the Transfer Magazine to the bay. This new design of Fuel Transfer System was adopted for all standardised 220 MWe PHWRs. Based on the experience gained in 220 MWe PHWRs in the area of operation and maintenance, a number of improvements have been carried out over the years. These aspects have been further strengthened and refined in the Fuel Transfer System of 540 MWe units. The operating experience of the system indicates that the presence of heavy water in the Transfer Magazine poses limitations in its maintenance in the Fuel Transfer room. Further, Surveillance and maintenance of large number of under water equipment and associated valves, rams and underwater sensors is putting extra burden on the O and M efforts. A new concept of mobile light water filled Transfer Machine has been evolved for proposed 700 MWe PHWR units to simplify Fuel Transfer System. This has been made possible by adopting snout level control in the Fuelling Machine, elimination of Shuttle Transport System and locating the Storage Bay adjacent to the Reactor Building. This paper describes the evolution of Fuel Transfer System concepts and various improvements based on the experience gained in the operation and maintenance of the system. (author)

Heat transfer in heterogeneous propellant combustion systems

International Nuclear Information System (INIS)

Brewster, M.Q.

1992-01-01

This paper reports that heat transfer plays an important role in several critical areas of heterogeneous, solid-propellant combustion systems. These areas include heat feedback to the propellant surface, heat transfer between burning aluminum droplets and their surroundings, heat transfer to internal insulation systems, and heat transfer to aft-end equipment. Gas conduction dominates heat feedback to the propellant surface in conventional ammonium perchlorate (AP) composite propellants, although particle radiative feedback also plays a significant role in combustion of metalized propellants. Particle radiation plays a dominant role in heat transfer to internal insulation, compared with that of convection. However, conduction by impingement of burning aluminum particles, which has not been extensively studied, may also be significant. Radiative heat loss plays an important role in determining the burning rate of molten aluminum particles due to a highly luminous, oxide particle-laden, detached flame envelope. Radiation by aluminum oxide smoke particles also plays a dominant role in heat transfer from the exhaust plume to aft-end equipment. Uncertainties in aluminum oxide particle-size distribution and optical properties still make it difficult to predict radiative plume heat transfer accurately from first principles

Transfer of Juggling Skills Acquired in a Virtual Environment

DEFF Research Database (Denmark)

Hauge, Alex Patrick; Kragegaard, Christian Skriver; Kjæhr, Emil Bering

2013-01-01

This paper explores whether motoric skills acquired within a virtual training environment can be successfully transferred to the real world by comparing a virtual environment with a traditional learning environment. Specifically, a system for learning juggling with virtual balls was designed with...

The transfer of learning process: From an elementary science methods course to classroom instruction

Science.gov (United States)

Carter, Nina Leann

The purpose of this qualitative multiple-case study was to explore the transfer of learning process in student teachers. This was carried out by focusing on information learned from an elementary science methods and how it was transferred into classroom instruction during student teaching. Participants were a purposeful sampling of twelve elementary education student teachers attending a public university in north Mississippi. Factors that impacted the transfer of learning during lesson planning and implementation were sought. The process of planning and implementing a ten-day science instructional unit during student teaching was examined through lesson plan documentation, in-depth individual interviews, and two focus group interviews. Narratives were created to describe the participants' experiences as well as how they plan for instruction and consider science pedagogical content knowledge (PCK). Categories and themes were then used to build explanations applying to the research questions. The themes identified were Understanding of Science PCK, Minimalism, Consistency in the Teacher Education Program, and Emphasis on Science Content. The data suggested that the participants lack in their understanding of science PCK, took a minimalistic approach to incorporating science into their ten-day instructional units, experienced inconsistencies in the teacher education program, and encountered a lack of emphasis on science content in their field experience placements. The themes assisted in recognizing areas in the elementary science methods courses, student teaching field placements, and university supervision in need of modification.

An Integrative Model of Organizational Learning and Social Capital on Effective Knowledge Transfer and Perceived Organizational Performance

Science.gov (United States)

Rhodes, Jo; Lok, Peter; Hung, Richard Yu-Yuan; Fang, Shih-Chieh

2008-01-01

Purpose: The purpose of this paper is to set out to examine the relationships of organizational learning, social capital and the effectiveness of knowledge transfer and perceived organisational performance. Integrating organizational learning capability with social capital networks to shape a holistic knowledge sharing and management enterprise…

A Web-Based Learning Support System for Inquiry-Based Learning

Science.gov (United States)

Kim, Dong Won; Yao, Jingtao

The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

Intelligent Web-Based Learning System with Personalized Learning Path Guidance

Science.gov (United States)

Chen, C. M.

2008-01-01

Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

Machine learning systems

Energy Technology Data Exchange (ETDEWEB)

Forsyth, R

1984-05-01

With the dramatic rise of expert systems has come a renewed interest in the fuel that drives them-knowledge. For it is specialist knowledge which gives expert systems their power. But extracting knowledge from human experts in symbolic form has proved arduous and labour-intensive. So the idea of machine learning is enjoying a renaissance. Machine learning is any automatic improvement in the performance of a computer system over time, as a result of experience. Thus a learning algorithm seeks to do one or more of the following: cover a wider range of problems, deliver more accurate solutions, obtain answers more cheaply, and simplify codified knowledge. 6 references.

Radiative transfer in atmosphere-sea ice-ocean system

Energy Technology Data Exchange (ETDEWEB)

Jin, Z.; Stamnes, K.; Weeks, W.F. [Univ. of Alaska, Fairbanks, AK (United States); Tsay, S.C. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)

1996-04-01

Radiative energy is critical in controlling the heat and mass balance of sea ice, which significantly affects the polar climate. In the polar oceans, light transmission through the atmosphere and sea ice is essential to the growth of plankton and algae and, consequently, to the microbial community both in the ice and in the ocean. Therefore, the study of radiative transfer in the polar atmosphere, sea ice, and ocean system is of particular importance. Lacking a properly coupled radiative transfer model for the atmosphere-sea ice-ocean system, a consistent study of the radiative transfer in the polar atmosphere, snow, sea ice, and ocean system has not been undertaken before. The radiative transfer processes in the atmosphere and in the ice and ocean have been treated separately. Because the radiation processes in the atmosphere, sea ice, and ocean depend on each other, this separate treatment is inconsistent. To study the radiative interaction between the atmosphere, clouds, snow, sea ice, and ocean, a radiative transfer model with consistent treatment of radiation in the coupled system is needed and is under development.

Improving buried threat detection in ground-penetrating radar with transfer learning and metadata analysis

Science.gov (United States)

Colwell, Kenneth A.; Torrione, Peter A.; Morton, Kenneth D.; Collins, Leslie M.

2015-05-01

Ground-penetrating radar (GPR) technology has proven capable of detecting buried threats. The system relies on a binary classifier that is trained to distinguish between two classes: a target class, encompassing many types of buried threats and their components; and a nontarget class, which includes false alarms from the system prescreener. Typically, the training process involves a simple partition of the data into these two classes, which allows for straightforward application of standard classifiers. However, since training data is generally collected in fully controlled environments, it includes auxiliary information about each example, such as the specific type of threat, its purpose, its components, and its depth. Examples from the same specific or general type may be expected to exhibit similarities in their GPR data, whereas examples from different types may differ greatly. This research aims to leverage this additional information to improve overall classification performance by fusing classifier concepts for multiple groups, and to investigate whether structure in this information can be further utilized for transfer learning, such that the amount of expensive training data necessary to learn a new, previously-unseen target type may be reduced. Methods for accomplishing these goals are presented with results from a dataset containing a variety of target types.

Corrosion control for the Hanford site waste transfer system

International Nuclear Information System (INIS)

Haberman, J.H.

1995-01-01

Processing large volumes of spent reactor fuel and other related waste management activities produced radioactive wastes which have been stored in underground high-level waste storage tanks since the 1940s. The effluent waste streams from the processing facilities were stored underground in high-level waste storage tanks. The waste was transferred between storage tanks and from the tanks to waste processing facilities in a complex network of underground piping. The underground waste transfer system consists of process piping, catch tanks, lift tanks, diversion boxes, pump pits, valves, and jumpers. Corrosion of the process piping from contact with the soil is a primary concern. The other transfer system components are made of corrosion-resistant alloys or they are isolated from the underground environment and experience little degradation. Corrosion control of the underground transfer system is necessary to ensure that transfer routes will be available for future waste retrieval, processing,a nd disposal. Today, most waste transfer lines are protected by an active impressed-current cathodic protection (CP) system. The original system has been updated. Energization surveys and a recent base-line survey demonstrate that system operational goals are met

QuickCash: Secure Transfer Payment Systems

Directory of Open Access Journals (Sweden)

Abdulrahman Alhothaily

2017-06-01

Full Text Available Payment systems play a significant role in our daily lives. They are an important driver of economic activities and a vital part of the banking infrastructure of any country. Several current payment systems focus on security and reliability but pay less attention to users’ needs and behaviors. For example, people may share their bankcards with friends or relatives to withdraw money for various reasons. This behavior can lead to a variety of privacy and security issues since the cardholder has to share a bankcard and other sensitive information such as a personal identification number (PIN. In addition, it is commonplace that cardholders may lose their cards, and may not be able to access their accounts due to various reasons. Furthermore, transferring money to an individual who has lost their bankcard and identification information is not a straightforward task. A user-friendly person-to-person payment system is urgently needed to perform secure and reliable transactions that benefit from current technological advancements. In this paper, we propose two secure fund transfer methods termed QuickCash Online and QuickCash Offline to transfer money from peer to peer using the existing banking infrastructure. Our methods provide a convenient way to transfer money quickly, and they do not require using bank cards or any identification card. Unlike other person-to-person payment systems, the proposed methods do not require the receiving entity to have a bank account, or to perform any registration procedure. We implement our QuickCash payment systems and analyze their security strengths and properties.

QuickCash: Secure Transfer Payment Systems

Science.gov (United States)

Alhothaily, Abdulrahman; Alrawais, Arwa; Song, Tianyi; Lin, Bin; Cheng, Xiuzhen

2017-01-01

Payment systems play a significant role in our daily lives. They are an important driver of economic activities and a vital part of the banking infrastructure of any country. Several current payment systems focus on security and reliability but pay less attention to users’ needs and behaviors. For example, people may share their bankcards with friends or relatives to withdraw money for various reasons. This behavior can lead to a variety of privacy and security issues since the cardholder has to share a bankcard and other sensitive information such as a personal identification number (PIN). In addition, it is commonplace that cardholders may lose their cards, and may not be able to access their accounts due to various reasons. Furthermore, transferring money to an individual who has lost their bankcard and identification information is not a straightforward task. A user-friendly person-to-person payment system is urgently needed to perform secure and reliable transactions that benefit from current technological advancements. In this paper, we propose two secure fund transfer methods termed QuickCash Online and QuickCash Offline to transfer money from peer to peer using the existing banking infrastructure. Our methods provide a convenient way to transfer money quickly, and they do not require using bank cards or any identification card. Unlike other person-to-person payment systems, the proposed methods do not require the receiving entity to have a bank account, or to perform any registration procedure. We implement our QuickCash payment systems and analyze their security strengths and properties. PMID:28608846

QuickCash: Secure Transfer Payment Systems.

Science.gov (United States)

Alhothaily, Abdulrahman; Alrawais, Arwa; Song, Tianyi; Lin, Bin; Cheng, Xiuzhen

2017-06-13

Payment systems play a significant role in our daily lives. They are an important driver of economic activities and a vital part of the banking infrastructure of any country. Several current payment systems focus on security and reliability but pay less attention to users' needs and behaviors. For example, people may share their bankcards with friends or relatives to withdraw money for various reasons. This behavior can lead to a variety of privacy and security issues since the cardholder has to share a bankcard and other sensitive information such as a personal identification number (PIN). In addition, it is commonplace that cardholders may lose their cards, and may not be able to access their accounts due to various reasons. Furthermore, transferring money to an individual who has lost their bankcard and identification information is not a straightforward task. A user-friendly person-to-person payment system is urgently needed to perform secure and reliable transactions that benefit from current technological advancements. In this paper, we propose two secure fund transfer methods termed QuickCash Online and QuickCash Offline to transfer money from peer to peer using the existing banking infrastructure. Our methods provide a convenient way to transfer money quickly, and they do not require using bank cards or any identification card. Unlike other person-to-person payment systems, the proposed methods do not require the receiving entity to have a bank account, or to perform any registration procedure. We implement our QuickCash payment systems and analyze their security strengths and properties.

Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

Directory of Open Access Journals (Sweden)

Di Feng

2018-02-01

Full Text Available Reusing the tactile knowledge of some previously-explored objects (prior objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT, and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10 % when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20 % . The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer.

Are skills learned in nursing transferable to other careers?

Science.gov (United States)

Duffield, Christine; O'Brien-Pallas, Linda; Aitken, Leanne M

2005-01-01

To determine the influence of skills gained in nursing on the transition to a non-nursing career. Little is known about the impact that nursing skills have on the transition to new careers or about the transferability of nursing skills to professions outside nursing. A postal questionnaire was mailed to respondents who had left nursing. The questionnaire included demographic, nursing education and practice information, reasons for entering and leaving nursing, perceptions of the skills gained in nursing and the ease of adjustment to a new career. Data analysis included exploratory and confirmatory factor analysis, Pearson product moment correlations and linear and multiple regression analysis. Skills learned as a nurse that were valuable in acquiring a career outside nursing formed two factors, including "management of self and others" and "knowledge and skills learned," explaining 32% of the variation. The highest educational achievement while working as a nurse, choosing nursing as a "default choice," leaving nursing because of "worklife/homelife balance" and the skills of "management of self and others" and "knowledge and skills" had a significant relationship with difficulty adjusting to a non-nursing work role and, overall, explained 28% of the variation in this difficulty adjusting. General knowledge and skills learned in nursing prove beneficial in adjusting to roles outside nursing.

Recommender Systems for Learning

CERN Document Server

Manouselis, Nikos; Verbert, Katrien; Duval, Erik

2013-01-01

Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness

NARCIS (Netherlands)

Klemke, Roland; Kurapati, Shalini; Kolfschoten, Gwendolyn

2013-01-01

Klemke, R., Kurapati, S., & Kolfschoten, G. (2013, 6 June). Transferring an educational board game to a multi-user mobile learning game to increase shared situational awareness. In P. Rooney (Ed.), Proceedings of the 3rd Irish Symposium on Game Based Learning (pp. 8-9). Dublin, Ireland. Please see

W-314, waste transfer alternative piping system description

International Nuclear Information System (INIS)

Papp, I.G.

1998-01-01

It is proposed that the reliability, operability, and flexibility of the Retrieval Transfer System be substantially upgraded by replacing the planned single in-farm pipeline from the AN-AY-AZ-(SY) Tank Farm Complex to the AP Farm with three parallel pipelines outside the tank farms. The proposed system provides simplified and redundant routes for the various transfer missions, and prevents the risk of transfer gridlock when the privatization effort swings into full operation

W-314, waste transfer alternative piping system description

Energy Technology Data Exchange (ETDEWEB)

Papp, I.G.

1998-04-30

It is proposed that the reliability, operability, and flexibility of the Retrieval Transfer System be substantially upgraded by replacing the planned single in-farm pipeline from the AN-AY-AZ-(SY) Tank Farm Complex to the AP Farm with three parallel pipelines outside the tank farms. The proposed system provides simplified and redundant routes for the various transfer missions, and prevents the risk of transfer gridlock when the privatization effort swings into full operation.

A Model for the Transfer of Perceptual-Motor Skill Learning in Human Behaviors

Science.gov (United States)

Rosalie, Simon M.; Muller, Sean

2012-01-01

This paper presents a preliminary model that outlines the mechanisms underlying the transfer of perceptual-motor skill learning in sport and everyday tasks. Perceptual-motor behavior is motivated by performance demands and evolves over time to increase the probability of success through adaptation. Performance demands at the time of an event…

A pneumatic transfer system for special form 252Cf

International Nuclear Information System (INIS)

Gehrke, R.J.; Berry, S.M.; Grafwallner, E.G.; Hoggan, J.M.

1996-09-01

A pneumatic transfer system has been developed for use with series 100 Special Form 252 Cf. It was developed to reduce the exposure to personnel handling sources of 252 Cf with masses up to 150 microg by permitting remotely activated two-way transfer between the storage container and the irradiation position. The pneumatic transfer system also permits transfers for reproducible repetitive irradiation periods. In addition to the storage container equipped with quick-release fittings, the transfer system consists of an irradiation station, a control box with momentary contact switches to activate the air-pressure control valves and indicators to identify the location of the source, and connecting air hose and electrical wire. A source of 20 psig air and 110 volt electrical power are required for operation of the transfer system which can be easily moved and set up by one individual in 5 to 10 minutes. Tests have shown that rarely does a source become lodged in the transfer tubing, but two methods have been developed to handle incomplete transfers of the 252 Cf source. The first method consists of closing one air vent to allow a pressure impulse to propel the source to the opposite side. The second method applies to those 252 Cf capsules with a threaded or tapped end to which a small ferromagnetic piece can be attached; an incompletely transferred source in the transfer tube can then be guided to a position of safety by surrounding the transfer tubing containing the capsule with a horseshoe magnet attached to the end of a long pole

ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

Science.gov (United States)

Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

2018-02-01

Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

Scaling CMS data transfer system for LHC start-up

International Nuclear Information System (INIS)

Tuura, L; Bockelman, B; Bonacorsi, D; Egeland, R; Feichtinger, D; Metson, S; Rehn, J

2008-01-01

The CMS experiment will need to sustain uninterrupted high reliability, high throughput and very diverse data transfer activities as the LHC operations start. PhEDEx, the CMS data transfer system, will be responsible for the full range of the transfer needs of the experiment. Covering the entire spectrum is a demanding task: from the critical high-throughput transfers between CERN and the Tier-1 centres, to high-scale production transfers among the Tier-1 and Tier-2 centres, to managing the 24/7 transfers among all the 170 institutions in CMS and to providing straightforward access to handful of files to individual physicists. In order to produce the system with confirmed capability to meet the objectives, the PhEDEx data transfer system has undergone rigourous development and numerous demanding scale tests. We have sustained production transfers exceeding 1 PB/month for several months and have demonstrated core system capacity several orders of magnitude above expected LHC levels. We describe the level of scalability reached, and how we got there, with focus on the main insights into developing a robust, lock-free and scalable distributed database application, the validation stress test methods we have used, and the development and testing tools we found practically useful

Self-perceived long-term transfer of learning after postpartum hemorrhage simulation training.

Science.gov (United States)

de Melo, Brena Carvalho Pinto; Rodrigues Falbo, Ana; Sorensen, Jette Led; van Merriënboer, Jeroen J G; van der Vleuten, Cees

2018-05-01

To explore long-term transfer (application of acquired knowledge and skills on the job) after postpartum hemorrhage simulation training based on either instructional design (ID) principles or conventional best practice. In this qualitative study, semi-structured interviews with obstetrics and gynecology healthcare practitioners were conducted between August 7 and September 26, 2015, in Recife, Brazil. The participants were randomly selected from each of two postpartum hemorrhage simulations attended 2 years earlier (one ID and one conventional best practice). Thematic analysis was used to explore (1) residents' perceptions of long-term transfer of learning, (2) ID elements influencing the perceived long-term transfer, and (3) differences in the participants' perceptions according to the type of simulation attended. There were 12 interview participants. After either simulation format, residents perceived long-term transfer effects. Training design factors influencing transfer were, in their opinion, related to trainees' characteristics, simulation design, and workplace environment. Trainees who participated in the ID-based simulation perceived better communication skills and better overall situational awareness: "I didn't do that before." All residents perceived long-term transfer after simulation training for postpartum hemorrhage. Those who attended the ID format additionally perceived improvements in communication skills and situational awareness, which are fundamental factors in the management of postpartum hemorrhage. © 2018 International Federation of Gynecology and Obstetrics.

Impact of Self-Explanation and Analogical Comparison Support on Learning Processes, Motivation, Metacognition, and Transfer

Science.gov (United States)

Richey, J. Elizabeth

Research examining analogical comparison and self-explanation has produced a robust set of findings about learning and transfer supported by each instructional technique. However, it is unclear how the types of knowledge generated through each technique differ, which has important implications for cognitive theory as well as instructional practice. I conducted a pair of experiments to directly compare the effects of instructional prompts supporting self-explanation, analogical comparison, and the study of instructional explanations across a number of fine-grained learning process, motivation, metacognition, and transfer measures. Experiment 1 explored these questions using sequence extrapolation problems, and results showed no differences between self-explanation and analogical comparison support conditions on any measure. Experiment 2 explored the same questions in a science domain. I evaluated condition effects on transfer outcomes; self-reported self-explanation, analogical comparison, and metacognitive processes; and achievement goals. I also examined relations between transfer and self-reported processes and goals. Receiving materials with analogical comparison support and reporting greater levels of analogical comparison were both associated with worse transfer performance, while reporting greater levels of self-explanation was associated with better performance. Learners' self-reports of self-explanation and analogical comparison were not related to condition assignment, suggesting that the questionnaires did not measure the same processes promoted by the intervention, or that individual differences in processing are robust even when learners are instructed to engage in self-explanation or analogical comparison.

Developing and testing transferability and feasibility of a model for educators using simulation-based learning - A European collaboration

DEFF Research Database (Denmark)

Bøje, Rikke Buus; Bland, Andrew; Sutton, Andrew

2017-01-01

of the study were to develop a model to educate the educators who deliver simulation-based learning and to test to which extent this model could be transferred to education providers in different national settings. METHODS: This model, its transferability and feasibility, was tested across three European...

Modeling learning technology systems as business systems

NARCIS (Netherlands)

Avgeriou, Paris; Retalis, Symeon; Papaspyrou, Nikolaos

2003-01-01

The design of Learning Technology Systems, and the Software Systems that support them, is largely conducted on an intuitive, ad hoc basis, thus resulting in inefficient systems that defectively support the learning process. There is now justifiable, increasing effort in formalizing the engineering

Data transfer in on-line systems

International Nuclear Information System (INIS)

Zacharov, V.

1978-01-01

The problem of transfer of data in both directions between experimental equipment and process systems on the one hand, and hardware processors on the other, is an important one. This fundamental question is discussed in the coxtent of contemporary practice, where the principal processing element is the minicomputer. Although several interface conventions are considered, practice is dominated by the CAMAC system, and the main emphasis is to review recent developments in that system, particularly in the area of distributed configurations. The impact of new microcircuit technology on the way in which data transfers are performed is only beginning. The present discussion trys to assess this impact and to identify the main changes that are expected to occur. (Auth.)

Transfer of Perceptual Learning of Depth Discrimination Between Local and Global Stereograms

OpenAIRE

Gantz, Liat; Bedell, Harold

2010-01-01

Several previous studies reported differences when stereothresholds are assessed with local-contour stereograms vs. complex random-dot stereograms (RDSs). Dissimilar thresholds may be due to differences in the properties of the stereograms (e.g., spatial frequency content, contrast, inter-element separation, area) or to different underlying processing mechanisms. This study examined the transfer of perceptual learning of depth discrimination between local and global RDSs with similar properti...

Optical Energy Transfer and Conversion System

Science.gov (United States)

Hogan, Bartholomew P. (Inventor); Stone, William C. (Inventor)

2018-01-01

An optical energy transfer and conversion system comprising a fiber spooler and an electrical power extraction subsystem connected to the spooler with an optical waveguide. Optical energy is generated at and transferred from a base station through fiber wrapped around the spooler, and ultimately to the power extraction system at a remote mobility platform for conversion to another form of energy. The fiber spooler may reside on the remote mobility platform which may be a vehicle, or apparatus that is either self-propelled or is carried by a secondary mobility platform either on land, under the sea, in the air or in space.

Personalised Learning Object System Based on Self-Regulated Learning Theories

Directory of Open Access Journals (Sweden)

Ali Alharbi

2014-06-01

Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

MOODLE – COMPUTERIZED DISTANT LEARNING SUPPORT SYSTEM

Directory of Open Access Journals (Sweden)

V. A. Tunda

2014-01-01

Full Text Available Moodle (Modular Object-Oriented Dynamic Learning Environment is the system developed by the English-speaking community around the world for more than 10 years, supports both, offline and online training. In most cases, Moodle is used to support and connect learning face-to-face with online training, as well as with other types of learning. Moodle allows you to ask all sorts of questions and assess responses in a variety of ways. The central concept of Moodle is a course in which one or more teachers offer students resources (such as files, folders, Web pages and participate in interactive activities (such as forums, wikis, blogging, lessons, seminars, assignments, examinations. Students and teachers can change roles, mutually assess each other, share knowledge on the topics of study in the glossary and database system.In the English-speaking world, there are public sites with detailed documentation on Moodle, which is constantly verified and modified in accordance with emerging new versions of the system; Russian versions do not have public sites with detailed translation of the English-language documentation. On what and to whom you want to perform actions in the daily practice of the modern versions, only the barest of outlines on paid seminars and presentations to those who started the implementation of Moodle in your organization are given. And this despite the fact that the system has a great variety of Moodle (over 500 settings with different levels of functionality to be performed, to maintain and develop specially organized by the team of specialists. The question is not only about creating a training course in Moodle. It's about maintaining the health of the system within the institution, such as a University. Under the "health maintenance" means: availability and preservation of up-to-date documentation on system and manuals on Moodle separately for administrators, managers, teachers and students at their level, training consultants

I sup(123) target transfer system

International Nuclear Information System (INIS)

Almeida, G.L. de; Rautenberg, F.A.

1986-01-01

The construction of target transfer system using a robot into hot cell of IEN cyclotron (Brazilian-CNEN) for sup(123)I production is presented. The system operation is described, and the advantages are shown. (M.C.K.)

Embedded system file transfer USB

International Nuclear Information System (INIS)

Jaoua, Mehdi

2008-01-01

The development of the communication series A emphasized new aspects of data exchange. The transfer of data, subject of my project of end of studies, consists in transferring from the files of a support of mass towards another via port USB. In first phase, I had like stain the realization of an embarked system allowing the communication between a key USB and final of communication such as a Pc. For this fact, I had to include/understand the operation of protocol USB and thus I could programmed a Peak to manage this communication. The second phase, will consist in extending this project towards a transmission de< donnees between two keys USB without intervention of a powerful machine equipped with an operating system pour rant to manage this transaction. (Author)

Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks.

Science.gov (United States)

Kim, D H; MacKinnon, T

2018-05-01

To identify the extent to which transfer learning from deep convolutional neural networks (CNNs), pre-trained on non-medical images, can be used for automated fracture detection on plain radiographs. The top layer of the Inception v3 network was re-trained using lateral wrist radiographs to produce a model for the classification of new studies as either "fracture" or "no fracture". The model was trained on a total of 11,112 images, after an eightfold data augmentation technique, from an initial set of 1,389 radiographs (695 "fracture" and 694 "no fracture"). The training data set was split 80:10:10 into training, validation, and test groups, respectively. An additional 100 wrist radiographs, comprising 50 "fracture" and 50 "no fracture" images, were used for final testing and statistical analysis. The area under the receiver operator characteristic curve (AUC) for this test was 0.954. Setting the diagnostic cut-off at a threshold designed to maximise both sensitivity and specificity resulted in values of 0.9 and 0.88, respectively. The AUC scores for this test were comparable to state-of-the-art providing proof of concept for transfer learning from CNNs in fracture detection on plain radiographs. This was achieved using only a moderate sample size. This technique is largely transferable, and therefore, has many potential applications in medical imaging, which may lead to significant improvements in workflow productivity and in clinical risk reduction. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Management control as basis for a transfer pricing system

NARCIS (Netherlands)

Steens, H.B.A.; Van Dam, Harmen; Casna, Richard

2003-01-01

The chapter documents the contribution to a international seminar on transfer pricing. The chapter describes how key management concepts can contribute to shaping transfer pricing systems and defining transfer pricing methods.

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

Science.gov (United States)

Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

2016-07-01

We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology

Science.gov (United States)

Petković, Dalibor; Shamshirband, Shahaboddin; Pavlović, Nenad T.; Anuar, Nor Badrul; Kiah, Miss Laiha Mat

2014-07-01

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.

Transfer of memory trace of cerebellum-dependent motor learning in human prism adaptation: a model study.

Science.gov (United States)

Nagao, Soichi; Honda, Takeru; Yamazaki, Tadashi

2013-11-01

Accumulating experimental evidence suggests that the memory trace of ocular reflex adaptation is initially encoded in the cerebellar cortex, and later transferred to the cerebellar nuclei for consolidation through repetitions of training. However, the memory transfer is not well characterized in the learning of voluntary movement. Here, we implement our model of memory transfer to interpret the data of prism adaptation (Martin, Keating, Goodkin, Bastian, & Thach, 1996a, 1996b), assuming that the cerebellar nuclear memory formed by memory transfer is used for normal throwing. When the subject was trained to throw darts wearing prisms in 30-40 trials, the short-term memory for recalibrating the throwing direction by gaze would be formed in the cerebellar cortex, which was extinguished by throwing with normal vision in a similar number of trials. After weeks of repetitions of short-term prism adaptation, the long-term memory would be formed in the cerebellar nuclei through memory transfer, which enabled one to throw darts to the center wearing prisms without any training. These two long-term memories, one for throwing with normal vision and the other for throwing wearing prisms, are assumed to be utilized automatically under volitional control. Moreover, when the prisms were changed to new prisms, a new memory for adapting to the new prisms would be formed in the cerebellar cortex, just to counterbalance the nuclear memory of long-term adaptation to the original prisms in a similar number of trials. These results suggest that memory transfer may occur in the learning of voluntary movements. Copyright © 2013 Elsevier Ltd. All rights reserved.

Affordance Realization in Climbing: Learning and Transfer.

Science.gov (United States)

Seifert, Ludovic; Orth, Dominic; Mantel, Bruno; Boulanger, Jérémie; Hérault, Romain; Dicks, Matt

2018-01-01

The aim of this study was to investigate how the affordances of an indoor climbing wall changed for intermediate climbers following a period of practice during which hold orientation was manipulated within a learning and transfer protocol. The learning protocol consisted of four sessions, in which eight climbers randomly ascended three different routes of fixed absolute difficulty (5c on the French scale), as fluently as possible. All three routes were 10.3 m in height and composed of 20 hand-holds at the same locations on an artificial climbing wall; only hold orientations were altered: (i) a horizontal-edge route (H) was designed to afford horizontal hold grasping, (ii) a vertical-edge route (V) afforded vertical hold grasping, and (iii), a double-edge route (D) was designed to afford both horizontal and vertical hold grasping. Five inertial measurement units (IMU) (3D accelerometer, 3D gyroscope, 3D magnetometer) were attached to the hip, feet and forearms to analyze the vertical acceleration and direction (3D unitary vector) of each limb and hip in ambient space during the entire ascent. Segmentation and classification processes supported detection of movement and stationary phases for each IMU. Depending on whether limbs and/or hip were moving, a decision tree distinguished four states of behavior: stationary (absence of limb and hip motion), hold exploration (absence of hip motion but at least one limb in motion), hip movement (hip in motion but absence of limb motion) and global motion (hip in motion and at least one limb in motion). Results showed that with practice, the learners decreased the relative duration of hold exploration, suggesting that they improved affordance perception of hold grasp-ability. The number of performatory movements also decreased as performance increased during learning sessions, confirming that participants' climbing efficacy improved as a function of practice. Last, the results were more marked for the H route, while the D route

Affordance Realization in Climbing: Learning and Transfer

Directory of Open Access Journals (Sweden)

Ludovic Seifert

2018-05-01

Full Text Available The aim of this study was to investigate how the affordances of an indoor climbing wall changed for intermediate climbers following a period of practice during which hold orientation was manipulated within a learning and transfer protocol. The learning protocol consisted of four sessions, in which eight climbers randomly ascended three different routes of fixed absolute difficulty (5c on the French scale, as fluently as possible. All three routes were 10.3 m in height and composed of 20 hand-holds at the same locations on an artificial climbing wall; only hold orientations were altered: (i a horizontal-edge route (H was designed to afford horizontal hold grasping, (ii a vertical-edge route (V afforded vertical hold grasping, and (iii, a double-edge route (D was designed to afford both horizontal and vertical hold grasping. Five inertial measurement units (IMU (3D accelerometer, 3D gyroscope, 3D magnetometer were attached to the hip, feet and forearms to analyze the vertical acceleration and direction (3D unitary vector of each limb and hip in ambient space during the entire ascent. Segmentation and classification processes supported detection of movement and stationary phases for each IMU. Depending on whether limbs and/or hip were moving, a decision tree distinguished four states of behavior: stationary (absence of limb and hip motion, hold exploration (absence of hip motion but at least one limb in motion, hip movement (hip in motion but absence of limb motion and global motion (hip in motion and at least one limb in motion. Results showed that with practice, the learners decreased the relative duration of hold exploration, suggesting that they improved affordance perception of hold grasp-ability. The number of performatory movements also decreased as performance increased during learning sessions, confirming that participants' climbing efficacy improved as a function of practice. Last, the results were more marked for the H route, while the D

An Approach for Externalization of Expert Tacit Knowledge Using a Query Management System in an E-Learning Environment

Science.gov (United States)

Khan, Abdul Azeez; Khader, Sheik Abdul

2014-01-01

E-learning or electronic learning platforms facilitate delivery of the knowledge spectrum to the learning community through information and communication technologies. The transfer of knowledge takes place from experts to learners, and externalization of the knowledge transfer is significant. In the e-learning environment, the learners seek…

Critical Points in Distance Learning System

Directory of Open Access Journals (Sweden)

Airina Savickaitė

2013-08-01

Full Text Available Purpose – This article presents the results of distance learning system analysis, i.e. the critical elements of the distance learning system. The critical points of distance learning are a part of distance education online environment interactivity/community process model. The most important is the fact that the critical point is associated with distance learning participants. Design/methodology/approach – Comparative review of articles and analysis of distance learning module. Findings – A modern man is a lifelong learner and distance learning is a way to be a modern person. The focus on a learner and feedback is the most important thing of learning distance system. Also, attention should be paid to the lecture-appropriate knowledge and ability to convey information. Distance system adaptation is the way to improve the learner’s learning outcomes. Research limitations/implications – Different learning disciplines and learning methods may have different critical points. Practical implications – The information of analysis could be important for both lecturers and students, who studies distance education systems. There are familiar critical points which may deteriorate the quality of learning. Originality/value – The study sought to develop remote systems for applications in order to improve the quality of knowledge. Keywords: distance learning, process model, critical points. Research type: review of literature and general overview.

Proactive and retroactive transfer of middle age adults in a sequential motor learning task

NARCIS (Netherlands)

Verneau, M.; Kamp, J. van der; Savelsbergh, G,J.; Looze, M.P. de

2015-01-01

We assessed the effects of aging in the transfer of motor learning in a sequential manual assembly task that is representative for real working conditions. On two different days, young (18-30years) and middle-aged adults (50-65years) practiced to build two products that consisted of the same six

Identification of MIMO systems with sparse transfer function coefficients

Science.gov (United States)

Qiu, Wanzhi; Saleem, Syed Khusro; Skafidas, Efstratios

2012-12-01

We study the problem of estimating transfer functions of multivariable (multiple-input multiple-output--MIMO) systems with sparse coefficients. We note that subspace identification methods are powerful and convenient tools in dealing with MIMO systems since they neither require nonlinear optimization nor impose any canonical form on the systems. However, subspace-based methods are inefficient for systems with sparse transfer function coefficients since they work on state space models. We propose a two-step algorithm where the first step identifies the system order using the subspace principle in a state space format, while the second step estimates coefficients of the transfer functions via L1-norm convex optimization. The proposed algorithm retains good features of subspace methods with improved noise-robustness for sparse systems.

Transfer Learning for Collaborative Filtering Using a Psychometrics Model

Directory of Open Access Journals (Sweden)

Haijun Zhang

2016-01-01

Full Text Available In a real e-commerce website, usually only a small number of users will give ratings to the items they purchased, and this can lead to the very sparse user-item rating data. The data sparsity issue will greatly limit the recommendation performance of most recommendation algorithms. However, a user may register accounts in many e-commerce websites. If such users’ historical purchasing data on these websites can be integrated, the recommendation performance could be improved. But it is difficult to align the users and items between these websites, and thus how to effectively borrow the users’ rating data of one website (source domain to help improve the recommendation performance of another website (target domain is very challenging. To this end, this paper extended the traditional one-dimensional psychometrics model to multidimension. The extended model can effectively capture users’ multiple interests. Based on this multidimensional psychometrics model, we further propose a novel transfer learning algorithm. It can effectively transfer users’ rating preferences from the source domain to the target domain. Experimental results show that the proposed method can significantly improve the recommendation performance.

Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

Science.gov (United States)

Wu, Dongrui; Lance, Brent J; Parsons, Thomas D

2013-01-01

Brain-computer interaction (BCI) and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL), active class selection (ACS), and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.

Collaborative filtering for brain-computer interaction using transfer learning and active class selection.

Directory of Open Access Journals (Sweden)

Dongrui Wu

Full Text Available Brain-computer interaction (BCI and physiological computing are terms that refer to using processed neural or physiological signals to influence human interaction with computers, environment, and each other. A major challenge in developing these systems arises from the large individual differences typically seen in the neural/physiological responses. As a result, many researchers use individually-trained recognition algorithms to process this data. In order to minimize time, cost, and barriers to use, there is a need to minimize the amount of individual training data required, or equivalently, to increase the recognition accuracy without increasing the number of user-specific training samples. One promising method for achieving this is collaborative filtering, which combines training data from the individual subject with additional training data from other, similar subjects. This paper describes a successful application of a collaborative filtering approach intended for a BCI system. This approach is based on transfer learning (TL, active class selection (ACS, and a mean squared difference user-similarity heuristic. The resulting BCI system uses neural and physiological signals for automatic task difficulty recognition. TL improves the learning performance by combining a small number of user-specific training samples with a large number of auxiliary training samples from other similar subjects. ACS optimally selects the classes to generate user-specific training samples. Experimental results on 18 subjects, using both k nearest neighbors and support vector machine classifiers, demonstrate that the proposed approach can significantly reduce the number of user-specific training data samples. This collaborative filtering approach will also be generalizable to handling individual differences in many other applications that involve human neural or physiological data, such as affective computing.

Liquid hydrogen transfer pipes and level regulation systems

International Nuclear Information System (INIS)

Marquet, M.; Prugne, P.; Roubeau, P.

1961-01-01

Describes: 1) Transfer pipes - Plunging rods in liquid hydrogen Dewars; transfer pipes: knee-joint system for quick and accurate positioning of plunging Dewar rods; system's rods: combined valve and rod; valves are activated either by a bulb pressure or by a solenoid automatically or hand controlled. The latter allows intermittent filling. 2) Level regulating systems: Level bulbs: accurate to 1 or 4 m; maximum and minimum level bulbs: automatic control of the liquid hydrogen valve. (author) [fr

Effective Bayesian Transfer Learning

Science.gov (United States)

2010-03-01

the class of algorithms analyzed by Bartlett’s work under task R4). With emphasis on transferring one type of objects to another, (e.g., coffee cups...obstacles, so those are temporarily pruned from the graph. In addition, the start and goal locations may not be currently included in the graph. They carried...Transfer Level 3 Varying shape within class Task A: Instances of an object from the same class. ( Coffee mug) Task B: Instances of a different object

Satellite data transferring subsystem based on system 'Materik'

International Nuclear Information System (INIS)

Belogub, V.P.; Kal'schikov, I.B.; Kirillov, Yu.K.; Kulikov, V.N.; Shumov, A.N.

1998-01-01

One of the most important indicators of successful function of the International Monitoring System is existence of highly reliable communication channels providing transfer data from observation points in a real time scales. Up to present, the most communication channels were provided with existing VF-channels (Voice Frequency) that are relatively low-speedy in transfer process (4.8-9.6 kbit/sec.). In addition, reliability of the channels is insufficient because of many retransmission points. In connection with it, the special control service of MD RF decided to improve the information transfer system (ITS) installed between the observation point and National Data Center (Dubna-city). The improvement of the ITS comprises replacement of wire lines of VF-channels with satellite ones within the framework of the computer-aided satellite communication system (CASCS) M aterik . Besides it was considered to be expedient that the satellite system of data transfer from NPP to the Crisis Center of 'ROSENERGOATOM' Concern would be combined with CASCS M aterik , using the facilities of the Central Earth Station of Satellite Communication (CESSC) in Dubna. Such approach to the creation of Satellite communication has advantages in solution of radiation safety and global monitoring issues

Web-Based Learning Support System

Science.gov (United States)

Fan, Lisa

Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

Wireless Power Transfer System for Rotary Parts Telemetry of Gas Turbine Engine

Directory of Open Access Journals (Sweden)

Xiaoming He

2018-04-01

Full Text Available A novel wireless power transfer approach for the rotary parts telemetry of a gas turbine engine is proposed. The advantages of a wireless power transfer (WPT system in the power supply for the rotary parts telemetry of a gas turbine engine are introduced. By simplifying the circuit of the inductively-coupled WPT system and developing its equivalent circuit model, the mathematical expressions of transfer efficiency and transfer power of the system are derived. A mutual inductance model between receiving and transmitting coils of the WPT system is presented and studied. According to this model, the mutual inductance between the receiving and the transmitting coils can be calculated at different axial distances. Then, the transfer efficiency and transfer power can be calculated as well. Based on the test data, the relationship of the different distances between the two coils, the transfer efficiency, and transfer power is derived. The proper positions where the receiving and transmitting coils are installed in a gas turbine engine are determined under conditions of satisfying the transfer efficiency and transfer power that the telemetry system required.

Self-Oscillating Wireless Power Transfer Systems

OpenAIRE

Tretyakov, Sergei A.; Simovski, Constantin R.; Valagiannopoulos, Constantinos A.; Ra'di, Younes

2017-01-01

Conventional wireless power transfer systems consist of a microwave power generator and transmitter located at one place and a microwave power receiver located at a distance. Here we show that wireless power transfer can be realized as a single distributed microwave generator with an over-the-air feedback, so that the microwave power is generated directly at the place where the energy needs to be delivered. We demonstrate that the use of this paradigm increases efficiency and dramatically red...

On the sample transport time of a pneumatic transfer system

International Nuclear Information System (INIS)

Kondo, Yoshihide

1983-01-01

The counts accumulated in measuring system are affected by the variations in transport time of the sample on cyclic activation experiments with a mechanical sample transfer system. In use of the pneumatic transfer system, which has been set up, the transport time is variable according to the differences as follows: The form, size and weight of samples, the pneumatic pressure and so on. Comprehending the relationships between the transpot time and these variable factors is essentially important to make experiments with this transfer system. (author)

Implementation of a Modular Hands-on Learning Pedagogy: Student Attitudes in a Fluid Mechanics and Heat Transfer Course

Science.gov (United States)

Burgher, J. K.; Finkel, D.; Adesope, O. O.; Van Wie, B. J.

2015-01-01

This study used a within-subjects experimental design to compare the effects of learning with lecture and hands-on desktop learning modules (DLMs) in a fluid mechanics and heat transfer class. The hands-on DLM implementation included the use of worksheets and one of two heat exchangers: an evaporative cooling device and a shell and tube heat…

Technology Transfer: Marketing Tomorrow's Technology

Science.gov (United States)

Tcheng, Erene

1995-01-01

The globalization of the economy and the end of the Cold War have triggered many changes in the traditional practices of U.S. industry. To effectively apply the resources available to the United States, the federal government has firmly advocated a policy of technology transfer between private industry and government labs, in this case the National Aeronautics and Space Administration (NASA). NASA Administrator Daniel Goldin is a strong proponent of this policy and has organized technology transfer or commercialization programs at each of the NASA field centers. Here at Langley Research Center, the Technology Applications Group (TAG) is responsible for facilitating the transfer of Langley developed research and technology to U.S. industry. Entering the program, I had many objectives for my summer research with TAG. Certainly, I wanted to gain a more thorough understanding of the concept of technology transfer and Langley's implementation of a system to promote it to both the Langley community and the community at large. Also, I hoped to become more familiar with Langley's research capabilities and technology inventory available to the public. More specifically, I wanted to learn about the technology transfer process at Langley. Because my mentor is a member of Materials and Manufacturing marketing sector of the Technology Transfer Team, another overriding objective for my research was to take advantage of his work and experience in materials research to learn about the Advanced Materials Research agency wide and help market these developments to private industry. Through the various projects I have been assigned to work on in TAG, I have successfully satisfied the majority of these objectives. Work on the Problem Statement Process for TAG as well as the development of the Advanced Materials Research Brochure have provided me with the opportunity to learn about the technology transfer process from the outside looking in and the inside looking out. Because TAG covers

Multi-center MRI carotid plaque component segmentation using feature normalization and transfer learning

DEFF Research Database (Denmark)

van Engelen, Arna; van Dijk, Anouk C; Truijman, Martine T.B.

2015-01-01

implementation of supervised methods. In this paper we segment carotid plaque components of clinical interest (fibrous tissue, lipid tissue, calcification and intraplaque hemorrhage) in a multicenter MRI study. We perform voxelwise tissue classification by traditional same-center training, and compare results...... not yield significant differences from that reference. We conclude that both extensive feature normalization and transfer learning can be valuable for the development of supervised methods that perform well on different types of datasets.......Automated segmentation of plaque components in carotid artery MRI is important to enable large studies on plaque vulnerability, and for incorporating plaque composition as an imaging biomarker in clinical practice. Especially supervised classification techniques, which learn from labeled examples...

Advanced Machine Learning Emulators of Radiative Transfer Models

Science.gov (United States)

Camps-Valls, G.; Verrelst, J.; Martino, L.; Vicent, J.

2017-12-01

Physically-based model inversion methodologies are based on physical laws and established cause-effect relationships. A plethora of remote sensing applications rely on the physical inversion of a Radiative Transfer Model (RTM), which lead to physically meaningful bio-geo-physical parameter estimates. The process is however computationally expensive, needs expert knowledge for both the selection of the RTM, its parametrization and the the look-up table generation, as well as its inversion. Mimicking complex codes with statistical nonlinear machine learning algorithms has become the natural alternative very recently. Emulators are statistical constructs able to approximate the RTM, although at a fraction of the computational cost, providing an estimation of uncertainty, and estimations of the gradient or finite integral forms. We review the field and recent advances of emulation of RTMs with machine learning models. We posit Gaussian processes (GPs) as the proper framework to tackle the problem. Furthermore, we introduce an automatic methodology to construct emulators for costly RTMs. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of GPs with the accurate design of an acquisition function that favours sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of our emulators in toy examples, leaf and canopy levels PROSPECT and PROSAIL RTMs, and for the construction of an optimal look-up-table for atmospheric correction based on MODTRAN5.

Recommendation System for Adaptive Learning.

Science.gov (United States)

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-01-01

An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

Assessing recall, conceptualization, and transfer capabilities of novice biochemistry students' across learning style preferences as revealed by self-explanations

Science.gov (United States)

Hilsenbeck-Fajardo, Jacqueline L.

2009-08-01

The research described herein is a multi-dimensional attempt to measure student's abilities to recall, conceptualize, and transfer fundamental and dynamic protein structure concepts as revealed by their own diagrammatic (pictorial) representations and written self-explanations. A total of 120 participants enrolled in a 'Fundamentals of Biochemistry' course contributed to this mixed-methodological study. The population of interest consisted primarily of pre-nursing and sport and exercise science majors. This course is typically associated with a high (researcher with an ideal context in which to apply novel transfer assessment strategies. In the past, students within this population have reported very little chemistry background. In the following study, student-generated diagrammatic representations and written explanations were coded thematically using a highly objective rubric that was designed specifically for this study. Responses provided by the students were characterized on the macroscopic, microscopic, molecular-level, and integrated scales. Recall knowledge gain (i.e., knowledge that was gained through multiple-choice questioning techniques) was quantitatively correlated to learning style preferences (i.e., high-object, low-object, and non-object). Quantitative measures revealed that participants tended toward an object (i.e., snapshot) -based visualization preference, a potentially limiting factor in their desire to consider dynamic properties of fundamental biochemical contexts such as heat-induced protein denaturation. When knowledge transfer was carefully assessed within the predefined context, numerous misconceptions pertaining to the fundamental and dynamic nature of protein structure were revealed. Misconceptions tended to increase as the transfer model shifted away from the context presented in the original learning material. Ultimately, a fundamentally new, novel, and unique measure of knowledge transfer was developed as a main result of this study

Transfer of Short-Term Motor Learning across the Lower Limbs as a Function of Task Conception and Practice Order

Science.gov (United States)

Stockel, Tino; Wang, Jinsung

2011-01-01

Interlimb transfer of motor learning, indicating an improvement in performance with one limb following training with the other, often occurs asymmetrically (i.e., from non-dominant to dominant limb or vice versa, but not both). In the present study, we examined whether interlimb transfer of the same motor task could occur asymmetrically and in…

Convolutional neural network with transfer learning for rice type classification

Science.gov (United States)

Patel, Vaibhav Amit; Joshi, Manjunath V.

2018-04-01

Presently, rice type is identified manually by humans, which is time consuming and error prone. Therefore, there is a need to do this by machine which makes it faster with greater accuracy. This paper proposes a deep learning based method for classification of rice types. We propose two methods to classify the rice types. In the first method, we train a deep convolutional neural network (CNN) using the given segmented rice images. In the second method, we train a combination of a pretrained VGG16 network and the proposed method, while using transfer learning in which the weights of a pretrained network are used to achieve better accuracy. Our approach can also be used for classification of rice grain as broken or fine. We train a 5-class model for classifying rice types using 4000 training images and another 2- class model for the classification of broken and normal rice using 1600 training images. We observe that despite having distinct rice images, our architecture, pretrained on ImageNet data boosts classification accuracy significantly.

Approaches to modelling radionuclide transfer in agricultural systems

International Nuclear Information System (INIS)

Mitchell, N. G.

1995-01-01

Radiological dose assessment requires information describing the concentration and distribution of radionuclides in the environment. This information can be obtained from monitoring but is also evaluated with the aid of mathematical models. In such models the pathways of radionuclides from the release point to man are described in terms of transfer between compartments. The main pathways to be considered include: deposition to vegetation and soils; transfer from soil-to-plant; uptake and turnover in domestic animals; and, intake by man. The development of mathematical models for simulating transfer via these pathways depends on: an understanding of the system under study, in particular for those processes that are most important in the overall transfer to man; the availability of data to determine the structure and parameters for the model; the computing systems available; the knowledge of the user of the model; and, the application of the model. (author)

ENHANCING STUDENTS‟ MOTIVATION AND ACHIEVEMENT IN LEARNING GRAMMAR THROUGH CONTEXTUAL TEACHING AND LEARNING THROUGH RELATING, EXPERIENCING, APPLYING, COOPERATING AND TRANSFERRING (REACT STRATEGY

Directory of Open Access Journals (Sweden)

Mashlihatul Umami Umami

2017-04-01

Full Text Available This research addresses the issue of whether Contextual Teaching and Learning (CTL through REACT (Relating, Experiencing, Applying, Cooperating and Transferring strategy is able to enhance motivation and achievement of English Department students‘ in learning grammar. The researcher uses a classroom action research in which it was held for about two cycles. The instruments of collecting the data are observation, rubric, questionaire and test. The researcher analyzes the data using three steps, i.e. students‘ motivation to learn are analyzed by the sheet of observation, each of individuals is also analyzed by fulfilling the questionnaire of self assessment, the progress of students‘ motivation and achievement are all monitored by rubric assessment tool, seven components of REACT strategy in learning is also recorded by the sheets of observation and the statistical analysis using t-test measures the improvement occurred. In addition, the researcher prepares field note and questionnaire to monitor the process of learning. Based on the results of qualitative-quantitative analysis, it can be found that the use of CTL approach especially using project based and cooperative learning improves the students‘ motivation and achievement in learning grammar.

ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

Directory of Open Access Journals (Sweden)

Vasiliy M. Trembach

2016-01-01

Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.

Selective automation and skill transfer in medical robotics: a demonstration on surgical knot-tying.

Science.gov (United States)

Knoll, Alois; Mayer, Hermann; Staub, Christoph; Bauernschmitt, Robert

2012-12-01

Transferring non-trivial human manipulation skills to robot systems is a challenging task. There have been a number of attempts to design research systems for skill transfer, but the level of the complexity of the actual skills transferable to the robot was rather limited, and delicate operations requiring a high dexterity and long action sequences with many sub-operations were impossible to transfer. A novel approach to human-machine skill transfer for multi-arm robot systems is presented. The methodology capitalizes on the metaphor of 'scaffolded learning', which has gained widespread acceptance in psychology. The main idea is to formalize the superior knowledge of a teacher in a certain way to generate support for a trainee. In our case, the scaffolding is constituted by abstract patterns, which facilitate the structuring and segmentation of information during 'learning by demonstration'. The actual skill generalization is then based on simulating fluid dynamics. The approach has been successfully evaluated in the medical domain for the delicate task of automated knot-tying for suturing with standard surgical instruments and a realistic minimally invasive robotic surgery system. Copyright © 2012 John Wiley & Sons, Ltd.

Establishment of a Learning Management System

International Nuclear Information System (INIS)

Han, K. W.; Kim, Y. T.; Lee, E. J.; Min, B. J.

2006-01-01

A web-based learning management system (LMS) has been established to address the need of customized education and training of Nuclear Training Center (NTC) of KAERI. The LMS is designed to deal with various learning types (e.g. on-line, off-line and blended) and a practically comprehensive learning activity cycle (e.g. course preparation, registration, learning, and postlearning) as well as to be user-friendly. A test with an example course scenario on the established system has shown its satisfactory performance. This paper discusses details of the established webbased learning management system in terms of development approach and functions of the LMS

E-learning Paradigms and The Development of E-learning Strategy

DEFF Research Database (Denmark)

Duus, Henrik Johannsen

2006-01-01

The e-learning area is characterized by a magnitude of different products, systems and approaches. The variations can also be observed in differences in the views and notions of e-learning among business people, researchers and journalists. This article attempts to disentangle the area by using...... economic and sociological theories, the theories of marketing management and strategy as well as practical experience gained by the author while working with leading edge suppliers of e-learning. On this basis, a distinction between knowledge creation e-learning and knowledge transfer e-learning....... The selection of which paradigm to use in the development of an e-learning strategy may prove crucial for success. Implications for the development of an e-learning strategy in businesses and learning institutions are outlined....

Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

Science.gov (United States)

2008-09-01

Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

Cascade Convolutional Neural Network Based on Transfer-Learning for Aircraft Detection on High-Resolution Remote Sensing Images

Directory of Open Access Journals (Sweden)

Bin Pan

2017-01-01

Full Text Available Aircraft detection from high-resolution remote sensing images is important for civil and military applications. Recently, detection methods based on deep learning have rapidly advanced. However, they require numerous samples to train the detection model and cannot be directly used to efficiently handle large-area remote sensing images. A weakly supervised learning method (WSLM can detect a target with few samples. However, it cannot extract an adequate number of features, and the detection accuracy requires improvement. We propose a cascade convolutional neural network (CCNN framework based on transfer-learning and geometric feature constraints (GFC for aircraft detection. It achieves high accuracy and efficient detection with relatively few samples. A high-accuracy detection model is first obtained using transfer-learning to fine-tune pretrained models with few samples. Then, a GFC region proposal filtering method improves detection efficiency. The CCNN framework completes the aircraft detection for large-area remote sensing images. The framework first-level network is an image classifier, which filters the entire image, excluding most areas with no aircraft. The second-level network is an object detector, which rapidly detects aircraft from the first-level network output. Compared with WSLM, detection accuracy increased by 3.66%, false detection decreased by 64%, and missed detection decreased by 23.1%.

Authoring Systems Delivering Reusable Learning Objects

Directory of Open Access Journals (Sweden)

George Nicola Sammour

2009-10-01

Full Text Available A three layer e-learning course development model has been defined based on a conceptual model of learning content object. It starts by decomposing the learning content into small chunks which are initially placed in a hierarchic structure of units and blocks. The raw content components, being the atomic learning objects (ALO, were linked to the blocks and are structured in the database. We set forward a dynamic generation of LO's using re-usable e-learning raw materials or ALO’s In that view we need a LO authoring/ assembling system fitting the requirements of interoperability and reusability and starting from selecting the raw learning content from the learning materials content database. In practice authoring systems are used to develop e-learning courses. The company EDUWEST has developed an authoring system that is database based and will be SCORM compliant in the near future.

CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

Directory of Open Access Journals (Sweden)

Yu. B. Popova

2016-01-01

Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

Transfer Effect of Speech-sound Learning on Auditory-motor Processing of Perceived Vocal Pitch Errors.

Science.gov (United States)

Chen, Zhaocong; Wong, Francis C K; Jones, Jeffery A; Li, Weifeng; Liu, Peng; Chen, Xi; Liu, Hanjun

2015-08-17

Speech perception and production are intimately linked. There is evidence that speech motor learning results in changes to auditory processing of speech. Whether speech motor control benefits from perceptual learning in speech, however, remains unclear. This event-related potential study investigated whether speech-sound learning can modulate the processing of feedback errors during vocal pitch regulation. Mandarin speakers were trained to perceive five Thai lexical tones while learning to associate pictures with spoken words over 5 days. Before and after training, participants produced sustained vowel sounds while they heard their vocal pitch feedback unexpectedly perturbed. As compared to the pre-training session, the magnitude of vocal compensation significantly decreased for the control group, but remained consistent for the trained group at the post-training session. However, the trained group had smaller and faster N1 responses to pitch perturbations and exhibited enhanced P2 responses that correlated significantly with their learning performance. These findings indicate that the cortical processing of vocal pitch regulation can be shaped by learning new speech-sound associations, suggesting that perceptual learning in speech can produce transfer effects to facilitating the neural mechanisms underlying the online monitoring of auditory feedback regarding vocal production.

Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

Science.gov (United States)

Mihai, Gabroveanu

2015-09-01

Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

Fuel assembly transfer and storage system for nuclear reactors

International Nuclear Information System (INIS)

Allain, Albert; Thomas, Claude.

1981-01-01

Transfer and storage system on a site comprising several reactors and at least one building housing the installations common to all these reactors. The system includes: transfer and storage modules for the fuel assemblies comprising a containment capable of containing several assemblies carried on a transport vehicle, a set of tracks for the modules between the reactors and the common installations, handling facilities associated with each reactor for moving the irradiated assemblies from the reactor to a transfer module placed in loading position on a track serving the reactor and conversely to move the new assemblies from the transfer module to the reactor, and at least one handling facility located in the common installation building for loading the modules with new assemblies [fr

The effects of practice schedule and critical thinking prompts on learning and transfer of complex judgment

NARCIS (Netherlands)

Helsdingen, Anne; Van Gog, Tamara; Van Merriënboer, Jeroen

2010-01-01

Helsdingen, A. S., Van Gog, T., & Van Merriënboer, J. J. G. (2011). The effects of practice schedule and critical thinking prompts on learning and transfer of complex judgment task. Journal of Educational Psychology, 103(2), 383-398. doi:10.1037/a0022370

Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning

Science.gov (United States)

Shi, Bibo; Hou, Rui; Mazurowski, Maciej A.; Grimm, Lars J.; Ren, Yinhao; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2018-02-01

Purpose: To determine whether domain transfer learning can improve the performance of deep features extracted from digital mammograms using a pre-trained deep convolutional neural network (CNN) in the prediction of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core needle biopsy. Method: In this study, we collected digital mammography magnification views for 140 patients with DCIS at biopsy, 35 of which were subsequently upstaged to invasive cancer. We utilized a deep CNN model that was pre-trained on two natural image data sets (ImageNet and DTD) and one mammographic data set (INbreast) as the feature extractor, hypothesizing that these data sets are increasingly more similar to our target task and will lead to better representations of deep features to describe DCIS lesions. Through a statistical pooling strategy, three sets of deep features were extracted using the CNNs at different levels of convolutional layers from the lesion areas. A logistic regression classifier was then trained to predict which tumors contain occult invasive disease. The generalization performance was assessed and compared using repeated random sub-sampling validation and receiver operating characteristic (ROC) curve analysis. Result: The best performance of deep features was from CNN model pre-trained on INbreast, and the proposed classifier using this set of deep features was able to achieve a median classification performance of ROC-AUC equal to 0.75, which is significantly better (p<=0.05) than the performance of deep features extracted using ImageNet data set (ROCAUC = 0.68). Conclusion: Transfer learning is helpful for learning a better representation of deep features, and improves the prediction of occult invasive disease in DCIS.

Learned control over spinal nociception: Transfer and stability of training success in a long-term study.

Science.gov (United States)

Bäumler, Maximilian; Feller, Moritz; Krafft, Stefanie; Schiffer, Manuela; Sommer, Jens; Straube, Andreas; Weinges, Fabian; Ruscheweyh, Ruth

2017-12-01

Healthy subjects can learn to use cognitive-emotional strategies to suppress their spinal nociception, quantified by the nociceptive flexor reflex (RIII reflex), when given visual RIII feedback. This likely reflects learned activation of descending pain inhibition. Here, we investigated if training success persists 4 and 8 months after the end of RIII feedback training, and if transfer (RIII suppression without feedback) is possible. 18 and 8 subjects who had successfully completed feedback training were investigated 4 and 8 months later. At 4 months, RIII suppression during feedback and transfer was similar to that achieved at the final RIII feedback training session (to 50 ± 22%, 53 ± 21% and 52 ± 21% of baseline, all differences n.s.). At 8 months, RIII suppression was somewhat (not significantly) smaller in the feedback run (to 64 ± 17%) compared to the final training session (56 ± 19%). Feedback and transfer runs were similar (to 64 ± 17% vs. 68 ± 24%, n.s.). Concomitant reductions in pain intensity ratings were stable at 4 and 8 months. RIII feedback training success was completely maintained after 4 months, and somewhat attenuated 8 months after training. Transfer was successful. These results are an important pre-requisite for application of RIII feedback training in the context of clinical pain. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Transfer Efficiency Analysis of Wireless Power Transfer System under Frequency Drift

DEFF Research Database (Denmark)

Huang, Shoudao; Li, Zhongqi; Lu, Kaiyuan

2015-01-01

Magnetic resonant wireless power transfer (WPT) is an emerging technology that may create new applications for wireless power charging. However, low efficiency resulting from resonant frequency drift is a main obstructing factor for promoting this technology. In this paper, the system efficiency...

Fuel transfer system for a nuclear reactor

International Nuclear Information System (INIS)

Katz, L.R.; Marshall, J.R.; Desmarchais, W.E.

1977-01-01

Disclosed is a fuel transfer system for moving nuclear reactor fuel assemblies from a new fuel storage pit to a containment area containing the nuclear reactor, and for transferring spent fuel assemblies under water from the reactor to a spent fuel storage area. The system includes an underwater track which extends through a wall dividing the fuel building from the reactor containment and a car on the track serves as the vehicle for moving fuel assemblies between these two areas. The car is driven by a motor and linkage extending from an operating deck to a chain belt drive on the car. A housing pivotally mounted at its center on the car is hydraulically actuated to vertically receive a fuel assembly which then is rotated to a horizontal position to permit movement through the wall between the containment and fuel building areas. Return to the vertical position provides for fuel assembly removal and the reverse process is repeated when transferring an assembly in the opposite direction. Limit switches used in controlling operation of the system are designed to be replaced from the operating deck when necessary by tools designed for this purpose. 5 claims, 8 figures

Accident on the gas transfer system

International Nuclear Information System (INIS)

Heugel, J.

1991-10-01

An accident has happened on the Vivitron gas transfer system on the 7 th August 1991. This report presents the context, facts and inquiries, analyses the reasons and explains also how the repairing has been effected

Analysing CMS transfers using Machine Learning techniques

CERN Document Server

Diotalevi, Tommaso

2016-01-01

LHC experiments transfer more than 10 PB/week between all grid sites using the FTS transfer service. In particular, CMS manages almost 5 PB/week of FTS transfers with PhEDEx (Physics Experiment Data Export). FTS sends metrics about each transfer (e.g. transfer rate, duration, size) to a central HDFS storage at CERN. The work done during these three months, here as a Summer Student, involved the usage of ML techniques, using a CMS framework called DCAFPilot, to process this new data and generate predictions of transfer latencies on all links between Grid sites. This analysis will provide, as a future service, the necessary information in order to proactively identify and maybe fix latency issued transfer over the WLCG.

THE CONCEPT OF TRANSFER PRICING SYSTEM IN RUSSIAN FEDERATION

Directory of Open Access Journals (Sweden)

Alexey S. Besfamilnyy

2016-01-01

Full Text Available The article presents the author's denition of transfer prices and transfer pricing based on the analysis of the current legislation in Russia as well as on current economic practice. Considered state regulation of transfer pricing for the purpose of harmonization of relationship between government and business. Given the denition of the transfer pricing system in Russian Federation and the description of its main parts and connections between them, necessary for effective functioning.

Student Modelling in Adaptive E-Learning Systems

Directory of Open Access Journals (Sweden)

Clemens Bechter

2011-09-01

Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

Cooperative heat transfer and ground coupled storage system

Science.gov (United States)

Metz, P.D.

A cooperative heat transfer and ground coupled storage system wherein collected solar heat energy is ground stored and permitted to radiate into the adjacent ground for storage therein over an extended period of time when such heat energy is seasonally maximally available. Thereafter, when said heat energy is seasonally minimally available and has propagated through the adjacent ground a substantial distance, the stored heat energy may be retrieved by a circumferentially arranged heat transfer means having a high rate of heat transfer.

Micro Learning: A Modernized Education System

Directory of Open Access Journals (Sweden)

Omer Jomah

2016-03-01

Full Text Available Learning is an understanding of how the human brain is wired to learning rather than to an approach or a system. It is one of the best and most frequent approaches for the 21st century learners. Micro learning is more interesting due to its way of teaching and learning the content in a small, very specific burst. Here the learners decide what and when to learn. Content, time, curriculum, form, process, mediality, and learning type are the dimensions of micro learning. Our paper will discuss about micro learning and about the micro-content management system. The study will reflect the views of different users, and will analyze the collected data. Finally, it will be concluded with its pros and cons. 

Control of pneumatic transfer system for neutron activation analysis

International Nuclear Information System (INIS)

Jung, H. S.; Chung, Y. S.; Wu, J. S.; Kim, H. K.; Choi, Y. S.; Kim, S. H.; Moon, J. H.; Baek, S. Y.

2000-06-01

Pneumatic transfer system(PTS) is one of the facilities to be used in irradiation of target materials for neutron activation analysis(NAA) in the research reactor. There are two systems the manual and the automatic system in PTS of HANARO research reactor. The pneumatic transfer system consists of many devices, sends and loads the capsules from NAA laboratory into three holes in the reflector tank of reactor and retrieves irradiated capsules after irradiation. This report describes the part's design, control system and the operation procedures. All the algorithm described in the text will be used for maintenance and upgrading

Control of pneumatic transfer system for neutron activation analysis

Energy Technology Data Exchange (ETDEWEB)

Jung, H. S.; Chung, Y. S.; Wu, J. S.; Kim, H. K.; Choi, Y. S.; Kim, S. H.; Moon, J. H.; Baek, S. Y

2000-06-01

Pneumatic transfer system(PTS) is one of the facilities to be used in irradiation of target materials for neutron activation analysis(NAA) in the research reactor. There are two systems the manual and the automatic system in PTS of HANARO research reactor. The pneumatic transfer system consists of many devices, sends and loads the capsules from NAA laboratory into three holes in the reflector tank of reactor and retrieves irradiated capsules after irradiation. This report describes the part's design, control system and the operation procedures. All the algorithm described in the text will be used for maintenance and upgrading.

Ray transference of a system with radial gradi- ent index

Directory of Open Access Journals (Sweden)

W. F. Harris

2012-12-01

Full Text Available The ray transference is central to the understanding of the first-order optical character of an optical system including the visual optical system of the eye.  It can be calculated for dioptric and catadioptric systems from a knowledge of curvatures, tilts and spacing of surfaces in the system provided the material between successive surfaces has a uniform index of refraction.  However the index of the natural lens of the eye is not uniform but varies with position.  There is a need, therefore, for a method of calculating the transference of systems containing such gradient-index elements.  As a first step this paper shows that the transference of elements in which the index varies radially can be obtained directly from published formulae.  The transferences of radial-gradient systems are examined.  Expressions are derived for several properties including the power, the front- and back-surface powers and the locations of the cardinal points.  Equations are obtained for rays through such systems and for the locations of images of object points through them.  Numerical examples are presented in the appen-dix. (S Afr Optom 2012 71(2 57-63

The direction of bilateral transfer depends on the performance parameter.

Science.gov (United States)

Pan, Zhujun; van Gemmert, Arend W A

2013-10-01

To acquire a more comprehensive understanding of the learning benefits associated with bilateral transfer and to gain knowledge of possible mechanisms behind bilateral transfer, we investigated the transfer direction of several parameters which are assumed to represent important features of movement control in a visuo-motor task. During the study, participants learned a multidirectional point-to-point drawing task in which the visual feedback was rotated 45° and the gain was increased. Performance changes of the untrained hand in movement time, trajectory length, normalized jerk, initial direction error, ratio of the primary sub-movement time to the total movement time, and the accuracy of the aiming movement after the primary sub-movement were investigated as indices of learning from bilateral transfer. The results showed that performance parameters related to the initial production of the movement, such as the initial direction, ratio of primary sub-movement to the total movement time, and movement accuracy after the primary sub-movement, only transferred to the non-dominant, while hand performance variables related to the overall outcome, such as movement duration, movement smoothness, and trajectory length, transferred in both directions. The findings of the current study support the basic principle of the "dynamic dominance model" because it is suggested that overall improvements in the non-dominant system are controlled by trajectory parameters in visuo-motor tasks, which resulted in transference of the afore mentioned production parameters to rather occur to the non-dominant hand as opposed to transference to the dominant hand. Published by Elsevier B.V.

A Group-learning Approach to Academic and Transferable Skills through an Exercise in the Global Positioning System.

Science.gov (United States)

Brown, Giles H.

1999-01-01

Describes a project based on the Global Positioning System (GPS) that offers students a chance to design and implement a mini-research program to prepare them for an undergraduate research project. Discusses the context of the GPS exercise, teaching and learning outcomes, and advantages and evaluation of the exercise. (CMK)

When Creativity Met Transfer: Increasing Creativity and Transfer by Controlling the Styles of Processing

Science.gov (United States)

Kaniel, Shlomo

2013-01-01

The primary purpose of this article is to combine both transfer of learning (hereafter, transfer) and creativity into similar processes that can increase the products of transfer and creativity. Both transfer and creativity operate within reciprocal relationships between memory storage and working memory. Moreover, they are also based on moving…

Learning Management Systems and Comparison of Open Source Learning Management Systems and Proprietary Learning Management Systems

Directory of Open Access Journals (Sweden)

Yücel Yılmaz

2016-04-01

Full Text Available The concept of learning has been increasingly gaining importance for individuals, businesses and communities in the age of information. On the other hand, developments in information and communication technologies take effect in the field of learning activities. With these technologies, barriers of time and space against the learning activities largely disappear and these technologies make it easier to carry out these activities more effectively. There remain a lot of questions regarding selection of learning management system (LMS to be used for the management of e-learning processes by all organizations conducing educational practices including universities, companies, non-profit organizations, etc. The main questions are as follows: Shall we choose open source LMS or commercial LMS? Can the selected LMS meet existing needs and future potential needs for the organization? What are the possibilities of technical support in the management of LMS? What kind of problems may be experienced in the use of LMS and how can these problems be solved? How much effective can officials in the organization be in the management of LMS? In this study, primarily e-learning and the concept of LMS will be discussed, and in the next section, as for answers to these questions, open source LMSs and centrally developed LMSs will be examined and their advantages and disadvantages relative to each other will be discussed.

Transfer Function Control for Biometric Monitoring System

Science.gov (United States)

Chmiel, Alan J. (Inventor); Humphreys, Bradley T. (Inventor); Grodinsky, Carlos M. (Inventor)

2015-01-01

A modular apparatus for acquiring biometric data may include circuitry operative to receive an input signal indicative of a biometric condition, the circuitry being configured to process the input signal according to a transfer function thereof and to provide a corresponding processed input signal. A controller is configured to provide at least one control signal to the circuitry to programmatically modify the transfer function of the modular system to facilitate acquisition of the biometric data.

Resolving the Problem of Intelligent Learning Content in Learning Management Systems

Science.gov (United States)

Rey-Lopez, Marta; Brusilovsky, Peter; Meccawy, Maram; Diaz-Redondo, Rebeca; Fernandez-Vilas, Ana; Ashman, Helen

2008-01-01

Current e-learning standardization initiatives have put much effort into easing interoperability between systems and the reusability of contents. For this to be possible, one of the most relevant areas is the definition of a run-time environment, which allows Learning Management Systems to launch, track and communicate with learning objects.…

Evaluating Usability of E-Learning Systems in Universities

OpenAIRE

Nicholas Kipkurui Kiget; Professor G. Wanyembi; Anselemo Ikoha Peters

2014-01-01

The use of e-learning systems has increased significantly in the recent times. E-learning systems are supplementing teaching and learning in universities globally. Kenyan universities have adopted e-learning technologies as means for delivering course content. However despite adoption of these systems, there are considerable challenges facing the usability of the systems. Lecturers and students have different perceptions in regard to the usability of e-learning systems. The aim of this study ...

Feedback Design Patterns for Math Online Learning Systems

Science.gov (United States)

Inventado, Paul Salvador; Scupelli, Peter; Heffernan, Cristina; Heffernan, Neil

2017-01-01

Increasingly, computer-based learning systems are used by educators to facilitate learning. Evaluations of several math learning systems show that they result in significant student learning improvements. Feedback provision is one of the key features in math learning systems that contribute to its success. We have recently been uncovering feedback…

End-to-End Airplane Detection Using Transfer Learning in Remote Sensing Images

Directory of Open Access Journals (Sweden)

Zhong Chen

2018-01-01

Full Text Available Airplane detection in remote sensing images remains a challenging problem due to the complexity of backgrounds. In recent years, with the development of deep learning, object detection has also obtained great breakthroughs. For object detection tasks in natural images, such as the PASCAL (Pattern Analysis, Statistical Modelling and Computational Learning VOC (Visual Object Classes Challenge, the major trend of current development is to use a large amount of labeled classification data to pre-train the deep neural network as a base network, and then use a small amount of annotated detection data to fine-tune the network for detection. In this paper, we use object detection technology based on deep learning for airplane detection in remote sensing images. In addition to using some characteristics of remote sensing images, some new data augmentation techniques have been proposed. We also use transfer learning and adopt a single deep convolutional neural network and limited training samples to implement end-to-end trainable airplane detection. Classification and positioning are no longer divided into multistage tasks; end-to-end detection attempts to combine them for optimization, which ensures an optimal solution for the final stage. In our experiment, we use remote sensing images of airports collected from Google Earth. The experimental results show that the proposed algorithm is highly accurate and meaningful for remote sensing object detection.

The block transfer system

International Nuclear Information System (INIS)

Bradish, G.J. III; Reid, A.E.

1986-01-01

The central instrumentation control and data acquisition (CICADA) computer system is comprised of a functionally distributed hierarchical network of thirteen (13) 32-bit mini-computers that are the heart of the control, monitoring, data collection and data analysis for the tokamak fusion test reactor (TFTR). The CICADA system was designed with the goal of providing complete control, monitoring, and data acquisition for TFTR, which includes the acquisition and storage of 20M points of data within a five-minute shot cycle. It was realized early in the system design that in order to meet this goal an ancillary system would have to be provided to supplement the subsystem CAMAC systems that, due to the relatively slow throughput of the serial highways and the overhead of relaying data to the central facilities within a star network, would not provide the necessary throughput. The authors discuss how the block transfer system provided a means of moving data directly from the CAMAC crate to the application running on the central facility computers

Radiative heat transfer in low-dimensional systems -- microscopic mode

Science.gov (United States)

Woods, Lilia; Phan, Anh; Drosdoff, David

2013-03-01

Radiative heat transfer between objects can increase dramatically at sub-wavelength scales. Exploring ways to modulate such transport between nano-systems is a key issue from fundamental and applied points of view. We advance the theoretical understanding of radiative heat transfer between nano-objects by introducing a microscopic model, which takes into account the individual atoms and their atomic polarizabilities. This approach is especially useful to investigate nano-objects with various geometries and give a detailed description of the heat transfer distribution. We employ this model to study the heat exchange in graphene nanoribbon/substrate systems. Our results for the distance separations, substrates, and presence of extended or localized defects enable making predictions for tailoring the radiative heat transfer at the nanoscale. Financial support from the Department of Energy under Contract No. DE-FG02-06ER46297 is acknowledged.

System Transfer, Education, and Development in Mozambique

Directory of Open Access Journals (Sweden)

Jose Cossa

2011-03-01

Full Text Available In this study the author used conceptual historical method to assess the phenomenon of system transfer and the association between education and development in Mozambique. The assessment was administered through critical analysis of documents pertaining to the Salazar (1924-1966, Machel (1975-1986, and Chissano (1986-2005 administrations. The findings were that (a the colonial government created economic and educational systems for colonizing Mozambique, whereas the Machel and Chissano administrations adapted foreign systems of government and education (i.e., Socialism, Soviet, Democracy, Portuguese, etc., to their particular context without altering the inherent theoretical basis of the systems transferred; (b the Machel and Chissano administrations, implicitly or explicitly, perceived the relationship between education and development as circular causality rather than a unidirectional linear causality, while the Salazar administration perceived it as unidirectional linear causality; and (c while the Machel and Chissano administrations focused on primary education, literacy campaigns, and education of women and girls, they differed in the reasons for such focus.

Learning in context: identifying gaps in research on the transfer of medical communication skills to the clinical workplace.

Science.gov (United States)

van den Eertwegh, Valerie; van Dulmen, Sandra; van Dalen, Jan; Scherpbier, Albert J J A; van der Vleuten, Cees P M

2013-02-01

In order to reduce the inconsistencies of findings and the apparent low transfer of communication skills from training to medical practice, this narrative review identifies some main gaps in research on medical communication skills training and presents insights from theories on learning and transfer to broaden the view for future research. Relevant literature was identified using Pubmed, GoogleScholar, Cochrane database, and Web of Science; and analyzed using an iterative procedure. Research findings on the effectiveness of medical communication training still show inconsistencies and variability. Contemporary theories on learning based on a constructivist paradigm offer the following insights: acquisition of knowledge and skills should be viewed as an ongoing process of exchange between the learner and his environment, so called lifelong learning. This process can neither be atomized nor separated from the context in which it occurs. Four contemporary approaches are presented as examples. The following shift in focus for future research is proposed: beyond isolated single factor effectiveness studies toward constructivist, non-reductionistic studies integrating the context. Future research should investigate how constructivist approaches can be used in the medical context to increase effective learning and transition of communication skills. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

Science.gov (United States)

Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

2017-01-01

Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

Comment on 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study'.

Science.gov (United States)

Valdes, Gilmer; Interian, Yannet

2018-03-15

The application of machine learning (ML) presents tremendous opportunities for the field of oncology, thus we read 'Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study' with great interest. In this article, the authors used state of the art techniques: a pre-trained convolutional neural network (VGG-16 CNN), transfer learning, data augmentation, drop out and early stopping, all of which are directly responsible for the success and the excitement that these algorithms have created in other fields. We believe that the use of these techniques can offer tremendous opportunities in the field of Medical Physics and as such we would like to praise the authors for their pioneering application to the field of Radiation Oncology. That being said, given that the field of Medical Physics has unique characteristics that differentiate us from those fields where these techniques have been applied successfully, we would like to raise some points for future discussion and follow up studies that could help the community understand the limitations and nuances of deep learning techniques.

The cerebellum: a neuronal learning machine?

Science.gov (United States)

Raymond, J. L.; Lisberger, S. G.; Mauk, M. D.

1996-01-01

Comparison of two seemingly quite different behaviors yields a surprisingly consistent picture of the role of the cerebellum in motor learning. Behavioral and physiological data about classical conditioning of the eyelid response and motor learning in the vestibulo-ocular reflex suggests that (i) plasticity is distributed between the cerebellar cortex and the deep cerebellar nuclei; (ii) the cerebellar cortex plays a special role in learning the timing of movement; and (iii) the cerebellar cortex guides learning in the deep nuclei, which may allow learning to be transferred from the cortex to the deep nuclei. Because many of the similarities in the data from the two systems typify general features of cerebellar organization, the cerebellar mechanisms of learning in these two systems may represent principles that apply to many motor systems.

The use of mathematics and electric circuit simulator software in the learning process of wireless power transfer for electrical engineering students

Science.gov (United States)

Habibi, Muhammad Afnan; Fall, Cheikh; Setiawan, Eko; Hodaka, Ichijo; Wijono, Hasanah, Rini Nur

2017-09-01

Wireless Power Transfer (WPT) isa technique to deliver the electrical power from the source to the load without using wires or conductors. The physics of WPT is well known and basically learned as a course in high school. However, it is very recent that WPT is useful in practical situation: it should be able to transfer electric power in a significant efficiency. It means that WPT requires not much knowledge to university students but may attract students because of cutting edge technique of WPT. On the other hand, phenomena of WPT is invisible and sometimes difficult to imagine. The objective of this paper is to demonstrate the use of mathematics and an electric circuit simulator using MATHEMATICA software and LT-SPICE software in designing a WPT system application. It brings to a conclusion that the students as well the designer can take the benefit of the proposed method. By giving numerical values to circuit parameters, students acquires the power output and efficiency of WPT system. The average power output as well as the efficiency of the designed WPT which resonance frequency set on the system,leads it to produce high output power and better efficiency.

An rf communications system for the West Valley transfer cart

International Nuclear Information System (INIS)

Crutcher, R.I.; Moore, M.R.

1993-01-01

A prototype radio frequency communications system for digital data was designed and built by Oak Ridge National Laboratory for use in controlling the vitrification facility transfer cart at the West Valley Nuclear Services facility in New York. The communications system provides bidirectional wireless data transfer between the operator control station and the material transfer cart. The system was designed to operate in radiation fields of 10 4 R/h while withstanding a total integrated dose of 10 7 R of gamma radiation. Implementation of antenna spatial diversity, automatic gain control, and spectral processing improves operation in the reflective environment of the metal-lined reprocessing cells

Inexplicit Learning: Transferring Knowledge through Visual and Emulative practices

Directory of Open Access Journals (Sweden)

Koumudi Patil

2017-12-01

Full Text Available This study attempts to understand how expert knowledge is transmitted in the absence or lack of explicit and formal means of knowledge acquisition, with particular interest in the evolved relationship of a master-apprentice, observable in pockets of traditional communities of practice. An ethnographic study based on content analysis of the transcriptions of members of a craft community from Varanasi, India has been used to strengthen the undermined pedagogical role of observation and emulation in the transfer of inexplicit knowledge. It is argued that in-situ observation and emulation foster situations for facilitating co-production of knowledge, further implying co-authorship. Gaining community membership in craft communities is not merely a matter of gaining a professional degree; instead, it is a slow process of enculturation.Keywords: Observation, Emulation, Inexplicit learning, Master-apprentice. Communities of Practice

Indirect learning control for nonlinear dynamical systems

Science.gov (United States)

Ryu, Yeong Soon; Longman, Richard W.

1993-01-01

In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

Overview of the West Valley Vitrification Facility transfer cart control system

International Nuclear Information System (INIS)

Bradley, E.C.; Rupple, F.R.

1993-01-01

Oak Ridge National Laboratory (ORNL) has designed the control system for the West Valley Demonstration Project Vitrification Facility transfer cart. The transfer cart will transfer canisters of vitrified high-level waste remotely within the Vitrification Facility. The control system will operate the cart under battery power by wireless control. The equipment includes cart mounted control electronics, battery charger, control pendants, engineer's console, and facility antennas

An Intelligent System for Determining Learning Style

Science.gov (United States)

Ozdemir, Ali; Alaybeyoglu, Aysegul; Mulayim, Naciye; Uysal, Muhammed

2018-01-01

In this study, an intelligent system which determines learning style of the students is developed to increase success in effective and easy learning. The importance of the proposed software system is to determine convenience degree of the student's learning style. Personal information form and Dunn Learning Style Preference Survey are used to…

Transferring a Teaching Learning Sequence between Two Different Educational Contexts: The Case of Greece and Finland

Science.gov (United States)

Spyrtou, Anna; Lavonen, Jari; Zoupidis, Anastasios; Loukomies, Anni; Pnevmatikos, Dimitris; Juuti, Kalle; Kariotoglou, Petros

2018-01-01

In the present paper, we report on the idea of exchanging educational innovations across European countries aiming to shed light on the following question: how feasible and useful is it to transfer an innovation across different national educational settings? The innovation, in this case, Inquiry-Based Teaching Learning Sequences, is recognized as…

Exploring PCK ability of prospective science teachers in reflective learning on heat and transfer

Science.gov (United States)

Nurmatin, S.; Rustaman, N. Y.

2016-02-01

Learning can be planned by the person him/herself when he or she tries to reflect his/her learning. A study involving prospective science teachers in junior secondary schools was carried out to analyze their ability on Pedagogical Content Knowledge (PCK) in reflective learning after teaching practice. The study was focused especially in creating Pedagogical and Professional Repertoires (PaP-eRs) as part of resource-folios. PaP-eRs as a narrative writing in the learning activities are created by prospective science teachers after lesson plan implementation. Making the narrative writing is intended that prospective science teachers can reflect their learning in teaching. Research subjects are six prospective science teachers who are implementing "Program Pengalaman Lapangan" (PPL) in two junior secondary schools in Bandung, West Java, Indonesia. All of them were assigned by supervisor teachers to teach VII grade students on certain topic "heat and its transfer". Instruments used as a means of collecting data in this study is PaP-eRs. Collected PaP-eRs were then analyzed using PaP-eRs analysis format as instruments for analysis. The result of analyzing PaP-eRs indicates that learning activities, which narrated, involve initial activities, core activities and final activities. However, any activity, which is narrated just superficial as its big line so the narration cannot be, used as reflective learning. It indicates that PCK ability of prospective science teachers in creating narrative writing (PaP-eRs) for reflective learning is still low.

Learning Markov models for stationary system behaviors

DEFF Research Database (Denmark)

Chen, Yingke; Mao, Hua; Jaeger, Manfred

2012-01-01

to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....

A Transfer-Based Framework for Interdisciplinary Communication, Teaching, and Research

Directory of Open Access Journals (Sweden)

Denise Comer

2016-10-01

Full Text Available Transfer consists of the ways in which people reshape, adapt, rethink, and challenge what they understand and learn in one context to other contexts. While transfer is often discussed in relationship to student learning and writing (how students transfer their writing and learning across contexts, transfer also provides a crucial framework for faculty, administrators to use in navigating the dynamic, intersecting, and disparate contexts of academia. A transfer framework invites faculty, administrators, and students to actively engage with, reflect on, and position themselves within and across varying and overlapping domains. Doing so can facilitate increased networks of collaboration, cultivate more robust advances in knowledge and research methods, improve pedagogy, and increase student learning gains.

VIRTUAL LABORATORY IN DISTANCE LEARNING SYSTEM

Directory of Open Access Journals (Sweden)

Е. Kozlovsky

2011-11-01

Full Text Available Questions of designing and a choice of technologies of creation of virtual laboratory for the distance learning system are considered. Distance learning system «Kherson Virtual University» is used as illustration.

Learning a common dictionary for subject-transfer decoding with resting calibration.

Science.gov (United States)

Morioka, Hiroshi; Kanemura, Atsunori; Hirayama, Jun-ichiro; Shikauchi, Manabu; Ogawa, Takeshi; Ikeda, Shigeyuki; Kawanabe, Motoaki; Ishii, Shin

2015-05-01

Brain signals measured over a series of experiments have inherent variability because of different physical and mental conditions among multiple subjects and sessions. Such variability complicates the analysis of data from multiple subjects and sessions in a consistent way, and degrades the performance of subject-transfer decoding in a brain-machine interface (BMI). To accommodate the variability in brain signals, we propose 1) a method for extracting spatial bases (or a dictionary) shared by multiple subjects, by employing a signal-processing technique of dictionary learning modified to compensate for variations between subjects and sessions, and 2) an approach to subject-transfer decoding that uses the resting-state activity of a previously unseen target subject as calibration data for compensating for variations, eliminating the need for a standard calibration based on task sessions. Applying our methodology to a dataset of electroencephalography (EEG) recordings during a selective visual-spatial attention task from multiple subjects and sessions, where the variability compensation was essential for reducing the redundancy of the dictionary, we found that the extracted common brain activities were reasonable in the light of neuroscience knowledge. The applicability to subject-transfer decoding was confirmed by improved performance over existing decoding methods. These results suggest that analyzing multisubject brain activities on common bases by the proposed method enables information sharing across subjects with low-burden resting calibration, and is effective for practical use of BMI in variable environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Mass transfer dynamics in double degenerate binary systems

International Nuclear Information System (INIS)

Dan, M; Rosswog, S; Brueggen, M

2009-01-01

We present a numerical study of the mass transfer dynamics prior to the gravitational wave-driven merger of a double white dwarf system. Recently, there has been some discussion about the dynamics of these last stages, different methods seemed to provide qualitatively different results. While earlier SPH simulations indicated a very quick disruption of the binary on roughly the orbital time scale, more recent grid-based calculations find long-lived mass transfer for many orbital periods. Here we demonstrate how sensitive the dynamics of this last stage is to the exact initial conditions. We show that, after a careful preparation of the initial conditions, the reportedly short-lived systems undergo mass transfer for many dozens of orbits. The reported numbers of orbits are resolution-biased and therefore represent only lower limits to what is realized in nature. Nevertheless, the study shows convincingly the convergence of different methods to very similar results.

Teach Them How They Learn: Learning Styles and Information Systems Education

Science.gov (United States)

Cegielski, Casey G.; Hazen, Benjamin T.; Rainer, R. Kelly

2011-01-01

The rich, interdisciplinary tradition of learning styles is markedly absent in information systems-related research. The current study applies the framework of learning styles to a common educational component of many of today's information systems curricula--object-oriented systems development--in an effort to answer the question as to whether…

Knowledge acquisition and interface design for learning on demand systems

Science.gov (United States)

Nelson, Wayne A.

1993-01-01

The rapid changes in our world precipitated by technology have created new problems and new challenges for education and training. A knowledge 'explosion' is occurring as our society moves toward a service oriented economy that relies on information as the major resource. Complex computer systems are beginning to dominate the workplace, causing alarming growth and change in many fields. The rapidly changing nature of the workplace, especially in fields related to information technology, requires that our knowledge be updated constantly. This characteristic of modern society poses seemingly unsolvable instructional problems involving coverage and obsolescence. The sheer amount of information to be learned is rapidly increasing, while at the same time some information becomes obsolete in light of new information. Education, therefore, must become a lifelong process that features learning of new material and skills as needed in relation to the job to be done. Because of the problems cited above, the current model of learning in advance may no longer be feasible in our high-technology world. In many cases, learning in advance is impossible because there are simply too many things to learn. In addition, learning in advance can be time consuming, and often results in decontextualized knowledge that does not readily transfer to the work environment. The large and growing discrepancy between the amount of potentially relevant knowledge available and the amount a person can know and remember makes learning on demand an important alternative to current instructional practices. Learning on demand takes place whenever an individual must learn something new in order to perform a task or make a decision. Learning on demand is a promising approach for addressing the problems of coverage and obsolescence because learning is contextualized and integrated into the task environment rather than being relegated to a separate phase that precedes work. Learning on demand allows learners

Intelligent data analysis for e-learning enhancing security and trustworthiness in online learning systems

CERN Document Server

Miguel, Jorge; Xhafa, Fatos

2016-01-01

Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct-most notably cheating-however, e-Learning services are often designed and implemented without considering security requirements. This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as proc...

A Mobile Gamification Learning System for Improving the Learning Motivation and Achievements

Science.gov (United States)

Su, C-H.; Cheng, C-H.

2015-01-01

This paper aims to investigate how a gamified learning approach influences science learning, achievement and motivation, through a context-aware mobile learning environment, and explains the effects on motivation and student learning. A series of gamified learning activities, based on MGLS (Mobile Gamification Learning System), was developed and…

Heat transfer and mechanical interactions in fusion nuclear systems

International Nuclear Information System (INIS)

Nygren, R.E.

1984-01-01

This general review of design issues in heat transfer and mechanical interactions of the first wall, blanket and shield systems of tokamak and mirror fusion reactors begins with a brief introduction to fusion nuclear systems. The design issues are summarized in tables and the following examples are described to illustrate these concerns: the surface heating of limiters, heat transfer from solid breeders, MHD effects in liquid metal blankets, mechanical loads from electromagnetic transients and remote maintenance

E-learning systems intelligent techniques for personalization

CERN Document Server

Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C

2017-01-01

This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .

Simulation analysis on miniature wireless power transfer system

Science.gov (United States)

Liu, Tao; Wei, Zhiqiang; Yin, Bo; Chi, Haokun; Du, Panpan

2018-03-01

In recent years, the research on implantable medical devices has become a hot scientific topic, and the power supply of these devices are especially concerned. Generally, these devices are usually powered by disposable batteries. However, for some of the long-term human implant devices, such as pacemakers, once the battery has been exhausted after several years, the patient has to replace the battery by surgery, which increases the patient’s economic burden and pain. Wireless power transfer technology, using non-contact way for power transfer, can be a good solution to this problem. In this paper, a micro induction coil was designed, and the transfer efficiency in the air and human tissue model of two-layers were simulated by Ansoft HFSS. The results showed that the system could achieve the energy transfer in both cases, meanwhile, it indicated that the transfer efficiency was lower in a relative larger permittivity of transmission medium.

Assisted Learning Systems in e-Education

Directory of Open Access Journals (Sweden)

Gabriel ZAMFIR

2014-01-01

Full Text Available Human society, analyzed as a learning environment, presumes different languages in order to know, to understand or to develop it. This statement results as a default application of the cog-nitive domain in the educational scientific research, and it highlights a key feature: each essen-tial discovery was available for the entire language compatible society. E-Society is constructed as an application of E-Science in social services, and it is going to reveal a learning system for each application of the information technology developed for a compatible society. This article is proposed as a conceptual one focused on scientific research and the interrelationship be-tween the building blocks of research, defined as an engine for any designed learning system applied in the cognitive domain. In this approach, educational research become a learning sys-tem in e-Education. The purpose of this analysis is to configure the teacher assisted learning system and to expose its main principles which could be integrated in standard assisted instruc-tion applications, available in e-Classroom, supporting the design of specific didactic activities.

An Emulator Toolbox to Approximate Radiative Transfer Models with Statistical Learning

Directory of Open Access Journals (Sweden)

Juan Pablo Rivera

2015-07-01

Full Text Available Physically-based radiative transfer models (RTMs help in understanding the processes occurring on the Earth’s surface and their interactions with vegetation and atmosphere. When it comes to studying vegetation properties, RTMs allows us to study light interception by plant canopies and are used in the retrieval of biophysical variables through model inversion. However, advanced RTMs can take a long computational time, which makes them unfeasible in many real applications. To overcome this problem, it has been proposed to substitute RTMs through so-called emulators. Emulators are statistical models that approximate the functioning of RTMs. Emulators are advantageous in real practice because of the computational efficiency and excellent accuracy and flexibility for extrapolation. We hereby present an “Emulator toolbox” that enables analysing multi-output machine learning regression algorithms (MO-MLRAs on their ability to approximate an RTM. The toolbox is included in the free-access ARTMO’s MATLAB suite for parameter retrieval and model inversion and currently contains both linear and non-linear MO-MLRAs, namely partial least squares regression (PLSR, kernel ridge regression (KRR and neural networks (NN. These MO-MLRAs have been evaluated on their precision and speed to approximate the soil vegetation atmosphere transfer model SCOPE (Soil Canopy Observation, Photochemistry and Energy balance. SCOPE generates, amongst others, sun-induced chlorophyll fluorescence as the output signal. KRR and NN were evaluated as capable of reconstructing fluorescence spectra with great precision. Relative errors fell below 0.5% when trained with 500 or more samples using cross-validation and principal component analysis to alleviate the underdetermination problem. Moreover, NN reconstructed fluorescence spectra about 50-times faster and KRR about 800-times faster than SCOPE. The Emulator toolbox is foreseen to open new opportunities in the use of advanced

Quantum dot-dye hybrid systems for energy transfer applications

International Nuclear Information System (INIS)

Ren, Ting

2010-01-01

In this thesis, we focus on the preparation of energy transfer-based quantum dot (QD)-dye hybrid systems. Two kinds of QD-dye hybrid systems have been successfully synthesized: QD-silica-dye and QD-dye hybrid systems. In the QD-silica-dye hybrid system, multishell CdSe/CdS/ZnS QDs were adsorbed onto monodisperse Stoeber silica particles with an outer silica shell of thickness 2-24 nm containing organic dye molecules (Texas Red). The thickness of this dye layer has a strong effect on the total sensitized acceptor emission, which is explained by the increase in the number of dye molecules homogeneously distributed within the silica shell, in combination with an enhanced surface adsorption of QDs with increasing dye amount. Our conclusions were underlined by comparison of the experimental results with Monte-Carlo simulations, and by control experiments confirming attractive interactions between QDs and Texas Red freely dissolved in solution. New QD-dye hybrid system consisting of multishell QDs and organic perylene dyes have been synthesized. We developed a versatile approach to assemble extraordinarily stable QD-dye hybrids, which uses dicarboxylate anchors to bind rylene dyes to QD. This system yields a good basis to study the energy transfer between QD and dye because of its simple and compact design: there is no third kind of molecule linking QD and dye; no spacer; and the affinity of the functional group to the QD surface is strong. The FRET signal was measured for these complexes as a function of both dye to QD ratio and center-to-center distance between QD and dye by controlling number of covered ZnS layers. Data showed that fluorescence resonance energy transfer (FRET) was the dominant mechanism of the energy transfer in our QD-dye hybrid system. FRET efficiency can be controlled by not only adjusting the number of dyes on the QD surface or the QD to dye distance, but also properly choosing different dye and QD components. Due to the strong stability, our QD

Quantum dot-dye hybrid systems for energy transfer applications

Energy Technology Data Exchange (ETDEWEB)

Ren, Ting

2010-07-01

In this thesis, we focus on the preparation of energy transfer-based quantum dot (QD)-dye hybrid systems. Two kinds of QD-dye hybrid systems have been successfully synthesized: QD-silica-dye and QD-dye hybrid systems. In the QD-silica-dye hybrid system, multishell CdSe/CdS/ZnS QDs were adsorbed onto monodisperse Stoeber silica particles with an outer silica shell of thickness 2-24 nm containing organic dye molecules (Texas Red). The thickness of this dye layer has a strong effect on the total sensitized acceptor emission, which is explained by the increase in the number of dye molecules homogeneously distributed within the silica shell, in combination with an enhanced surface adsorption of QDs with increasing dye amount. Our conclusions were underlined by comparison of the experimental results with Monte-Carlo simulations, and by control experiments confirming attractive interactions between QDs and Texas Red freely dissolved in solution. New QD-dye hybrid system consisting of multishell QDs and organic perylene dyes have been synthesized. We developed a versatile approach to assemble extraordinarily stable QD-dye hybrids, which uses dicarboxylate anchors to bind rylene dyes to QD. This system yields a good basis to study the energy transfer between QD and dye because of its simple and compact design: there is no third kind of molecule linking QD and dye; no spacer; and the affinity of the functional group to the QD surface is strong. The FRET signal was measured for these complexes as a function of both dye to QD ratio and center-to-center distance between QD and dye by controlling number of covered ZnS layers. Data showed that fluorescence resonance energy transfer (FRET) was the dominant mechanism of the energy transfer in our QD-dye hybrid system. FRET efficiency can be controlled by not only adjusting the number of dyes on the QD surface or the QD to dye distance, but also properly choosing different dye and QD components. Due to the strong stability, our QD

Tools, courses, and learning pathways offered by the National Interagency Fuels, Fire, and Vegetation Technology Transfer

Science.gov (United States)

Eva K. Strand; Kathy H. Schon; Jeff Jones

2010-01-01

Technological advances in the area of fuel and wildland fire management have created a need for effective decision support tools and technology training. The National Interagency Fuels Committee and LANDFIRE have chartered a team to develop science-based learning tools for assessment of fire and fuels and to provide online training and technology transfer to help...

Personalized E- learning System Based on Intelligent Agent

Science.gov (United States)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

Comment on ‘Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study’

Science.gov (United States)

Valdes, Gilmer; Interian, Yannet

2018-03-01

The application of machine learning (ML) presents tremendous opportunities for the field of oncology, thus we read ‘Deep convolutional neural network with transfer learning for rectum toxicity prediction in cervical cancer radiotherapy: a feasibility study’ with great interest. In this article, the authors used state of the art techniques: a pre-trained convolutional neural network (VGG-16 CNN), transfer learning, data augmentation, drop out and early stopping, all of which are directly responsible for the success and the excitement that these algorithms have created in other fields. We believe that the use of these techniques can offer tremendous opportunities in the field of Medical Physics and as such we would like to praise the authors for their pioneering application to the field of Radiation Oncology. That being said, given that the field of Medical Physics has unique characteristics that differentiate us from those fields where these techniques have been applied successfully, we would like to raise some points for future discussion and follow up studies that could help the community understand the limitations and nuances of deep learning techniques.

A Simple and Effective Remedial Learning System with a Fuzzy Expert System

Science.gov (United States)

Lin, C.-C.; Guo, K.-H.; Lin, Y.-C.

2016-01-01

This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…

Transfer of short-term motor learning across the lower limbs as a function of task conception and practice order.

Science.gov (United States)

Stöckel, Tino; Wang, Jinsung

2011-11-01

Interlimb transfer of motor learning, indicating an improvement in performance with one limb following training with the other, often occurs asymmetrically (i.e., from non-dominant to dominant limb or vice versa, but not both). In the present study, we examined whether interlimb transfer of the same motor task could occur asymmetrically and in opposite directions (i.e., from right to left leg vs. left to right leg) depending on individuals' conception of the task. Two experimental conditions were tested: In a dynamic control condition, the process of learning was facilitated by providing the subjects with a type of information that forced them to focus on dynamic features of a given task (force impulse); and in a spatial control condition, it was done with another type of information that forced them to focus on visuomotor features of the same task (distance). Both conditions employed the same leg extension task. In addition, a fully-crossed transfer paradigm was used in which one group of subjects initially practiced with the right leg and were tested with the left leg for a transfer test, while the other group used the two legs in the opposite order. The results showed that the direction of interlimb transfer varied depending on the condition, such that the right and the left leg benefited from initial training with the opposite leg only in the spatial and the dynamic condition, respectively. Our finding suggests that manipulating the conception of a leg extension task has a substantial influence on the pattern of interlimb transfer in such a way that the direction of transfer can even be opposite depending on whether the task is conceived as a dynamic or spatial control task. Copyright © 2011 Elsevier Inc. All rights reserved.

Learning in context: identifying gaps in research on the transfer of medical communication skills to the clinical workplace.

NARCIS (Netherlands)

Eertwegh, V. van den; Dulmen, S. van; Dalen, J. van; Scherpbier, A.J.J.A.; Vleuten, C.P.M. van der

2013-01-01

Objective: In order to reduce the inconsistencies of findings and the apparent low transfer of communication skills from training to medical practice, this narrative review identifies some main gaps in research on medical communication skills training and presents insights from theories on learning

Learning in context: identifying gaps in research on the transfer of medical communication skills to the clinical workplace

NARCIS (Netherlands)

Eertwegh, V. van den; Dulmen, S. van; Dalen, J. Van; Scherpbier, A.J.J.A.; Vleuten, C.P.M. van der

2013-01-01

OBJECTIVE: In order to reduce the inconsistencies of findings and the apparent low transfer of communication skills from training to medical practice, this narrative review identifies some main gaps in research on medical communication skills training and presents insights from theories on learning

Exploring nursing e-learning systems success based on information system success model.

Science.gov (United States)

Chang, Hui-Chuan; Liu, Chung-Feng; Hwang, Hsin-Ginn

2011-12-01

E-learning is thought of as an innovative approach to enhance nurses' care service knowledge. Extensive research has provided rich information toward system development, courses design, and nurses' satisfaction with an e-learning system. However, a comprehensive view in understanding nursing e-learning system success is an important but less focused-on topic. The purpose of this research was to explore net benefits of nursing e-learning systems based on the updated DeLone and McLean's Information System Success Model. The study used a self-administered questionnaire to collected 208 valid nurses' responses from 21 of Taiwan's medium- and large-scale hospitals that have implemented nursing e-learning systems. The result confirms that the model is sufficient to explore the nurses' use of e-learning systems in terms of intention to use, user satisfaction, and net benefits. However, while the three exogenous quality factors (system quality, information quality, and service quality) were all found to be critical factors affecting user satisfaction, only information quality showed a direct effect on the intention to use. This study provides useful insights for evaluating nursing e-learning system qualities as well as an understanding of nurses' intentions and satisfaction related to performance benefits.

Development of on-site spent fuel transfer system designs

International Nuclear Information System (INIS)

Lambert, R.W.; Pennington, C.W.; Guerra, G.V.

1993-01-01

The Electric Power Research Institute (EPRI) of the United States has sponsored development of conceptual designs for accomplishing spent fuel transfer from spent fuel pools to casks and from one cask to another. Under an EPRI research contract, transnuclear has developed several concepts for spent fuel transfer systems. (J.P.N.)

Heat Transfer Modelling of Glass Media within TPV Systems

Science.gov (United States)

Bauer, Thomas; Forbes, Ian; Penlington, Roger; Pearsall, Nicola

2004-11-01

Understanding and optimisation of heat transfer, and in particular radiative heat transfer in terms of spectral, angular and spatial radiation distributions is important to achieve high system efficiencies and high electrical power densities for thermophtovoltaics (TPV). This work reviews heat transfer models and uses the Discrete Ordinates method. Firstly one-dimensional heat transfer in fused silica (quartz glass) shields was examined for the common arrangement, radiator-air-glass-air-PV cell. It has been concluded that an alternative arrangement radiator-glass-air-PV cell with increased thickness of fused silica should have advantages in terms of improved transmission of convertible radiation and enhanced suppression of non-convertible radiation.

15-Month-Olds’ Transfer of Learning between Touch Screen and Real-World Displays: Language Cues and Cognitive Loads

Science.gov (United States)

Zack, Elizabeth; Gerhardstein, Peter; Meltzoff, Andrew N.; Barr, Rachel

2012-01-01

Infants have difficulty transferring information between 2D and 3D sources. The current study extends Zack et al.’s (2009) touch screen imitation task to examine whether the addition of specific language cues significantly facilitates 15-month-olds’ transfer of learning between touch screens and real-world 3D objects. The addition of two kinds of linguistic cues (object label plus verb or nonsense name) did not elevate action imitation significantly above levels observed when such language cues were not used. Language cues hindered infants’ performance in the 3D→2D direction of transfer, but only for the object label plus verb condition. The lack of a facilitative effect of language is discussed in terms of competing cognitive loads imposed by conjointly transferring information across dimensions and processing linguistic cues in an action imitation task at this age. PMID:23121508

Versatile Desktop Experiment Module (DEMo) on Heat Transfer

Science.gov (United States)

Minerick, Adrienne R.

2010-01-01

This paper outlines a new Desktop Experiment Module (DEMo) engineered for a chemical engineering junior-level Heat Transfer course. This new DEMo learning tool is versatile, fairly inexpensive, and portable such that it can be positioned on student desks throughout a classroom. The DEMo system can illustrate conduction of various materials,…

Dynamic Stiffness Transfer Function of an Electromechanical Actuator Using System Identification

Science.gov (United States)

Kim, Sang Hwa; Tahk, Min-Jea

2018-04-01

In the aeroelastic analysis of flight vehicles with electromechanical actuators (EMAs), an accurate prediction of flutter requires dynamic stiffness characteristics of the EMA. The dynamic stiffness transfer function of the EMA with brushless direct current (BLDC) motor can be obtained by conducting complicated mathematical calculations of control algorithms and mechanical/electrical nonlinearities using linearization techniques. Thus, system identification approaches using experimental data, as an alternative, have considerable advantages. However, the test setup for system identification is expensive and complex, and experimental procedures for data collection are time-consuming tasks. To obtain the dynamic stiffness transfer function, this paper proposes a linear system identification method that uses information obtained from a reliable dynamic stiffness model with a control algorithm and nonlinearities. The results of this study show that the system identification procedure is compact, and the transfer function is able to describe the dynamic stiffness characteristics of the EMA. In addition, to verify the validity of the system identification method, the simulation results of the dynamic stiffness transfer function and the dynamic stiffness model were compared with the experimental data for various external loads.

Recommender Systems in Technology Enhanced Learning

NARCIS (Netherlands)

Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Santos, Olga

2010-01-01

Manouselis, N., Drachsler, H., Verbert, K., & Santos, C. S. (Eds.) (2010). Recommender System in Technology Enhanced Learning. Elsevier Procedia Computer Science: Volume 1, Issue 2. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL). September, 29-30,

Reconceptualizing Learning as a Dynamical System.

Science.gov (United States)

Ennis, Catherine D.

1992-01-01

Dynamical systems theory can increase our understanding of the constantly evolving learning process. Current research using experimental and interpretive paradigms focuses on describing the attractors and constraints stabilizing the educational process. Dynamical systems theory focuses attention on critical junctures in the learning process as…

Class and Home Problems. Identify-Solve-Broadcast Your Own Transport Phenomenon: Student-Created YouTube Videos to Foster Active Learning in Mass and Heat Transfer

Science.gov (United States)

Wen, Fei; Khera, Eshita

2016-01-01

Despite the instinctive perception of mass and heat transfer principles in daily life, productive learning in this course continues to be one of the greatest challenges for undergraduate students in chemical engineering. In an effort to enhance student learning in classroom, we initiated an innovative active-learning method titled…

Framework for Designing Context-Aware Learning Systems

Science.gov (United States)

Tortorella, Richard A. W.; Kinshuk; Chen, Nian-Shing

2018-01-01

Today people learn in many diverse locations and contexts, beyond the confines of classical brick and mortar classrooms. This trend is ever increasing, progressing hand-in-hand with the progress of technology. Context-aware learning systems are systems which adapt to the learner's context, providing tailored learning for a particular learning…

Control Decisions for Flammable Gas Hazards in Waste Transfer Systems

International Nuclear Information System (INIS)

KRIPPS, L.J.

2000-01-01

This report describes the control decisions for flammable gas hazards in waste transfer systems (i.e., waste transfer piping and waste transfer-associated structures) made at control decision meetings on November 30, 1999a and April 19, 2000, and their basis. These control decisions, and the analyses that support them, will be documented in an amendment to the Final Safety Analysis Report (FSAR) (CHG 2000a) and Technical Safety Requirements (TSR) (CHG 2000b) to close the Flammable Gas Unreviewed Safety Question (USQ) (Bacon 1996 and Wagoner 1996). Following the Contractor Tier I review of the FSAR and TSR amendment, it will be submitted to the US. Department of Energy (DOE), Office of River Protection (ORP) for review and approval. The control decision meeting on November 30, 1999 to address flammable gas hazards in waste transfer systems followed the control decision process and the criteria for control decisions described in Section 3.3.1.5 of the FSAR. The control decision meeting agenda, attendance list, and introductory and background presentations are included in Attachments 1 through 4. The control decision discussions on existing and other possible controls for flammable gas hazards in waste transfer systems and the basis for selecting or not selecting specific controls are summarized in this report

Estimating Students’ Satisfaction with Web Based Learning System in Blended Learning Environment

Directory of Open Access Journals (Sweden)

Sanja Bauk

2014-01-01

Full Text Available Blended learning became the most popular educational model that universities apply for teaching and learning. This model combines online and face-to-face learning environments, in order to enhance learning with implementation of new web technologies and tools in learning process. In this paper principles of DeLone and Mclean success model for information system are applied to Kano two-dimensional model, for categorizing quality attributes related to satisfaction of students with web based learning system used in blended learning model. Survey results are obtained among the students at “Mediterranean” University in Montenegro. The (dysfunctional dimensions of Kano model, including Kano basic matrix for assessment of the degree of students’ satisfaction level, have been considered in some more detail through corresponding numerical, graphical, and statistical analysis.

Digital case-based learning system in school.

Science.gov (United States)

Gu, Peipei; Guo, Jiayang

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Digital case-based learning system in school.

Directory of Open Access Journals (Sweden)

Peipei Gu

Full Text Available With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Mass transfer with chemical reaction in multiphase systems

International Nuclear Information System (INIS)

Alper, E.

1983-01-01

These volumes deal with the phenomenon of 'mass transfer with chemical reaction' which is of industrial, biological and physiological importance. In process engineering, it is encountered both in separation processes and in reaction engineering and both aspects are covered here in four sections: introduction; gas-liquid system; liquid-liquid system; and gas-liquid-solid system

Adaptive e-learning system using ontology

OpenAIRE

Yarandi, Maryam; Tawil, Abdel-Rahman; Jahankhani, Hossein

2011-01-01

This paper proposes an innovative ontological approach to design a personalised e-learning system which creates a tailored workflow for individual learner. Moreover, the learning content and sequencing logic is separated into content model and pedagogical model to increase the reusability and flexibility of the system.

Railcar waste transfer system hydrostatic test

International Nuclear Information System (INIS)

Ellingson, S.D.

1997-01-01

Recent modifications have been performed on the T-Plant Railcar Waste Transfer System, This Acceptance Test Procedure (ATP) has been prepared to demonstrate that identified piping welds and mechanical connections incorporated during the modification are of high integrity and are acceptable for service. This will be achieved by implementation of a hydrostatic leak test

Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

Science.gov (United States)

Burlina, Philippe; Pacheco, Katia D; Joshi, Neil; Freund, David E; Bressler, Neil M

2017-03-01

When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is often asymptomatic with regard to visual deficit. These individuals are at high risk for progressing to the advanced stage where the often treatable choroidal neovascular form of AMD can occur. Careful monitoring to detect the onset and prompt treatment of the neovascular form as well as dietary supplementation can reduce the risk of vision loss from AMD, therefore, preferred practice patterns recommend identifying individuals with the intermediate stage in a timely manner. Past automated retinal image analysis (ARIA) methods applied on fundus imagery have relied on engineered and hand-designed visual features. We instead detail the novel application of a machine learning approach using deep learning for the problem of ARIA and AMD analysis. We use transfer learning and universal features derived from deep convolutional neural networks (DCNN). We address clinically relevant 4-class, 3-class, and 2-class AMD severity classification problems. Using 5664 color fundus images from the NIH AREDS dataset and DCNN universal features, we obtain values for accuracy for the (4-, 3-, 2-) class classification problem of (79.4%, 81.5%, 93.4%) for machine vs. (75.8%, 85.0%, 95.2%) for physician grading. This study demonstrates the efficacy of machine grading based on deep universal features/transfer learning when applied to ARIA and is a promising step in providing a pre-screener to identify individuals with intermediate AMD and also as a tool that can facilitate identifying such individuals for clinical studies aimed at developing improved therapies. It also demonstrates comparable performance between computer and physician grading. Copyright © 2017 Elsevier Ltd. All rights reserved.

Component-Based Approach in Learning Management System Development

Science.gov (United States)

Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

2013-01-01

The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

Development of custom measurement system for biomechanical evaluation of independent wheelchair transfers.

Science.gov (United States)

Koontz, Alicia M; Lin, Yen-Sheng; Kankipati, Padmaja; Boninger, Michael L; Cooper, Rory A

2011-01-01

This study describes a new custom measurement system designed to investigate the biomechanics of sitting-pivot wheelchair transfers and assesses the reliability of selected biomechanical variables. Variables assessed include horizontal and vertical reaction forces underneath both hands and three-dimensional trunk, shoulder, and elbow range of motion. We examined the reliability of these measures between 5 consecutive transfer trials for 5 subjects with spinal cord injury and 12 nondisabled subjects while they performed a self-selected sitting pivot transfer from a wheelchair to a level bench. A majority of the biomechanical variables demonstrated moderate to excellent reliability (r > 0.6). The transfer measurement system recorded reliable and valid biomechanical data for future studies of sitting-pivot wheelchair transfers.We recommend a minimum of five transfer trials to obtain a reliable measure of transfer technique for future studies.

Replacement of Cross-Site Transfer System Startup Plan

International Nuclear Information System (INIS)

Gerken, M.D.

1996-01-01

This Startup Plan provides a discussion of organizational responsibilities, work planning, quality assurance (QA), personnel qualifications, and testing requirements for the Cross-Site Transfer System

Saponification reaction system: a detailed mass transfer coefficient determination.

Science.gov (United States)

Pečar, Darja; Goršek, Andreja

2015-01-01

The saponification of an aromatic ester with an aqueous sodium hydroxide was studied within a heterogeneous reaction medium in order to determine the overall kinetics of the selected system. The extended thermo-kinetic model was developed compared to the previously used simple one. The reaction rate within a heterogeneous liquid-liquid system incorporates a chemical kinetics term as well as mass transfer between both phases. Chemical rate constant was obtained from experiments within a homogeneous medium, whilst the mass-transfer coefficient was determined separately. The measured thermal profiles were then the bases for determining the overall reaction-rate. This study presents the development of an extended kinetic model for considering mass transfer regarding the saponification of ethyl benzoate with sodium hydroxide within a heterogeneous reaction medium. The time-dependences are presented for the mass transfer coefficient and the interfacial areas at different heterogeneous stages and temperatures. The results indicated an important role of reliable kinetic model, as significant difference in k(L)a product was obtained with extended and simple approach.

Toward a Theory of Adaptive Transfer: Expanding Disciplinary Discussions of "Transfer" in Second-Language Writing and Composition Studies

Science.gov (United States)

DePalma, Michael-John; Ringer, Jeffrey M.

2011-01-01

In this paper, we argue that discussions of transfer in L2 writing and composition studies have focused primarily on the reuse of past learning and thus have not adequately accounted for the adaptation of learned writing knowledge in unfamiliar situations. In an effort to expand disciplinary discussions of transfer in L2 writing and composition…

Design considerations for on-site spent-fuel transfer systems

International Nuclear Information System (INIS)

Jones, R.H.; Jones, C.R.

1989-06-01

Studies on spent fuel shipping logistics and operation make it clear that the use of large casks, i.e., 100--125 tons, is superior to smaller casks of similar construction. This superiority manifests itself in both transportation and/or shipping economics and safety as well as reduced personnel exposure in the processing of the casks. An on-site system for the transfer of spent fuel from the storage pool to a large shipping or storage cask, as well as the transfer of spent fuel directly from a storage cask to a shipping cask, could bring the large cask benefits to those restricted reactors. Sensing the need to look more closely at this opportunity, EPRI contracted with S. Levy, Incorporated of Campbell, CA to develop a set of design considerations for such transfer systems. Rather then embark on another design study, EPRI decided to first identify the system considerations that must be factored into any design. The format for this effort presents both the Consideration and the Rationale for the consideration. The resulting work identified thirty-six General Considerations and two Special Considerations. The Considerations are in the form of mandatory requirements and desirable but nonmandatory requirements. Additionally, a brief economic study was performed to get a feel for the cost considerations of on-site transfers. The study results suggest a relatively narrow set of scenarios where on-site transfers are economically superior to alternatives. These scenarios generally involve the use of concrete casks as on-site storage devices

Effect of metal shielding on a wireless power transfer system

Science.gov (United States)

Li, Jiacheng; Huang, Xueliang; Chen, Chen; Tan, Linlin; Wang, Wei; Guo, Jinpeng

2017-05-01

In this paper, the effect of non-ferromagnetic metal shielding (NFMS) material on the resonator of wireless power transfer (WPT) is studied by modeling, simulation and experimental analysis. And, the effect of NFMS material on the power transfer efficiency (PTE) of WPT systems is investigated by circuit model. Meanwhile, the effect of ferromagnetic metal shielding material on the PTE of WPT systems is analyzed through simulation. A double layer metal shield structure is designed. Experimental results demonstrate that by applying the novel double layer metal shielding method, the system PTE increases significantly while the electromagnetic field of WPT systems declines dramatically.

The Office Software Learning and Examination System Design Based on Fragmented Learning Idea

Directory of Open Access Journals (Sweden)

Xu Ling

2016-01-01

Full Text Available Fragmented learning is that through the segmentation of learning content or learning time, make learners can use the fragmented time for learning fragmentated content, have the characteristics of time flexibility, learning targeted and high learning efficiency. Based on the fragmented learning ideas, combined with the teaching idea of micro class and interactive teaching, comprehensive utilization of flash animation design software, .NET development platform, VSTO technology, multimedia development technology and so on, design and develop a system integrated with learning, practice and examination of the Office software, which is not only conducive to the effective and personalized learning of students, but also conducive to the understanding the students’ situation of teachers, and liberate teachers from the heavy labor of mechanical, focus on promoting the formation of students’ knowledge system.

E-Learning Systems, Environments and Approaches

OpenAIRE

Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.

2015-01-01

The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...

Alpha-gamma phase amplitude coupling subserves information transfer during perceptual sequence learning.

Science.gov (United States)

Tzvi, Elinor; Bauhaus, Leon J; Kessler, Till U; Liebrand, Matthias; Wöstmann, Malte; Krämer, Ulrike M

2018-03-01

Cross-frequency coupling is suggested to serve transfer of information between wide-spread neuronal assemblies and has been shown to underlie many cognitive functions including learning and memory. In previous work, we found that alpha (8-13 Hz) - gamma (30-48 Hz) phase amplitude coupling (αγPAC) is decreased during sequence learning in bilateral frontal cortex and right parietal cortex. We interpreted this to reflect decreased demands for visuo-motor mapping once the sequence has been encoded. In the present study, we put this hypothesis to the test by adding a "simple" condition to the standard serial reaction time task (SRTT) with minimal needs for visuo-motor mapping. The standard SRTT in our paradigm entailed a perceptual sequence allowing for implicit learning of a sequence of colors with randomly assigned motor responses. Sequence learning in this case was thus not associated with reduced demands for visuo-motor mapping. Analysis of oscillatory power revealed a learning-related alpha decrease pointing to a stronger recruitment of occipito-parietal areas when encoding the perceptual sequence. Replicating our previous findings but in contrast to our hypothesis, αγPAC was decreased in sequence compared to random trials over right frontal and parietal cortex. It also tended to be smaller compared to trials requiring a simple motor sequence. We additionally analyzed αγPAC in resting-state data of a separate cohort. PAC in electrodes over right parietal cortex was significantly stronger compared to sequence trials and tended to be higher compared to simple and random trials of the SRTT data. We suggest that αγPAC in right parietal cortex reflects a "default-mode" brain state, which gets perturbed to allow for encoding of visual regularities into memory. Copyright © 2018 Elsevier Inc. All rights reserved.

Intelligent fractions learning system: implementation

CSIR Research Space (South Africa)

Smith, Andrew C

2011-05-01

Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...

Fusion and particle transfer around the Coulomb-Barrier in intermediate systems

International Nuclear Information System (INIS)

Pascholati, P.R.

1989-01-01

The most important characteristics of fusion reactions below and around the Coulomb-barrier are summarized. Experimental fusion cross sections for typical systems are discussed and compared with current formulae obtained from semi-classical and quantum tunneling approaches. The influence of nucleons transfer in the enhancement of the fusion cross section below the Coulomb-barrier is also shown. Sub-barrier fusion cross sections for the systems 35,37 Cl + 58,64 Ni and 33 S + 90,91,92 Zr, and near-barrier cross sections of all important transfer channels have been measured using the XTU-TANDEM at Legnaro, Italy. In 35,37 Cl + 58,64 Ni systems, the motivation further investigated was the influence of the valence proton in the enhancement of the sub-barrier fusion cross section. The data are discussed in comparison with the similar data of 34,36 S + 58,64 Ni with the aim of revealing the influence of coupled proton transfer channels. Calculations were performed using the simplified coupled channel code CCFUS including ''pick-up'' of one and two neutrons and ''stripping'' of two neutrons channels. Signatures of positive Q-values transfer channels coupled to fusion were clearly identified. For the 33 S + 90,91,92 Zr systems taking into account the coupling effects between transfer and fusion and using the semi-classical approach, transfer form-factors were extracted and succesfully employed to described the isotopic effects in fusion enhancement. (Author) [es

One More Reason to Learn a New Language: Testing Academic Self-Efficacy Transfer at Junior High School

Science.gov (United States)

Fryer, Luke K.; Oga-Baldwin, W. L. Quint

2017-01-01

Self-efficacy is an essential source of motivation for learning. While considerable research has theorised and examined the how and why of self-efficacy in a single domain of study, longitudinal research has not yet tested how self-efficacy might generalise or transfer between subjects such as mathematics, native and foreign language studies. The…

Terminal zone glacial sediment transfer at a temperate overdeepened glacier system

Science.gov (United States)

Swift, D. A.; Cook, S. J.; Graham, D. J.; Midgley, N. G.; Fallick, A. E.; Storrar, R.; Toubes Rodrigo, M.; Evans, D. J. A.

2018-01-01

Continuity of sediment transfer through glacial systems is essential to maintain subglacial bedrock erosion, yet transfer at temperate glaciers with overdeepened beds, where subglacial fluvial sediment transport should be greatly limited by adverse slopes, remains poorly understood. Complex multiple transfer processes in temperate overdeepened systems has been indicated by the presence of large frontal moraine systems, supraglacial debris of mixed transport origin, thick basal ice sequences, and englacial thrusts and eskers. At Svínafellsjökull, thrusts comprising decimetre-thick debris-rich bands of stratified facies ice of basal origin, with a coarser size distribution and higher clast content than that observed in basal ice layers, contribute substantially to the transfer of subglacial material in the terminal zone. Entrainment and transfer of material occurs by simple shear along the upper surface of bands and by strain-induced deformation of stratified and firnified glacier ice below. Thrust material includes rounded and well-rounded clasts that are also striated, indicating that fluvial bedload is deposited as subglacial channels approach the overdeepening and then entrained along thrusts. Substantial transfer also occurs within basal ice, with facies type and debris content dependent on the hydrological connectedness of the adverse slope. A process model of transfer at glaciers with terminal overdeepenings is proposed, in which the geometry of the overdeepening influences spatial patterns of ice deformation, hydrology, and basal ice formation. We conclude that the significance of thrusting in maintaining sediment transfer continuity has likely been overlooked by glacier sediment budgets and glacial landscape evolution studies.

An E-learning System based on Affective Computing

Science.gov (United States)

Duo, Sun; Song, Lu Xue

In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

LEARNING TOOLS INTEROPERABILITY – A NEW STANDARD FOR INTEGRATION OF DISTANCE LEARNING PLATFORMS