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Sample records for abstract rule learning

  1. Neural Correlates of Abstract Rule Learning: An Event-Related Potential Study

    ERIC Educational Resources Information Center

    Sun, Fang; Hoshi-Shiba, Reiko; Abla, Dilshat; Okanoya, Kazuo

    2012-01-01

    Abstract rule learning is a fundamental aspect of human cognition, and is essential for language acquisition. However, despite its importance, the neural mechanisms underlying abstract rule learning are still largely unclear. In this study, we investigated the neural correlates of abstract rule learning by recording auditory event-related…

  2. Individual Differences in Learning and Transfer: Stable Tendencies for Learning Exemplars versus Abstracting Rules

    PubMed Central

    McDaniel, Mark A.; Cahill, Michael J.; Robbins, Mathew; Wiener, Chelsea

    2013-01-01

    We hypothesize that during training some learners may focus on acquiring the particular exemplars and responses associated with the exemplars (termed exemplar learners), whereas other learners attempt to abstract underlying regularities reflected in the particular exemplars linked to an appropriate response (termed rule learners). Supporting this distinction, after training (on a function-learning task), participants either displayed an extrapolation profile reflecting acquisition of the trained cue-criterion associations (exemplar learners) or abstraction of the function rule (rule learners; Studies 1a and 1b). Further, working memory capacity (measured by Ospan) was associated with the tendency to rely on rule versus exemplar processes. Studies 1c and 2 examined the persistence of these learning tendencies on several categorization tasks. Study 1c showed that rule learners were more likely than exemplar learners (indexed a priori by extrapolation profiles) to resist using idiosyncratic features (exemplar similarity) in generalization (transfer) of the trained category. Study 2 showed that the rule learners but not the exemplar learners performed well on a novel categorization task (transfer) after training on an abstract coherent category. These patterns suggest that in complex conceptual tasks, (a) individuals tend to either focus on exemplars during learning or on extracting some abstraction of the concept, (b) this tendency might be a relatively stable characteristic of the individual, and (c) transfer patterns are determined by that tendency. PMID:23750912

  3. Communicative signals support abstract rule learning by 7-month-old infants

    PubMed Central

    Ferguson, Brock; Lew-Williams, Casey

    2016-01-01

    The mechanisms underlying the discovery of abstract rules like those found in natural language may be evolutionarily tuned to speech, according to previous research. When infants hear speech sounds, they can learn rules that govern their combination, but when they hear non-speech sounds such as sine-wave tones, they fail to do so. Here we show that infants’ rule learning is not tied to speech per se, but is instead enhanced more broadly by communicative signals. In two experiments, infants succeeded in learning and generalizing rules from tones that were introduced as if they could be used to communicate. In two control experiments, infants failed to learn the very same rules when familiarized to tones outside of a communicative exchange. These results reveal that infants’ attention to social agents and communication catalyzes a fundamental achievement of human learning. PMID:27150270

  4. Communicative signals support abstract rule learning by 7-month-old infants.

    PubMed

    Ferguson, Brock; Lew-Williams, Casey

    2016-01-01

    The mechanisms underlying the discovery of abstract rules like those found in natural language may be evolutionarily tuned to speech, according to previous research. When infants hear speech sounds, they can learn rules that govern their combination, but when they hear non-speech sounds such as sine-wave tones, they fail to do so. Here we show that infants' rule learning is not tied to speech per se, but is instead enhanced more broadly by communicative signals. In two experiments, infants succeeded in learning and generalizing rules from tones that were introduced as if they could be used to communicate. In two control experiments, infants failed to learn the very same rules when familiarized to tones outside of a communicative exchange. These results reveal that infants' attention to social agents and communication catalyzes a fundamental achievement of human learning. PMID:27150270

  5. Information from Multiple Modalities Helps 5-Month-Olds Learn Abstract Rules

    ERIC Educational Resources Information Center

    Frank, Michael C.; Slemmer, Jonathan A.; Marcus, Gary F.; Johnson, Scott P.

    2009-01-01

    By 7 months of age, infants are able to learn rules based on the abstract relationships between stimuli ( Marcus et al., 1999 ), but they are better able to do so when exposed to speech than to some other classes of stimuli. In the current experiments we ask whether multimodal stimulus information will aid younger infants in identifying abstract…

  6. Bimodal emotion congruency is critical to preverbal infants' abstract rule learning.

    PubMed

    Tsui, Angeline Sin Mei; Ma, Yuen Ki; Ho, Anna; Chow, Hiu Mei; Tseng, Chia-huei

    2016-05-01

    Extracting general rules from specific examples is important, as we must face the same challenge displayed in various formats. Previous studies have found that bimodal presentation of grammar-like rules (e.g. ABA) enhanced 5-month-olds' capacity to acquire a rule that infants failed to learn when the rule was presented with visual presentation of the shapes alone (circle-triangle-circle) or auditory presentation of the syllables (la-ba-la) alone. However, the mechanisms and constraints for this bimodal learning facilitation are still unknown. In this study, we used audio-visual relation congruency between bimodal stimulation to disentangle possible facilitation sources. We exposed 8- to 10-month-old infants to an AAB sequence consisting of visual faces with affective expressions and/or auditory voices conveying emotions. Our results showed that infants were able to distinguish the learned AAB rule from other novel rules under bimodal stimulation when the affects in audio and visual stimuli were congruently paired (Experiments 1A and 2A). Infants failed to acquire the same rule when audio-visual stimuli were incongruently matched (Experiment 2B) and when only the visual (Experiment 1B) or the audio (Experiment 1C) stimuli were presented. Our results highlight that bimodal facilitation in infant rule learning is not only dependent on better statistical probability and redundant sensory information, but also the relational congruency of audio-visual information. A video abstract of this article can be viewed at https://m.youtube.com/watch?v=KYTyjH1k9RQ. PMID:26280911

  7. Bimodal Emotion Congruency Is Critical to Preverbal Infants' Abstract Rule Learning

    ERIC Educational Resources Information Center

    Tsui, Angeline Sin Mei; Ma, Yuen Ki; Ho, Anna; Chow, Hiu Mei; Tseng, Chia-huei

    2016-01-01

    Extracting general rules from specific examples is important, as we must face the same challenge displayed in various formats. Previous studies have found that bimodal presentation of grammar-like rules (e.g. ABA) enhanced 5-month-olds' capacity to acquire a rule that infants failed to learn when the rule was presented with visual presentation of…

  8. Abstract Rule Learning for Visual Sequences in 8- and 11-Month-Olds

    ERIC Educational Resources Information Center

    Johnson, Scott P.; Fernandes, Keith J.; Frank, Michael C.; Kirkham, Natasha; Marcus, Gary; Rabagliati, Hugh; Slemmer, Jonathan A.

    2009-01-01

    The experiments reported here investigated the development of a fundamental component of cognition: to recognize and generalize abstract relations. Infants were presented with simple rule-governed patterned sequences of visual shapes (ABB, AAB, and ABA) that could be discriminated from differences in the position of the repeated element (late,…

  9. Category learning strategies in younger and older adults: Rule abstraction and memorization.

    PubMed

    Wahlheim, Christopher N; McDaniel, Mark A; Little, Jeri L

    2016-06-01

    Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, the frequencies of rule- and exemplar-based learners were not significantly different between age groups, but there was a significantly higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies) in the older than younger adult group. Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. (PsycINFO Database Record PMID:26950225

  10. Abstract Rule Learning in 11- and 14-Month-Old Infants

    ERIC Educational Resources Information Center

    Koulaguina, Elena; Shi, Rushen

    2013-01-01

    This study tests the hypothesis that distributional information can guide infants in the generalization of word order movement rules at the initial stage of language acquisition. Participants were 11- and 14-month-old infants. Stimuli were sentences in Russian, a language that was unknown to our infants. During training the word order of each…

  11. Beyond learning fixed rules and social cues: abstraction in the social arena.

    PubMed

    Call, Joseph

    2003-07-29

    Abstraction is a central idea in many areas of physical comparative cognition such as categorization, numerical competence or problem solving. This idea, however, has rarely been applied to comparative social cognition. In this paper, I propose that the notion of abstraction can be applied to the social arena and become an important tool to investigate the social cognition and behaviour processes in animals. To make this point, I present recent evidence showing that chimpanzees know about what others can see and about what others intend. These data do not fit either low-level mechanisms based on stimulus-response associations or high-level explanations based on metarepresentational mechanisms such as false belief attribution. Instead, I argue that social abstraction, in particular the development of concepts such as seeing in others, is key to explaining the behaviour of our closest relative in a variety of situations. PMID:12903652

  12. Learning Abstracts, 1999.

    ERIC Educational Resources Information Center

    League for Innovation in the Community Coll.

    This document contains volume two of Learning Abstracts, a bimonthly newsletter from the League for Innovation in the Community College. Articles in these seven issues include: (1) "Get on the Fast Track to Learning: An Accelerated Associate Degree Option" (Gerardo E. de los Santos and Deborah J. Cruise); (2) "The Learning College: Both Learner…

  13. Frontal cortex and the discovery of abstract action rules

    PubMed Central

    Badre, David; Kayser, Andrew S.; D’Esposito, Mark

    2010-01-01

    Summary Although we often encounter circumstances with which we have no prior experience, we rapidly learn how to behave in these novel situations. Such adaptive behavior relies on abstract behavioral rules that are generalizable, rather than concrete rules mapping specific cues to specific responses. Though the frontal cortex is known to support concrete rule learning, less well understood are the neural mechanisms supporting the acquisition of abstract rules. Here we use a novel reinforcement learning paradigm to demonstrate that more anterior regions along the rostro-caudal axis of frontal cortex support rule learning at higher levels of abstraction. Moreover, these results indicate that when humans confront new rule learning problems, this rostro-caudal division of labor supports the search for relationships between context and action at multiple levels of abstraction simultaneously. PMID:20435006

  14. Learning Abstracts, 2001.

    ERIC Educational Resources Information Center

    Wilson, Cynthia, Ed.

    2001-01-01

    Volume 4 of the League for Innovation in the Community College's Learning Abstracts include the following: (1) "Touching Students in the Digital Age: The Move Toward Learner Relationship Management (LRM)," by Mark David Milliron, which offers an overview of an organizing concept to help community colleges navigate the intersection between digital…

  15. From domain-generality to domain-sensitivity: 4-month-olds learn an abstract repetition rule in music that 7-month-olds do not.

    PubMed

    Dawson, Colin; Gerken, LouAnn

    2009-06-01

    Learning must be constrained for it to lead to productive generalizations. Although biology is undoubtedly an important source of constraints, prior experience may be another, leading learners to represent input in ways that are more conducive to some generalizations than others, and/or to up- and down-weight features when entertaining generalizations. In two experiments, 4-month-old and 7-month-old infants were familiarized with sequences of musical chords or tones adhering either to an AAB pattern or an ABA pattern. In both cases, the 4-month-olds learned the generalization, but the 7-month-olds did not. The success of the 4-month-olds appears to contradict an account that this type of pattern learning is the provenance of a language-specific rule-learning module. It is not yet clear what drives the age-related change, but plausible candidates include differential experience with language and music, as well as interactions between general cognitive development and stimulus complexity. PMID:19338982

  16. Superior abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana)

    PubMed Central

    Magnotti, John F.; Katz, Jeffrey S.; Wright, Anthony A.; Kelly, Debbie M.

    2015-01-01

    The ability to learn abstract relational concepts is fundamental to higher level cognition. In contrast to item-specific concepts (e.g. pictures containing trees versus pictures containing cars), abstract relational concepts are not bound to particular stimulus features, but instead involve the relationship between stimuli and therefore may be extrapolated to novel stimuli. Previous research investigating the same/different abstract concept has suggested that primates might be specially adapted to extract relations among items and would require fewer exemplars of a rule to learn an abstract concept than non-primate species. We assessed abstract-concept learning in an avian species, Clark's nutcracker (Nucifraga columbiana), using a small number of exemplars (eight pairs of the same rule, and 56 pairs of the different rule) identical to that previously used to compare rhesus monkeys, capuchin monkeys and pigeons. Nutcrackers as a group (N = 9) showed more novel stimulus transfer than any previous species tested with this small number of exemplars. Two nutcrackers showed full concept learning and four more showed transfer considerably above chance performance, indicating partial concept learning. These results show that the Clark's nutcracker, a corvid species well known for its amazing feats of spatial memory, learns the same/different abstract concept better than any non-human species (including non-human primates) yet tested on this same task. PMID:25972399

  17. Superior abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana).

    PubMed

    Magnotti, John F; Katz, Jeffrey S; Wright, Anthony A; Kelly, Debbie M

    2015-05-01

    The ability to learn abstract relational concepts is fundamental to higher level cognition. In contrast to item-specific concepts (e.g. pictures containing trees versus pictures containing cars), abstract relational concepts are not bound to particular stimulus features, but instead involve the relationship between stimuli and therefore may be extrapolated to novel stimuli. Previous research investigating the same/different abstract concept has suggested that primates might be specially adapted to extract relations among items and would require fewer exemplars of a rule to learn an abstract concept than non-primate species. We assessed abstract-concept learning in an avian species, Clark's nutcracker (Nucifraga columbiana), using a small number of exemplars (eight pairs of the same rule, and 56 pairs of the different rule) identical to that previously used to compare rhesus monkeys, capuchin monkeys and pigeons. Nutcrackers as a group (N = 9) showed more novel stimulus transfer than any previous species tested with this small number of exemplars. Two nutcrackers showed full concept learning and four more showed transfer considerably above chance performance, indicating partial concept learning. These results show that the Clark's nutcracker, a corvid species well known for its amazing feats of spatial memory, learns the same/different abstract concept better than any non-human species (including non-human primates) yet tested on this same task. PMID:25972399

  18. The Acquisition of Allophonic Rules: Statistical Learning with Linguistic Constraints

    ERIC Educational Resources Information Center

    Peperkamp, Sharon; Le Calvez, Rozenn; Nadal, Jean-Pierre; Dupoux, Emmanuel

    2006-01-01

    Phonological rules relate surface phonetic word forms to abstract underlying forms that are stored in the lexicon. Infants must thus acquire these rules in order to infer the abstract representation of words. We implement a statistical learning algorithm for the acquisition of one type of rule, namely allophony, which introduces context-sensitive…

  19. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.

    PubMed

    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. PMID:25902728

  20. Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex

    PubMed Central

    Cole, Michael W.; Etzel, Joset A.; Zacks, Jeffrey M.; Schneider, Walter; Braver, Todd S.

    2011-01-01

    Flexible, adaptive behavior is thought to rely on abstract rule representations within lateral prefrontal cortex (LPFC), yet it remains unclear how these representations provide such flexibility. We recently demonstrated that humans can learn complex novel tasks in seconds. Here we hypothesized that this impressive mental flexibility may be possible due to rapid transfer of practiced rule representations within LPFC to novel task contexts. We tested this hypothesis using functional MRI and multivariate pattern analysis, classifying LPFC activity patterns across 64 tasks. Classifiers trained to identify abstract rules based on practiced task activity patterns successfully generalized to novel tasks. This suggests humans can transfer practiced rule representations within LPFC to rapidly learn new tasks, facilitating cognitive performance in novel circumstances. PMID:22125519

  1. Abstracting in the Context of Spontaneous Learning

    ERIC Educational Resources Information Center

    Williams, Gaye

    2007-01-01

    There is evidence that spontaneous learning leads to relational understanding and high positive affect. To study spontaneous abstracting, a model was constructed by combining the RBC model of abstraction with Krutetskii's mental activities. Using video-stimulated interviews, the model was then used to analyze the behavior of two Year 8 students…

  2. Sleep facilitates learning a new linguistic rule

    PubMed Central

    Batterink, Laura J.; Oudiette, Delphine; Reber, Paul J.; Paller, Ken A.

    2014-01-01

    Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. PMID:25447376

  3. Sleep facilitates learning a new linguistic rule.

    PubMed

    Batterink, Laura J; Oudiette, Delphine; Reber, Paul J; Paller, Ken A

    2014-12-01

    Natural languages contain countless regularities. Extraction of these patterns is an essential component of language acquisition. Here we examined the hypothesis that memory processing during sleep contributes to this learning. We exposed participants to a hidden linguistic rule by presenting a large number of two-word phrases, each including a noun preceded by one of four novel words that functioned as an article (e.g., gi rhino). These novel words (ul, gi, ro and ne) were presented as obeying an explicit rule: two words signified that the noun referent was relatively near, and two that it was relatively far. Undisclosed to participants was the fact that the novel articles also predicted noun animacy, with two of the articles preceding animate referents and the other two preceding inanimate referents. Rule acquisition was tested implicitly using a task in which participants responded to each phrase according to whether the noun was animate or inanimate. Learning of the hidden rule was evident in slower responses to phrases that violated the rule. Responses were delayed regardless of whether rule-knowledge was consciously accessible. Brain potentials provided additional confirmation of implicit and explicit rule-knowledge. An afternoon nap was interposed between two 20-min learning sessions. Participants who obtained greater amounts of both slow-wave and rapid-eye-movement sleep showed increased sensitivity to the hidden linguistic rule in the second session. We conclude that during sleep, reactivation of linguistic information linked with the rule was instrumental for stabilizing learning. The combination of slow-wave and rapid-eye-movement sleep may synergistically facilitate the abstraction of complex patterns in linguistic input. PMID:25447376

  4. Dynamics of temporal learning rules

    NASA Astrophysics Data System (ADS)

    Roberts, Patrick D.

    2000-09-01

    The changes of synaptic strength are analyzed on two time scales: the fast local field dynamics, and the slow synaptic modification dynamics. The fast dynamics are determined by the synaptic strengths and background noise in the system. The slow dynamics are determined by the functional form of a temporal learning rule. Temporal learning rules are defined to be functions yielding state dependent changes in synaptic strengths depending on the timing of pre- and postsynaptic states in the network. The evolution of local field dynamics that result from various learning rules are analyzed for a stochastic, discrete time neural model with no relative refractory period that receives a series of delayed adaptive inputs. A fixed point is found in the learning dynamics, and conditions for two types of instabilities are analyzed. Four universality classes of dynamics are found that are independent of the details of the temporal learning rules. Examples are given of biological systems in which these temporal learning rules have been identified, and their functional consequences are discussed.

  5. Musical expertise induces audiovisual integration of abstract congruency rules.

    PubMed

    Paraskevopoulos, Evangelos; Kuchenbuch, Anja; Herholz, Sibylle C; Pantev, Christo

    2012-12-12

    Perception of everyday life events relies mostly on multisensory integration. Hence, studying the neural correlates of the integration of multiple senses constitutes an important tool in understanding perception within an ecologically valid framework. The present study used magnetoencephalography in human subjects to identify the neural correlates of an audiovisual incongruency response, which is not generated due to incongruency of the unisensory physical characteristics of the stimulation but from the violation of an abstract congruency rule. The chosen rule-"the higher the pitch of the tone, the higher the position of the circle"-was comparable to musical reading. In parallel, plasticity effects due to long-term musical training on this response were investigated by comparing musicians to non-musicians. The applied paradigm was based on an appropriate modification of the multifeatured oddball paradigm incorporating, within one run, deviants based on a multisensory audiovisual incongruent condition and two unisensory mismatch conditions: an auditory and a visual one. Results indicated the presence of an audiovisual incongruency response, generated mainly in frontal regions, an auditory mismatch negativity, and a visual mismatch response. Moreover, results revealed that long-term musical training generates plastic changes in frontal, temporal, and occipital areas that affect this multisensory incongruency response as well as the unisensory auditory and visual mismatch responses. PMID:23238733

  6. Rule Learning in Autism: The Role of Reward Type and Social Context

    PubMed Central

    Jones, E. J. H.; Webb, S. J.; Estes, A.; Dawson, G.

    2013-01-01

    Learning abstract rules is central to social and cognitive development. Across two experiments, we used Delayed Non-Matching to Sample tasks to characterize the longitudinal development and nature of rule-learning impairments in children with Autism Spectrum Disorder (ASD). Results showed that children with ASD consistently experienced more difficulty learning an abstract rule from a discrete physical reward than children with DD. Rule learning was facilitated by the provision of more concrete reinforcement, suggesting an underlying difficulty in forming conceptual connections. Learning abstract rules about social stimuli remained challenging through late childhood, indicating the importance of testing executive functions in both social and non-social contexts. PMID:23311315

  7. Rule learning in autism: the role of reward type and social context.

    PubMed

    Jones, E J H; Webb, S J; Estes, A; Dawson, G

    2013-01-01

    Learning abstract rules is central to social and cognitive development. Across two experiments, we used Delayed Non-Matching to Sample tasks to characterize the longitudinal development and nature of rule-learning impairments in children with Autism Spectrum Disorder (ASD). Results showed that children with ASD consistently experienced more difficulty learning an abstract rule from a discrete physical reward than children with DD. Rule learning was facilitated by the provision of more concrete reinforcement, suggesting an underlying difficulty in forming conceptual connections. Learning abstract rules about social stimuli remained challenging through late childhood, indicating the importance of testing executive functions in both social and non-social contexts. PMID:23311315

  8. a Heterosynaptic Learning Rule for Neural Networks

    NASA Astrophysics Data System (ADS)

    Emmert-Streib, Frank

    In this article we introduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the pre- and postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean learning time increases with the number of patterns to be learned polynomially, indicating efficient learning.

  9. Myths and legends in learning classification rules

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1990-01-01

    A discussion is presented of machine learning theory on empirically learning classification rules. Six myths are proposed in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, universal learning algorithms, and interactive learning. Some of the problems raised are also addressed from a Bayesian perspective. Questions are suggested that machine learning researchers should be addressing both theoretically and experimentally.

  10. Myths and legends in learning classification rules

    NASA Technical Reports Server (NTRS)

    Buntine, Wray

    1990-01-01

    This paper is a discussion of machine learning theory on empirically learning classification rules. The paper proposes six myths in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, 'universal' learning algorithms, and interactive learnings. Some of the problems raised are also addressed from a Bayesian perspective. The paper concludes by suggesting questions that machine learning researchers should be addressing both theoretically and experimentally.

  11. Learning and Tuning of Fuzzy Rules

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1997-01-01

    In this chapter, we review some of the current techniques for learning and tuning fuzzy rules. For clarity, we refer to the process of generating rules from data as the learning problem and distinguish it from tuning an already existing set of fuzzy rules. For learning, we touch on unsupervised learning techniques such as fuzzy c-means, fuzzy decision tree systems, fuzzy genetic algorithms, and linear fuzzy rules generation methods. For tuning, we discuss Jang's ANFIS architecture, Berenji-Khedkar's GARIC architecture and its extensions in GARIC-Q. We show that the hybrid techniques capable of learning and tuning fuzzy rules, such as CART-ANFIS, RNN-FLCS, and GARIC-RB, are desirable in development of a number of future intelligent systems.

  12. Reflective Abstraction and Mathematics Education: The Genetic Decomposition of the Chain Rule--Work in Progress

    ERIC Educational Resources Information Center

    Jojo, Zingiswa Monica Mybert; Maharaj, Aneshkumar; Brijlall, Deonarain

    2012-01-01

    Students have experienced difficulty in understanding and using the chain rule. This study aims at assisting the students to understand and apply the chain rule and thus inform the author's teaching for future learning of students. A questionnaire will be designed to explore the conceptual understanding of the concept of the chain rule by first…

  13. Effects of Abstract and Concrete Simulation Elements on Science Learning

    ERIC Educational Resources Information Center

    Jaakkola, T.; Veermans, K.

    2015-01-01

    Contemporary evidence on the effectiveness of concrete and abstract representations in science education is based solely on studies conducted in college context. There it has been found that learning with abstract representations produces predominantly better outcomes than learning with concrete representations and combining the representations…

  14. Situated Learning in an Abstract Algebra Classroom

    ERIC Educational Resources Information Center

    Ticknor, Cindy S.

    2012-01-01

    Advisory committees of mathematics consider abstract algebra as an essential component of the mathematical preparation of secondary teachers, yet preservice teachers find it challenging to connect the topics addressed in this advanced course with the high school algebra they must someday teach. This study analyzed the mathematical content…

  15. Reducing Abstraction When Learning Graph Theory

    ERIC Educational Resources Information Center

    Hazzan, Orit; Hadar, Irit

    2005-01-01

    This article presents research on students' understanding of basic concepts in Graph Theory. Students' understanding is analyzed through the lens of the theoretical framework of reducing abstraction (Hazzan, 1999). As it turns out, in spite of the relative simplicity of the concepts that are introduced in the introductory part of a traditional…

  16. A Bayesian Theory of Sequential Causal Learning and Abstract Transfer

    ERIC Educational Resources Information Center

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

    2016-01-01

    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…

  17. Effects of Variation and Prior Knowledge on Abstract Concept Learning

    ERIC Educational Resources Information Center

    Braithwaite, David W.; Goldstone, Robert L.

    2015-01-01

    Learning abstract concepts through concrete examples may promote learning at the cost of inhibiting transfer. The present study investigated one approach to solving this problem: systematically varying superficial features of the examples. Participants learned to solve problems involving a mathematical concept by studying either superficially…

  18. Learning Abstract Statistics Concepts Using Simulation

    ERIC Educational Resources Information Center

    Mills, Jamie D.

    2004-01-01

    The teaching and learning of statistics has impacted the curriculum in elementary, secondary, and post-secondary education. Because of this growing movement to expand and include statistics into all levels of education, there is also a considerable interest in how to teach statistics. For statistics concepts that tend to be very difficult or…

  19. Refining Linear Fuzzy Rules by Reinforcement Learning

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil

    1996-01-01

    Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.

  20. Multilayer perceptrons may learn simple rules quickly

    NASA Astrophysics Data System (ADS)

    Urbanczik, R.

    1998-08-01

    Zero-temperature Gibbs learning is considered for a connected committee machine with K hidden units. For large K, the scale of the learning curve strongly depends on the target rule. When learning a perceptron, the sample size P needed for optimal generalization scales so that N<rule if a new input is classified by the majority vote of all students in the version space. When learning a committee machine with M hidden units, 1<

  1. Rule Learning with Probabilistic Smoothing

    NASA Astrophysics Data System (ADS)

    Costa, Gianni; Guarascio, Massimo; Manco, Giuseppe; Ortale, Riccardo; Ritacco, Ettore

    A hierarchical classification framework is proposed for discriminating rare classes in imprecise domains, characterized by rarity (of both classes and cases), noise and low class separability. The devised framework couples the rules of a rule-based classifier with as many local probabilistic generative models. These are trained over the coverage of the corresponding rules to better catch those globally rare cases/classes that become less rare in the coverage. Two novel schemes for tightly integrating rule-based and probabilistic classification are introduced, that classify unlabeled cases by considering multiple classifier rules as well as their local probabilistic counterparts. An intensive evaluation shows that the proposed framework is competitive and often superior in accuracy w.r.t. established competitors, while overcoming them in dealing with rare classes.

  2. Concrete and Abstract Visualizations in History Learning Tasks

    ERIC Educational Resources Information Center

    Prangsma, Maaike E.; van Boxtel, Carla A. M.; Kanselaar, Gellof; Kirschner, Paul A.

    2009-01-01

    Background: History learning requires that students understand historical phenomena, abstract concepts and the relations between them. Students have problems grasping, using and relating complex historical developments and structures. Aims: A study was conducted to determine the effects of tasks with abstract and/or concrete visualizations on the…

  3. Phonological Memory and Rule Learning

    ERIC Educational Resources Information Center

    Williams, John N.; Lovatt, Peter

    2005-01-01

    Our research reflects the current trend to relate individual differences in second language learning to underlying cognitive processes e.g., Robinson, 2002. We believe that such investigations, apart from being of practical importance, can also shed light on the cognitive mechanisms underlying the language learning process. Here we focus on the…

  4. Harder Words: Learning Abstract Verbs with Opaque Syntax

    ERIC Educational Resources Information Center

    Becker, Misha; Estigarribia, Bruno

    2013-01-01

    Highly abstract predicates (e.g. "think") present a number of difficulties for language learners (Gleitman et al., 2005). A partial solution to learning these verbs is that learners exploit regularities in the syntactic frames in which these verbs occur. While agreeing with this general approach to learning verbs, we caution that this…

  5. Influence of Audio-Visual Presentations on Learning Abstract Concepts.

    ERIC Educational Resources Information Center

    Lai, Shu-Ling

    2000-01-01

    Describes a study of college students that investigated whether various types of visual illustrations influenced abstract concept learning when combined with audio instruction. Discusses results of analysis of variance and pretest posttest scores in relation to learning performance, attitudes toward the computer-based program, and differences in…

  6. On learning dynamics underlying the evolution of learning rules.

    PubMed

    Dridi, Slimane; Lehmann, Laurent

    2014-02-01

    In order to understand the development of non-genetically encoded actions during an animal's lifespan, it is necessary to analyze the dynamics and evolution of learning rules producing behavior. Owing to the intrinsic stochastic and frequency-dependent nature of learning dynamics, these rules are often studied in evolutionary biology via agent-based computer simulations. In this paper, we show that stochastic approximation theory can help to qualitatively understand learning dynamics and formulate analytical models for the evolution of learning rules. We consider a population of individuals repeatedly interacting during their lifespan, and where the stage game faced by the individuals fluctuates according to an environmental stochastic process. Individuals adjust their behavioral actions according to learning rules belonging to the class of experience-weighted attraction learning mechanisms, which includes standard reinforcement and Bayesian learning as special cases. We use stochastic approximation theory in order to derive differential equations governing action play probabilities, which turn out to have qualitative features of mutator-selection equations. We then perform agent-based simulations to find the conditions where the deterministic approximation is closest to the original stochastic learning process for standard 2-action 2-player fluctuating games, where interaction between learning rules and preference reversal may occur. Finally, we analyze a simplified model for the evolution of learning in a producer-scrounger game, which shows that the exploration rate can interact in a non-intuitive way with other features of co-evolving learning rules. Overall, our analyses illustrate the usefulness of applying stochastic approximation theory in the study of animal learning. PMID:24055617

  7. Concrete-Semiconcrete-Abstract (CSA) Instruction: A Decision Rule for Improving Instructional Efficacy

    ERIC Educational Resources Information Center

    Sealander, Karen A.; Johnson, Gae R.; Lockwood, Adam B.; Medina, Catherine M.

    2012-01-01

    A concrete-semiconcrete-abstract (CSA) instructional approach derived from discovery learning (DIS) was embedded in a direct instruction (DI) methodology to teach eight elementary students with math disabilities. One-minute abstract-level probes were the primary metric used to assess student performance on subtraction problems (minuends 0-9). A…

  8. Biclustering Learning of Trading Rules.

    PubMed

    Huang, Qinghua; Wang, Ting; Tao, Dacheng; Li, Xuelong

    2015-10-01

    Technical analysis with numerous indicators and patterns has been regarded as important evidence for making trading decisions in financial markets. However, it is extremely difficult for investors to find useful trading rules based on numerous technical indicators. This paper innovatively proposes the use of biclustering mining to discover effective technical trading patterns that contain a combination of indicators from historical financial data series. This is the first attempt to use biclustering algorithm on trading data. The mined patterns are regarded as trading rules and can be classified as three trading actions (i.e., the buy, the sell, and no-action signals) with respect to the maximum support. A modified K nearest neighborhood ( K -NN) method is applied to classification of trading days in the testing period. The proposed method [called biclustering algorithm and the K nearest neighbor (BIC- K -NN)] was implemented on four historical datasets and the average performance was compared with the conventional buy-and-hold strategy and three previously reported intelligent trading systems. Experimental results demonstrate that the proposed trading system outperforms its counterparts and will be useful for investment in various financial markets. PMID:25494520

  9. The statistical mechanics of learning a rule

    SciTech Connect

    Watkin, T.L.H.; Rau, A. ); Biehl, M. )

    1993-04-01

    A summary is presented of the statistical mechanical theory of learning a rule with a neural network, a rapidly advancing area which is closely related to other inverse problems frequently encountered by physicists. By emphasizing the relationship between neural networks and strongly interacting physical systems, such as spin glasses, the authors show how learning theory has provided a workshop in which to develop new, exact analytical techniques.

  10. Post-analysis of learned rules

    SciTech Connect

    Liu, Bing; Hsu, W.

    1996-12-31

    Rule induction research implicitly assumes that after producing the rules from a dataset, these rules will be used directly by an expert system or a human user. In real-life applications, the situation may not be as simple as that, particularly, when the user of the rules is a human being. The human user almost always has some previous concepts or knowledge about the domain represented by the dataset. Naturally, he/she wishes to know how the new rules compare with his/her existing knowledge. In dynamic domains where the rules may change over time, it is important to know what the changes are. These aspects of research have largely been ignored in the past. With the increasing use of machine learning techniques in practical applications such as data mining, this issue of post analysis of rules warrants greater emphasis and attention. In this paper, we propose a technique to deal with this problem. A system has been implemented to perform the post analysis of classification rules generated by systems such as C4.5. The proposed technique is general and highly interactive. It will be particularly useful in data mining and data analysis.

  11. Episodes to Scripts to Rules: Concrete-Abstractions in Kindergarten Children's Explanations of a Robot's Behavior

    ERIC Educational Resources Information Center

    Mioduser, David; Levy, Sharona T.; Talis, Vadim

    2009-01-01

    This study explores young children's abstraction of the rules underlying a robot's emergent behavior. The study was conducted individually with six kindergarten children, along five sessions that included description and construction tasks, ordered by increasing difficulty. We developed and used a robotic control interface, structured as…

  12. Alternate Learning Center. Abstracts of Inservice Training Programs.

    ERIC Educational Resources Information Center

    Rhode Island State Dept. of Education, Providence. Div. of Development and Operations.

    This booklet is a collection of abstracts describing the 18 programs offered at the Alternate Learning Center of the Rhode Island Teacher Center which has as its Primary function school based inservice training for local teachers and administrators. Each project is described in detail, including course goals, specific objectives, training…

  13. Experience and Abstract Reasoning in Learning Backward Induction

    PubMed Central

    Hawes, Daniel R.; Vostroknutov, Alexander; Rustichini, Aldo

    2011-01-01

    Backward induction is a benchmark of game theoretic rationality, yet surprisingly little is known as to how humans discover and initially learn to apply this abstract solution concept in experimental settings. We use behavioral and functional magnetic resonance imaging (fMRI) data to study the way in which subjects playing in a sequential game of perfect information learn the optimal backward induction strategy for the game. Experimental data from our two studies support two main findings: First, subjects converge to a common process of recursive inference similar to the backward induction procedure for solving the game. The process is recursive because earlier insights and conclusions are used as inputs in later steps of the inference. This process is matched by a similar pattern in brain activation, which also proceeds backward, following the prediction error: brain activity initially codes the responses to losses in final positions; in later trials this activity shifts to the starting position. Second, the learning process is not exclusively cognitive, but instead combines experience-based learning and abstract reasoning. Critical experiences leading to the adoption of an improved solution strategy appear to be stimulated by brain activity in the reward system. This indicates that the negative affect induced by initial failures facilitates the switch to a different method of solving the problem. Abstract reasoning is combined with this response, and is expressed by activation in the ventrolateral prefrontal cortex. Differences in brain activation match differences in performance between subjects who show different learning speeds. PMID:22363254

  14. Brains rule! fun = learning = neuroscience literacy.

    PubMed

    Zardetto-Smith, Andrea M; Mu, Keli; Phelps, Cynthia L; Houtz, Lynne E; Royeen, Charlotte B

    2002-10-01

    Brains Rule! Neuroscience Expositions is a project designed to improve neuroscience literacy among children and the general public by applying a model where neuroscience professionals transfer knowledge and enthusiasm about neuroscience through fun, engaging hands-on activities. This educational model draws strength from many national and local partnerships of neuroscience professionals to coordinate expositions across the country in a variety of local communities. Brains Rule! Neuroscience Expositions uses a flexible science fair-like format to engage children in the process of science and teach about neuroscience concepts, facts, and professions. Neuroscience literacy is important to everyday life and helps individuals better understand themselves, make informed decisions about health and drug use, participate knowledgeably in governmental and social issues, and better understand scientific advancements. In this study, children's ratings of Brains Rule! Neuroscience Expositions activities were analyzed both quantitatively and qualitatively. Analysis of the responses revealed that overall the children perceived the learning activities as fun and interesting and believed that they learned something about the brain and nervous system after engaging in the activities. The Brains Rule! Neuroscience Expositions education model can be an effective tool in improving neuroscience literacy for both children and adults. PMID:12374424

  15. Machine Learning of Maritime Fog Forecast Rules.

    NASA Astrophysics Data System (ADS)

    Tag, Paul M.; Peak, James E.

    1996-05-01

    In recent years, the field of artificial intelligence has contributed significantly to the science of meteorology, most notably in the now familiar form of expert systems. Expert systems have focused on rules or heuristics by establishing, in computer code, the reasoning process of a weather forecaster predicting, for example, thunderstorms or fog. In addition to the years of effort that goes into developing such a knowledge base is the time-consuming task of extracting such knowledge and experience from experts. In this paper, the induction of rules directly from meteorological data is explored-a process called machine learning. A commercial machine learning program called C4.5, is applied to a meteorological problem, forecasting maritime fog, for which a reliable expert system has been previously developed. Two detasets are used: 1) weather ship observations originally used for testing and evaluating the expert system, and 2) buoy measurements taken off the coast of California. For both datasets, the rules produced by C4.5 are reasonable and make physical sense, thus demonstrating that an objective induction approach can reveal physical processes directly from data. For the ship database, the machine-generated rules are not as accurate as those from the expert system but are still significantly better than persistence forecasts. For the buoy data, the forecast accuracies are very high, but only slightly superior to persistence. The results indicate that the machine learning approach is a viable tool for developing meteorological expertise, but only when applied to reliable data with sufficient cases of known outcome. In those instances when such databases are available, the use of machine learning can provide useful insight that otherwise might take considerable human analysis to produce.

  16. Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning.

    PubMed

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-07-01

    Often the world is structured such that distinct sensory contexts signify the same abstract rule set. Learning from feedback thus informs us not only about the value of stimulus-action associations but also about which rule set applies. Hierarchical clustering models suggest that learners discover structure in the environment, clustering distinct sensory events into a single latent rule set. Such structure enables a learner to transfer any newly acquired information to other contexts linked to the same rule set, and facilitates re-use of learned knowledge in novel contexts. Here, we show that humans exhibit this transfer, generalization and clustering during learning. Trial-by-trial model-based analysis of EEG signals revealed that subjects' reward expectations incorporated this hierarchical structure; these structured neural signals were predictive of behavioral transfer and clustering. These results further our understanding of how humans learn and generalize flexibly by building abstract, behaviorally relevant representations of the complex, high-dimensional sensory environment. PMID:27082659

  17. Temporal dynamics of task switching and abstract-concept learning in pigeons.

    PubMed

    Daniel, Thomas A; Cook, Robert G; Katz, Jeffrey S

    2015-01-01

    The current study examined whether pigeons could learn to use abstract concepts as the basis for conditionally switching behavior as a function of time. Using a mid-session reversal task, experienced pigeons were trained to switch from matching-to-sample (MTS) to non-matching-to-sample (NMTS) conditional discriminations within a session. One group had prior training with MTS, while the other had prior training with NMTS. Over training, stimulus set size was progressively doubled from 3 to 6 to 12 stimuli to promote abstract concept development. Prior experience had an effect on the initial learning at each of the set sizes but by the end of training there were no group differences, as both groups showed similar within-session linear matching functions. After acquiring the 12-item set, abstract-concept learning was tested by placing novel stimuli at the beginning and end of a test session. Prior matching and non-matching experience affected transfer behavior. The matching experienced group transferred to novel stimuli in both the matching and non-matching portion of the sessions using a matching rule. The non-matching experienced group transferred to novel stimuli in both portions of the session using a non-matching rule. The representations used as the basis for mid-session reversal of the conditional discrimination behaviors and subsequent transfer behavior appears to have different temporal sources. The implications for the flexibility and organization of complex behaviors are considered. PMID:26388825

  18. Temporal dynamics of task switching and abstract-concept learning in pigeons

    PubMed Central

    Daniel, Thomas A.; Cook, Robert G.; Katz, Jeffrey S.

    2015-01-01

    The current study examined whether pigeons could learn to use abstract concepts as the basis for conditionally switching behavior as a function of time. Using a mid-session reversal task, experienced pigeons were trained to switch from matching-to-sample (MTS) to non-matching-to-sample (NMTS) conditional discriminations within a session. One group had prior training with MTS, while the other had prior training with NMTS. Over training, stimulus set size was progressively doubled from 3 to 6 to 12 stimuli to promote abstract concept development. Prior experience had an effect on the initial learning at each of the set sizes but by the end of training there were no group differences, as both groups showed similar within-session linear matching functions. After acquiring the 12-item set, abstract-concept learning was tested by placing novel stimuli at the beginning and end of a test session. Prior matching and non-matching experience affected transfer behavior. The matching experienced group transferred to novel stimuli in both the matching and non-matching portion of the sessions using a matching rule. The non-matching experienced group transferred to novel stimuli in both portions of the session using a non-matching rule. The representations used as the basis for mid-session reversal of the conditional discrimination behaviors and subsequent transfer behavior appears to have different temporal sources. The implications for the flexibility and organization of complex behaviors are considered. PMID:26388825

  19. Does Mathematical Learning Occur in Going from Concrete to Abstract or in Going from Abstract to Concrete?

    ERIC Educational Resources Information Center

    Roth, Wolff-Michael; Hwang, SungWon

    2006-01-01

    The notions of "abstract "and "concrete" are central to the conceptualization of mathematical knowing and learning. It is generally accepted that development goes from concrete toward the abstract; but dialectical theorists maintain just the opposite: development consists of an ascension from the abstract to the concrete. In this article, we…

  20. Same/Different Abstract Concept Learning by Archerfish (Toxotes chatareus)

    PubMed Central

    Newport, Cait; Wallis, Guy; Siebeck, Ulrike E.

    2015-01-01

    While several phylogenetically diverse species have proved capable of learning abstract concepts, previous attempts to teach fish have been unsuccessful. In this report, the ability of archerfish (Toxotes chatareus) to learn the concepts of sameness and difference using a simultaneous two-item discrimination task was tested. Six archerfish were trained to either select a pair of same or different stimuli which were presented simultaneously. Training consisted of a 2-phase approach. Training phase 1: the symbols in the same and different pair did not change, thereby allowing the fish to solve the test through direct association. The fish were trained consecutively with four different sets of stimuli to familiarize them with the general procedure before moving on to the next training phase. Training phase 2: six different symbols were used to form the same or different pairs. After acquisition, same/different concept learning was tested by presenting fish with six novel stimuli (transfer test). Five fish successfully completed the first training phase. Only one individual passed the second training phase, however, transfer performance was consistent with chance. This individual was given further training using 60 training exemplars but the individual was unable to reach the training criterion. We hypothesize that archerfish are able to solve a limited version of the same/different test by learning the response to each possible stimulus configuration or by developing a series of relatively simple choice contingencies. We conclude that the simultaneous two-item discrimination task we describe cannot be successfully used to test the concepts of same and different in archerfish. In addition, despite considerable effort training archerfish using several tests and training methods, there is still no evidence that fish can learn an abstract concept-based test. PMID:26599071

  1. Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats.

    PubMed

    Lloyd, Kevin; Becker, Nadine; Jones, Matthew W; Bogacz, Rafal

    2012-01-01

    Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

  2. An implementation and analysis of the Abstract Syntax Notation One and the basic encoding rules

    NASA Technical Reports Server (NTRS)

    Harvey, James D.; Weaver, Alfred C.

    1990-01-01

    The details of abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively solve the problem of data transfer across incompatible host environments are presented, and a compiler that was built to automate their use is described. Experiences with this compiler are also discussed which provide a quantitative analysis of the performance costs associated with the application of these standards. An evaluation is offered as to how well suited ASN.1 and BER are in solving the common data representation problem.

  3. Beyond Explicit Rule Learning: Automatizing Second Language Morphosyntax.

    ERIC Educational Resources Information Center

    DeKeyser, Robert M.

    1997-01-01

    Presents a fine-grained analysis of extensive empirical data on the automatization of explicitly learned rules of morphosyntax in a second language. Results indicate that the learning of morphosyntactic rules is highly skill-specific and that these skills develop gradually over time, adhering to the same power function learning curve as the…

  4. A Local Learning Rule for Independent Component Analysis

    NASA Astrophysics Data System (ADS)

    Isomura, Takuya; Toyoizumi, Taro

    2016-06-01

    Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering.

  5. A Local Learning Rule for Independent Component Analysis

    PubMed Central

    Isomura, Takuya; Toyoizumi, Taro

    2016-01-01

    Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering. PMID:27323661

  6. A Local Learning Rule for Independent Component Analysis.

    PubMed

    Isomura, Takuya; Toyoizumi, Taro

    2016-01-01

    Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering. PMID:27323661

  7. Statistical Mechanics of On-line Ensemble Teacher Learning through a Novel Perceptron Learning Rule

    NASA Astrophysics Data System (ADS)

    Hara, Kazuyuki; Miyoshi, Seiji

    2012-06-01

    In ensemble teacher learning, ensemble teachers have only uncertain information about the true teacher, and this information is given by an ensemble consisting of an infinite number of ensemble teachers whose variety is sufficiently rich. In this learning, a student learns from an ensemble teacher that is iteratively selected randomly from a pool of many ensemble teachers. An interesting point of ensemble teacher learning is the asymptotic behavior of the student to approach the true teacher by learning from ensemble teachers. The student performance is improved by using the Hebbian learning rule in the learning. However, the perceptron learning rule cannot improve the student performance. On the other hand, we proposed a perceptron learning rule with a margin. This learning rule is identical to the perceptron learning rule when the margin is zero and identical to the Hebbian learning rule when the margin is infinity. Thus, this rule connects the perceptron learning rule and the Hebbian learning rule continuously through the size of the margin. Using this rule, we study changes in the learning behavior from the perceptron learning rule to the Hebbian learning rule by considering several margin sizes. From the results, we show that by setting a margin of κ>0, the effect of an ensemble appears and becomes significant when a larger margin κ is used.

  8. How learning to abstract shapes neural sound representations

    PubMed Central

    Ley, Anke; Vroomen, Jean; Formisano, Elia

    2014-01-01

    The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques such as multivariate pattern analysis (MVPA) in studying categorical sound representations. With their increased sensitivity to distributed activation changes—even in absence of changes in overall signal level—these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations. PMID:24917783

  9. A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

    PubMed Central

    Balcarras, Matthew; Womelsdorf, Thilo

    2016-01-01

    Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context

  10. A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning.

    PubMed

    Balcarras, Matthew; Womelsdorf, Thilo

    2016-01-01

    Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context

  11. Many faces, one rule: the role of perceptual expertise in infants’ sequential rule learning

    PubMed Central

    Bulf, Hermann; Brenna, Viola; Valenza, Eloisa; Johnson, Scott P.; Turati, Chiara

    2015-01-01

    Rule learning is a mechanism that allows infants to recognize and generalize rule-like patterns, such as ABB or ABA. Although infants are better at learning rules from speech vs. non-speech, rule learning can be applied also to frequently experienced visual stimuli, suggesting that perceptual expertise with material to be learned is critical in enhancing rule learning abilities. Yet infants’ rule learning has never been investigated using one of the most commonly experienced visual stimulus category available in infants’ environment, i.e., faces. Here, we investigate 7-month-olds’ ability to extract rule-like patterns from sequences composed of upright faces and compared their results to those of infants who viewed inverted faces, which presumably are encountered far less frequently than upright faces. Infants were habituated with face triads in either an ABA or ABB condition followed by a test phase with ABA and ABB triads composed of faces that differed from those showed during habituation. When upright faces were used, infants generalized the pattern presented during habituation to include the new face identities showed during testing, but when inverted faces were presented, infants failed to extract the rule. This finding supports the idea that perceptual expertise can modulate 7-month-olds’ abilities to detect rule-like patterns. PMID:26539142

  12. Learning General Phonological Rules from Distributional Information: A Computational Model

    ERIC Educational Resources Information Center

    Calamaro, Shira; Jarosz, Gaja

    2015-01-01

    Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony…

  13. The long learning route to abstract letter units.

    PubMed

    Thompson, G Brian

    2009-02-01

    This is a review of theory and evidence on how abstract letter units (ALUs) are initially learnt by the developing individual. Despite the predominance of the lower-case form of letters in the print environment, naming identification of upper case has precedence over lower case among preschool children. Such children showed a significant lag in extending their categories of upper-case variants to include the corresponding lower-case forms that are visually dissimilar. As late as 11 years of age children gave longer naming latencies for the lower-case than the upper-case forms. Initial learning of ALUs proceeded slowly over many months, consistent with the "common contexts" hypothesis but not consistent with the early acquisition predicted by the "common letter name" hypothesis. Evidence from cross-case transfer in a training experiment indicated that prior to acquiring full use of ALUs the children had formed representations of words that were letter based but specific to lower-case forms. PMID:18649251

  14. Morphophonemic Rule Learning in Normal and Articulation-Disordered Children.

    ERIC Educational Resources Information Center

    Dunn, Carla; Till, James A.

    1982-01-01

    Eight articulation disordered kindergarten children and eight normally speaking children were taught an artificial morphophonemic rule. Results revealed essentially no differences in the way the two groups learned the stop class. In contrast, the disordered children incorporated fricatives into the rule more quickly and responded with more…

  15. Evolving fuzzy rules in a learning classifier system

    NASA Technical Reports Server (NTRS)

    Valenzuela-Rendon, Manuel

    1993-01-01

    The fuzzy classifier system (FCS) combines the ideas of fuzzy logic controllers (FLC's) and learning classifier systems (LCS's). It brings together the expressive powers of fuzzy logic as it has been applied in fuzzy controllers to express relations between continuous variables, and the ability of LCS's to evolve co-adapted sets of rules. The goal of the FCS is to develop a rule-based system capable of learning in a reinforcement regime, and that can potentially be used for process control.

  16. The Role of Comprehension in Learning Concrete and Abstract Sentences

    ERIC Educational Resources Information Center

    Pezdek, Kathy; Royer, James M.

    1974-01-01

    A study was made to assess the effect of comprehension on the recognition of meaning and wording changes with concrete and abstract sentences. The results of the experiment were discussed in light of recent models which propose different storage mechanisms for concrete and abstract sentences. (Author/RM)

  17. Toward Generalization of Automated Temporal Abstraction to Partially Observable Reinforcement Learning.

    PubMed

    Çilden, Erkin; Polat, Faruk

    2015-08-01

    Temporal abstraction for reinforcement learning (RL) aims to decrease learning time by making use of repeated sub-policy patterns in the learning task. Automatic extraction of abstractions during RL process is difficult but has many challenges such as dealing with the curse of dimensionality. Various studies have explored the subject under the assumption that the problem domain is fully observable by the learning agent. Learning abstractions for partially observable RL is a relatively less explored area. In this paper, we adapt an existing automatic abstraction method, namely extended sequence tree, originally designed for fully observable problems. The modified method covers a certain family of model-based partially observable RL settings. We also introduce belief state discretization methods that can be used with this new abstraction mechanism. The effectiveness of the proposed abstraction method is shown empirically by experimenting on well-known benchmark problems. PMID:25216494

  18. Human EEG Uncovers Latent Generalizable Rule Structure during Learning

    PubMed Central

    Collins, Anne G. E.; Cavanagh, James F.

    2014-01-01

    Human cognition is flexible and adaptive, affording the ability to detect and leverage complex structure inherent in the environment and generalize this structure to novel situations. Behavioral studies show that humans impute structure into simple learning problems, even when this tendency affords no behavioral advantage. Here we used electroencephalography to investigate the neural dynamics indicative of such incidental latent structure. Event-related potentials over lateral prefrontal cortex, typically observed for instructed task rules, were stratified according to individual participants' constructed rule sets. Moreover, this individualized latent rule structure could be independently decoded from multielectrode pattern classification. Both neural markers were predictive of participants' ability to subsequently generalize rule structure to new contexts. These EEG dynamics reveal that the human brain spontaneously constructs hierarchically structured representations during learning of simple task rules. PMID:24672013

  19. Bayesian Learning and the Psychology of Rule Induction

    ERIC Educational Resources Information Center

    Endress, Ansgar D.

    2013-01-01

    In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum's (2011) Bayesian model of rule-learning as a case study to…

  20. A Rational Analysis of Rule-Based Concept Learning

    ERIC Educational Resources Information Center

    Goodman, Noah D.; Tenenbaum, Joshua B.; Feldman, Jacob; Griffiths, Thomas L.

    2008-01-01

    This article proposes a new model of human concept learning that provides a rational analysis of learning feature-based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space--a concept language of logical rules. This article compares the model predictions to human generalization judgments in several…

  1. Rule-Based Category Learning in Down Syndrome

    ERIC Educational Resources Information Center

    Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.

    2014-01-01

    Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…

  2. A Developmental Study of Conceptual Tempo, Concept Learning, and Abstraction

    ERIC Educational Resources Information Center

    Juliano, Daniel

    1977-01-01

    Shows that age or conceptual tempo are not related to the number of trials needed to reach the criteria for a learning task. Impulsive responders performed more poorly than groups of slow-inaccurate, fast-accurate, and reflective responders on the transfer of learning task. (RL)

  3. Learning categories via rules and similarity: comparing adults and children.

    PubMed

    Rabi, Rahel; Miles, Sarah J; Minda, John Paul

    2015-03-01

    Two experiments explored the different strategies used by children and adults when learning new perceptual categories. Participants were asked to learn a set of categories for which both a single-feature rule and overall similarity would allow for perfect performance. Other rules allowed for suboptimal performance. Transfer stimuli (Experiments 1 and 2) and single features (Experiment 2) were presented after training to help determine how the categories were learned. In both experiments, we found that adults made significantly more optimal rule-based responses to the test stimuli than children. Children showed a variety of categorization styles, with a few relying on the optimal rules, many relying on suboptimal single-feature rules, and only a few relying on overall family resemblance. We interpret these results within a multiple systems framework, and we argue that children show the pattern they do because they lack the necessary cognitive resources to fully engage in hypothesis testing, rule selection, and verbally mediated category learning. PMID:25558860

  4. Dissertation Abstracts: Scientific Evidence Related to Teaching and Learning Mathematics

    ERIC Educational Resources Information Center

    Cicmanec, Karen B.

    2008-01-01

    This categorical analysis explores the mathematics education doctoral dissertations archived in UMI "Digital Dissertations" (1991-2005) and 115 abstracts of doctoral dissertations from 46 institutions offering doctoral degrees in 2004. The goal of this study is to a) index changes in the numbers of mathematics education doctoral candidates and b)…

  5. Dopaminergic Genetic Polymorphisms Predict Rule-based Category Learning.

    PubMed

    Byrne, Kaileigh A; Davis, Tyler; Worthy, Darrell A

    2016-07-01

    Dopaminergic genes play an important role in cognitive function. DRD2 and DARPP-32 dopamine receptor gene polymorphisms affect striatal dopamine binding potential, and the Val158Met single-nucleotide polymorphism of the COMT gene moderates dopamine availability in the pFC. Our study assesses the role of these gene polymorphisms on performance in two rule-based category learning tasks. Participants completed unidimensional and conjunctive rule-based tasks. In the unidimensional task, a rule along a single stimulus dimension can be used to distinguish category members. In contrast, a conjunctive rule utilizes a combination of two dimensions to distinguish category members. DRD2 C957T TT homozygotes outperformed C allele carriers on both tasks, and DARPP-32 AA homozygotes outperformed G allele carriers on both tasks. However, we found an interaction between COMT and task type where Met allele carriers outperformed Val homozygotes in the conjunctive rule task, but both groups performed equally well in the unidimensional task. Thus, striatal dopamine binding may play a critical role in both types of rule-based tasks, whereas prefrontal dopamine binding is important for learning more complex conjunctive rule tasks. Modeling results suggest that striatal dopaminergic genes influence selective attention processes whereas cortical genes mediate the ability to update complex rule representations. PMID:26918585

  6. Learning a New Selection Rule in Visual and Frontal Cortex.

    PubMed

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

    2016-08-01

    How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. PMID:27269960

  7. Learning a New Selection Rule in Visual and Frontal Cortex

    PubMed Central

    van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R.

    2016-01-01

    How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. PMID:27269960

  8. Prosodic cues enhance rule learning by changing speech segmentation mechanisms

    PubMed Central

    de Diego-Balaguer, Ruth; Rodríguez-Fornells, Antoni; Bachoud-Lévi, Anne-Catherine

    2015-01-01

    Prosody has been claimed to have a critical role in the acquisition of grammatical information from speech. The exact mechanisms by which prosodic cues enhance learning are fully unknown. Rules from language often require the extraction of non-adjacent dependencies (e.g., he plays, he sings, he speaks). It has been proposed that pauses enhance learning because they allow computing non-adjacent relations helping word segmentation by removing the need to compute adjacent computations. So far only indirect evidence from behavioral and electrophysiological measures comparing learning effects after exposure to speech with and without pauses support this claim. By recording event-related potentials during the acquisition process of artificial languages with and without pauses between words with embedded non-adjacent rules we provide direct evidence on how the presence of pauses modifies the way speech is processed during learning to enhance segmentation and rule generalization. The electrophysiological results indicate that pauses as short as 25 ms attenuated the N1 component irrespective of whether learning was possible or not. In addition, a P2 enhancement was present only when learning of non-adjacent dependencies was possible. The overall results support the claim that the simple presence of subtle pauses changed the segmentation mechanism used reflected in an exogenously driven N1 component attenuation and improving segmentation at the behavioral level. This effect can be dissociated from the endogenous P2 enhancement that is observed irrespective of the presence of pauses whenever non-adjacent dependencies are learned. PMID:26483731

  9. Importance of Fe and Mn Pipe Deposits to Lead and Copper Rule Compliance - abstract

    EPA Science Inventory

    When Madison, WI exceeded the lead Action Level in 1992, residential and off-line tests suggested that lead release into the water was more complex than a lead solubility mechanism. The water utility chose to address the Lead and Copper Rule (LCR) exceedance by implementing full ...

  10. Switching between Abstract Rules Reflects Disease Severity but Not Dopaminergic Status in Parkinson's Disease

    ERIC Educational Resources Information Center

    Kehagia, Angie A.; Cools, Roshan; Barker, Roger A.; Robbins, Trevor W.

    2009-01-01

    This study sought to disambiguate the impact of Parkinson's disease (PD) on cognitive control as indexed by task set switching, by addressing discrepancies in the literature pertaining to disease severity and paradigm heterogeneity. A task set is governed by a rule that determines how relevant stimuli (stimulus set) map onto specific responses…

  11. Abstraction, ethics and software: Why don`t the rules work?

    SciTech Connect

    Warwick, S.

    1994-12-31

    A theory is presented that one of the reasons why the use of unlicensed software is so widespread and unstigmatized is that legislatures, courts and other bodies which create policy operate at a higher level of abstraction than do individuals, and that abstraction is a key factor in the divergence of societal behavior from that condoned by legal statute. This theory is explored through a pilot study consisting of medium depth interviews with two volunteers who had used unlicensed software. Their attitudes, understanding of the law, and characterization of the their use of unlicensed software as based on {open_quotes}need{close_quotes} is reported. In addition, the concept of face is examined, and how it is maintained while violating law. It is suggested that further studies, using multiple methodologies, (in-depth interview, focus groups, and surveys) be conducted prior to developing further policy or legislation regarding intellectual property protection for software.

  12. Does hearing two dialects at different times help infants learn dialect-specific rules?

    PubMed

    Gonzales, Kalim; Gerken, LouAnn; Gómez, Rebecca L

    2015-07-01

    Infants might be better at teasing apart dialects with different language rules when hearing the dialects at different times, since language learners do not always combine input heard at different times. However, no previous research has independently varied the temporal distribution of conflicting language input. Twelve-month-olds heard two artificial language streams representing different dialects-a "pure stream" whose sentences adhered to abstract grammar rules like aX bY, and a "mixed stream" wherein any a- or b-word could precede any X- or Y-word. Infants were then tested for generalization of the pure stream's rules to novel sentences. Supporting our hypothesis, infants showed generalization when the two streams' sentences alternated in minutes-long intervals without any perceptually salient change across streams (Experiment 2), but not when all sentences from these same streams were randomly interleaved (Experiment 3). Results are interpreted in light of temporal context effects in word learning. PMID:25880342

  13. The Effects of Memory and Abstractive Integration on Children's Probability Learning.

    ERIC Educational Resources Information Center

    Kreitler, Shulamith; And Others

    1983-01-01

    Examines the relation between children's (1) probability learning performance and a measure of their memory for items presented in a sequence and (2) probability learning and performance on a test of abstractive integration. Participating were 80 six- and seven-year-old boys and girls from both low and middle socioeconomic classes. (Author/RH)

  14. Grapheme-color synaesthesia benefits rule-based Category learning.

    PubMed

    Watson, Marcus R; Blair, Mark R; Kozik, Pavel; Akins, Kathleen A; Enns, James T

    2012-09-01

    Researchers have long suspected that grapheme-color synaesthesia is useful, but research on its utility has so far focused primarily on episodic memory and perceptual discrimination. Here we ask whether it can be harnessed during rule-based Category learning. Participants learned through trial and error to classify grapheme pairs that were organized into categories on the basis of their associated synaesthetic colors. The performance of synaesthetes was similar to non-synaesthetes viewing graphemes that were physically colored in the same way. Specifically, synaesthetes learned to categorize stimuli effectively, they were able to transfer this learning to novel stimuli, and they falsely recognized grapheme-pair foils, all like non-synaesthetes viewing colored graphemes. These findings demonstrate that synaesthesia can be exploited when learning the kind of material taught in many classroom settings. PMID:22763316

  15. The Convallis rule for unsupervised learning in cortical networks.

    PubMed

    Yger, Pierre; Harris, Kenneth D

    2013-10-01

    The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the "Convallis rule", mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. PMID:24204224

  16. Proof Rules for Automated Compositional Verification through Learning

    NASA Technical Reports Server (NTRS)

    Barringer, Howard; Giannakopoulou, Dimitra; Pasareanu, Corina S.

    2003-01-01

    Compositional proof systems not only enable the stepwise development of concurrent processes but also provide a basis to alleviate the state explosion problem associated with model checking. An assume-guarantee style of specification and reasoning has long been advocated to achieve compositionality. However, this style of reasoning is often non-trivial, typically requiring human input to determine appropriate assumptions. In this paper, we present novel assume- guarantee rules in the setting of finite labelled transition systems with blocking communication. We show how these rules can be applied in an iterative and fully automated fashion within a framework based on learning.

  17. Learning of Rule Ensembles for Multiple Attribute Ranking Problems

    NASA Astrophysics Data System (ADS)

    Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

    In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

  18. Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning

    PubMed Central

    Minda, John P.; Rabi, Rahel

    2015-01-01

    Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants’ executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory. PMID:25688220

  19. The Convallis Rule for Unsupervised Learning in Cortical Networks

    PubMed Central

    Yger, Pierre; Harris, Kenneth D.

    2013-01-01

    The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the “Convallis rule”, mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. PMID:24204224

  20. Associative memory in neural networks with the Hebbian learning rule

    SciTech Connect

    Tsodyks, M.V. )

    1989-05-01

    The authors consider the Hopfield model with the most simple form of the Hebbian learning rule, when only simultaneous activity of pre- and post-synaptic neurons leads to modification of synapse. An extra inhibition proportional to full network activity is needed. Both symmetric nondiluted and asymmetric diluted networks are considered. The model performs well at extremely low level of activity rho < {Kappa}/sup -1/2/, where {Kappa} is the mean number of synapses per neuron.

  1. A hierarchical structure for representing and learning fuzzy rules

    NASA Technical Reports Server (NTRS)

    Yager, Ronald R.

    1993-01-01

    Yager provides an example in which the flat representation of fuzzy if-then rules leads to unsatisfactory results. Consider a rule base consisting to two rules: if U is 12 the V is 29; if U is (10-15) the V is (25-30). If U = 12 we would get V is G where G = (25-30). The application of the defuzzification process leads to a selection of V = 27.5. Thus we see that the very specific instruction was not followed. The problem with the technique used is that the most specific information was swamped by the less specific information. In this paper we shall provide for a new structure for the representation of fuzzy if-then rules. The representational form introduced here is called a Hierarchical Prioritized Structure (HPS) representation. Most importantly in addition to overcoming the problem illustrated in the previous example this HPS representation has an inherent capability to emulate the learning of general rules and provides a reasonable accurate cognitive mapping of how human beings store information.

  2. Children with specific language impairment show rapid, implicit learning of stress assignment rules

    PubMed Central

    Plante, Elena; Bahl, Megha; Vance, Rebecca; Gerken, LouAnn

    2010-01-01

    An implicit learning paradigm was used to assess children's sensitivity to syllable stress information in an artificial language. Study 1 demonstrated that preschool children, with and without specific language impairment (SLI), can generalize patterns of stress heard during a brief period of familiarization, and can also abstract underlying ordered rules by which stress patterns were assigned to syllables. In Study 2, the salience of stressed elements was acoustically enhanced. Counter to expectations, there was no evidence of learning with this manipulation for either the typically developing children or children with SLI. The results suggest that children with SLI and their typically-developing peers are sensitive to syllable stress cues to language structure. However, attempts to draw attention to these patterns by making them more salient may prompt children to use alternate learning strategies that do not lead to an implicit understanding of how stress contributes to the structure of language. PMID:20542518

  3. Chunking, Rule Learning, and Multiple Item Memory in Rat Interleaved Serial Pattern Learning

    ERIC Educational Resources Information Center

    Fountain, Stephen B.; Benson, Don M., Jr.

    2006-01-01

    Nonhuman animals, like humans, appear sensitive to the structure of the elements of sequences, perhaps even when the structure relates nonadjacent elements. In the present study, we examined the contribution of chunking, rule learning, and item memory when rats learned serial patterns composed of two interleaved subpatterns. In one group, the…

  4. Statistical learning is constrained to less abstract patterns in complex sensory input (but not the least).

    PubMed

    Emberson, Lauren L; Rubinstein, Dani Y

    2016-08-01

    The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1-dog1, bird2-dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1-dog_picture1, bird_picture2-dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual

  5. Sensitivity-based adaptive learning rules for binary feedforward neural networks.

    PubMed

    Zhong, Shuiming; Zeng, Xiaoqin; Wu, Shengli; Han, Lixin

    2012-03-01

    This paper proposes a set of adaptive learning rules for binary feedforward neural networks (BFNNs) by means of the sensitivity measure that is established to investigate the effect of a BFNN's weight variation on its output. The rules are based on three basic adaptive learning principles: the benefit principle, the minimal disturbance principle, and the burden-sharing principle. In order to follow the benefit principle and the minimal disturbance principle, a neuron selection rule and a weight adaptation rule are developed. Besides, a learning control rule is developed to follow the burden-sharing principle. The advantage of the rules is that they can effectively guide the BFNN's learning to conduct constructive adaptations and avoid destructive ones. With these rules, a sensitivity-based adaptive learning (SBALR) algorithm for BFNNs is presented. Experimental results on a number of benchmark data demonstrate that the SBALR algorithm has better learning performance than the Madaline rule II and backpropagation algorithms. PMID:24808553

  6. Reaction rate constants of H-abstraction by OH from large ketones: measurements and site-specific rate rules.

    PubMed

    Badra, Jihad; Elwardany, Ahmed E; Farooq, Aamir

    2014-06-28

    Reaction rate constants of the reaction of four large ketones with hydroxyl (OH) are investigated behind reflected shock waves using OH laser absorption. The studied ketones are isomers of hexanone and include 2-hexanone, 3-hexanone, 3-methyl-2-pentanone, and 4-methl-2-pentanone. Rate constants are measured under pseudo-first-order kinetics at temperatures ranging from 866 K to 1375 K and pressures near 1.5 atm. The reported high-temperature rate constant measurements are the first direct measurements for these ketones under combustion-relevant conditions. The effects of the position of the carbonyl group (C=O) and methyl (CH3) branching on the overall rate constant with OH are examined. Using previously published data, rate constant expressions covering, low-to-high temperatures, are developed for acetone, 2-butanone, 3-pentanone, and the hexanone isomers studied here. These Arrhenius expressions are used to devise rate rules for H-abstraction from various sites. Specifically, the current scheme is applied with good success to H-abstraction by OH from a series of n-ketones. Finally, general expressions for primary and secondary site-specific H-abstraction by OH from ketones are proposed as follows (the subscript numbers indicate the number of carbon atoms bonded to the next-nearest-neighbor carbon atom, the subscript CO indicates that the abstraction is from a site next to the carbonyl group (C=O), and the prime is used to differentiate different neighboring environments of a methylene group): PMID:24817270

  7. Applying an exemplar model to an implicit rule-learning task: Implicit learning of semantic structure.

    PubMed

    Chubala, Chrissy M; Johns, Brendan T; Jamieson, Randall K; Mewhort, D J K

    2016-06-01

    Studies of implicit learning often examine peoples' sensitivity to sequential structure. Computational accounts have evolved to reflect this bias. An experiment conducted by Neil and Higham [Neil, G. J., & Higham, P. A.(2012). Implicit learning of conjunctive rule sets: An alternative to artificial grammars. Consciousness and Cognition, 21, 1393-1400] points to limitations in the sequential approach. In the experiment, participants studied words selected according to a conjunctive rule. At test, participants discriminated rule-consistent from rule-violating words but could not verbalize the rule. Although the data elude explanation by sequential models, an exemplar model of implicit learning can explain them. To make the case, we simulate the full pattern of results by incorporating vector representations for the words used in the experiment, derived from the large-scale semantic space models LSA and BEAGLE, into an exemplar model of memory, MINERVA 2. We show that basic memory processes in a classic model of memory capture implicit learning of non-sequential rules, provided that stimuli are appropriately represented. PMID:26730987

  8. Super-Learning of an Optimal Dynamic Treatment Rule.

    PubMed

    Luedtke, Alexander R; van der Laan, Mark J

    2016-05-01

    We consider the estimation of an optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric, beyond possible knowledge about the treatment and censoring mechanisms. We propose data adaptive estimators of this optimal dynamic regime which are defined by sequential loss-based learning under both the blip function and weighted classification frameworks. Rather than a priori selecting an estimation framework and algorithm, we propose combining estimators from both frameworks using a super-learning based cross-validation selector that seeks to minimize an appropriate cross-validated risk. The resulting selector is guaranteed to asymptotically perform as well as the best convex combination of candidate algorithms in terms of loss-based dissimilarity under conditions. We offer simulation results to support our theoretical findings. PMID:27227726

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

    NASA Astrophysics Data System (ADS)

    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.

  10. Some aspects of using new techniques of teaching/learning in education in optics (Abstract only)

    NASA Astrophysics Data System (ADS)

    Suchanska, Malgorzata

    2003-11-01

    The deep learning in Optics can be encouraged by stimulating and considerate teaching. It means that teacher should demonstrate his/her personal commitment to the subject and stress its meaning, relevance and importance to the students. It is also important to allow students to be creative in solving problems and in interpretation of its contents. In order to help the students to become more creative persons it is necessary to enhance the learning process of modern knowledge in Optics, to design and conduct experiments, stimulate passions and interests, allow an access to the e-learning system (Internet) and introduce the psychological training (creativity, communication, lateral thinking etc.) (Abstract only available)

  11. Learning about Regiochemistry from a Hydrogen-Atom Abstraction Reaction in Water

    ERIC Educational Resources Information Center

    Sears-Dundes, Christopher; Huon, Yoeup; Hotz, Richard P.; Pinhas, Allan R.

    2011-01-01

    An experiment has been developed in which the hydrogen-atom abstraction and the coupling of propionitrile, using Fenton's reagent, are investigated. Students learn about the regiochemistry of radical formation, the stereochemistry of product formation, and the interpretation of GC-MS data, in a safe reaction that can be easily completed in one…

  12. An Eye-Tracking Study of Learning from Science Text with Concrete and Abstract Illustrations

    ERIC Educational Resources Information Center

    Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina; Ariasi, Nicola

    2013-01-01

    This study investigated the online process of reading and the offline learning from an illustrated science text. The authors examined the effects of using a concrete or abstract picture to illustrate a text and adopted eye-tracking methodology to trace text and picture processing. They randomly assigned 59 eleventh-grade students to 3 reading…

  13. A neuronal learning rule for sub-millisecond temporal coding

    NASA Astrophysics Data System (ADS)

    Gerstner, Wulfram; Kempter, Richard; van Hemmen, J. Leo; Wagner, Hermann

    1996-09-01

    A PARADOX that exists in auditory and electrosensory neural systems1,2 is that they encode behaviourally relevant signals in the range of a few microseconds with neurons that are at least one order of magnitude slower. The importance of temporal coding in neural information processing is not clear yet3-8. A central question is whether neuronal firing can be more precise than the time constants of the neuronal processes involved9. Here we address this problem using the auditory system of the barn owl as an example. We present a modelling study based on computer simulations of a neuron in the laminar nucleus. Three observations explain the paradox. First, spiking of an 'integrate-and-fire' neuron driven by excitatory postsynaptic potentials with a width at half-maximum height of 250 μs, has an accuracy of 25 μs if the presynaptic signals arrive coherently. Second, the necessary degree of coherence in the signal arrival times can be attained during ontogenetic development by virtue of an unsupervised hebbian learning rule. Learning selects connections with matching delays from a broad distribution of axons with random delays. Third, the learning rule also selects the correct delays from two independent groups of inputs, for example, from the left and right ear.

  14. Finding Influential Users in Social Media Using Association Rule Learning

    NASA Astrophysics Data System (ADS)

    Erlandsson, Fredrik; Bródka, Piotr; Borg, Anton; Johnson, Henric

    2016-04-01

    Influential users play an important role in online social networks since users tend to have an impact on one other. Therefore, the proposed work analyzes users and their behavior in order to identify influential users and predict user participation. Normally, the success of a social media site is dependent on the activity level of the participating users. For both online social networking sites and individual users, it is of interest to find out if a topic will be interesting or not. In this article, we propose association learning to detect relationships between users. In order to verify the findings, several experiments were executed based on social network analysis, in which the most influential users identified from association rule learning were compared to the results from Degree Centrality and Page Rank Centrality. The results clearly indicate that it is possible to identify the most influential users using association rule learning. In addition, the results also indicate a lower execution time compared to state-of-the-art methods.

  15. Rule-Based and Information-Integration Category Learning in Normal Aging

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M.

    2010-01-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated…

  16. Genetic learning in rule-based and neural systems

    NASA Technical Reports Server (NTRS)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  17. Prototype Abstraction and Distinctive Feature Learning: An Application to Learning Chinese Characters

    ERIC Educational Resources Information Center

    Matsuda, Noriyuki; Robbins, Donald

    1977-01-01

    Using recognition tests with new and old exemplars (multiple-component characters) and prototypes (common components), the traditional language learning technique of paired-associate training with exemplars of Chinese characters and specific English translations led to the poorest performance of the three methods tested. Learning either exemplars…

  18. Recognition by variance: learning rules for spatiotemporal patterns.

    PubMed

    Barak, Omri; Tsodyks, Misha

    2006-10-01

    Recognizing specific spatiotemporal patterns of activity, which take place at timescales much larger than the synaptic transmission and membrane time constants, is a demand from the nervous system exemplified, for instance, by auditory processing. We consider the total synaptic input that a single readout neuron receives on presentation of spatiotemporal spiking input patterns. Relying on the monotonic relation between the mean and the variance of a neuron's input current and its spiking output, we derive learning rules that increase the variance of the input current evoked by learned patterns relative to that obtained from random background patterns. We demonstrate that the model can successfully recognize a large number of patterns and exhibits a slow deterioration in performance with increasing number of learned patterns. In addition, robustness to time warping of the input patterns is revealed to be an emergent property of the model. Using a leaky integrate-and-fire realization of the readout neuron, we demonstrate that the above results also apply when considering spiking output. PMID:16907629

  19. Learning trees and rules with set-valued features

    SciTech Connect

    Cohen, W.W.

    1996-12-31

    In most learning systems examples are represented as fixed-length {open_quotes}feature vectors{close_quotes}, the components of which are either real numbers or nominal values. We propose an extension of the feature-vector representation that allows the value of a feature to be a set of strings; for instance, to represent a small white and black dog with the nominal features size and species and the set-valued feature color, one might use a feature vector with size-small, species-canis-familiaris and color-(white, black). Since we make no assumptions about the number of possible set elements, this extension of the traditional feature-vector representation is closely connected to Blum`s {open_quotes}infinite attribute{close_quotes} representation. We argue that many decision tree and rule learning algorithms can be easily extended to set-valued features. We also show by example that many real-world learning problems can be efficiently and naturally represented with set-valued features; in particular, text categorization problems and problems that arise in propositionalizing first-order representations lend themselves to set-valued features.

  20. Bothered by abstractness or engaged by cohesion? Experts' explanations enhance novices' deep-learning.

    PubMed

    Lachner, Andreas; Nückles, Matthias

    2015-03-01

    Experts' explanations have been shown to better enhance novices' transfer as compared with advanced students' explanations. Based on research on expertise and text comprehension, we investigated whether the abstractness or the cohesion of experts' and intermediates' explanations accounted for novices' learning. In Study 1, we showed that the superior cohesion of experts' explanations accounted for most of novices' transfer, whereas the degree of abstractness did not impact novices' transfer performance. In Study 2, we investigated novices' processing while learning with experts' and intermediates' explanations. We found that novices studying experts' explanations actively self-regulated their processing of the explanations, as they showed mainly deep-processing activities, whereas novices learning with intermediates' explanations were mainly engaged in shallow-processing activities by paraphrasing the explanations. Thus, we concluded that subject-matter expertise is a crucial prerequisite for instructors. Despite the abstract character of experts' explanations, their subject-matter expertise enables them to generate highly cohesive explanations that serve as a valuable scaffold for students' construction of flexible knowledge by engaging them in deep-level processing. PMID:25437792

  1. Abstract or Concrete Examples in Learning Mathematics? A Replication and Elaboration of Kaminski, Sloutsky, and Heckler's Study

    ERIC Educational Resources Information Center

    De Bock, Dirk; Deprez, Johan; Van Dooren, Wim; Roelens, Michel; Verschaffel, Lieven

    2011-01-01

    Kaminski, Sloutsky, and Heckler (2008a) published in "Science" a study on "The advantage of abstract examples in learning math," in which they claim that students may benefit more from learning mathematics through a single abstract, symbolic representation than from multiple concrete examples. This publication elicited both enthusiastic and…

  2. Discovering Abstract Concepts to Aid Cross-Map Transfer for a Learning Agent

    NASA Astrophysics Data System (ADS)

    Herpson, Cédric; Corruble, Vincent

    The capacity to apply knowledge in a context different than the one in which it was learned has become crucial within the area of autonomous agents. This paper specifically addresses the issue of transfer of knowledge acquired through online learning in partially observable environments. We investigate the discovery of relevant abstract concepts which help the transfer of knowledge in the context of an environment characterized by its 2D geographical configuration. The architecture proposed is tested in a simple grid-world environment where two agents duel each other. Results show that an agent’s performances are improved through learning, including when it is tested on a map it has not yet seen.

  3. Does hearing two dialects at different times help infants learn dialect-specific rules?

    PubMed Central

    Gonzales, Kalim; Gerken, LouAnn; Gómez, Rebecca L.

    2015-01-01

    Infants might be better at teasing apart dialects with different language rules when hearing the dialects at different times, since language learners do not always combine input heard at different times. However, no previous research has independently varied the temporal distribution of conflicting language input. Twelve-month-olds heard two artificial language streams representing different dialects—a “pure stream” whose sentences adhered to abstract grammar rules like aX bY, and a “mixed stream” wherein any a- or b-word could precede any X- or Y-word. Infants were then tested for generalization of the pure stream’s rules to novel sentences. Supporting our hypothesis, infants showed generalization when the two streams’ sentences alternated in minutes-long intervals without any perceptually salient change across streams (Experiment 2), but not when all sentences from these same streams were randomly interleaved (Experiment 3). Results are interpreted in light of temporal context effects in word learning. PMID:25880342

  4. Are the Products of Statistical Learning Abstract or Stimulus-Specific?

    PubMed Central

    Vouloumanos, Athena; Brosseau-Liard, Patricia E.; Balaban, Evan; Hager, Alanna D.

    2012-01-01

    Learners can segment potential lexical units from syllable streams when statistically variable transitional probabilities between adjacent syllables are the only cues to word boundaries. Here we examine the nature of the representations that result from statistical learning by assessing learners’ ability to generalize across acoustically different stimuli. In three experiments, we compare two possibilities: that the products of statistical segmentation processes are abstract and generalizable representations, or, alternatively, that products of statistical learning are stimulus-bound and restricted to perceptually similar instances. In Experiment 1, learners segmented units from statistically predictable streams, and recognized these units when they were acoustically transformed by temporal reversals. In Experiment 2, learners were able to segment units from temporally reversed syllable streams, but were only able to generalize in conditions of mild acoustic transformation. In Experiment 3, learners were able to recognize statistically segmented units after a voice change but were unable to do so when the novel voice was mildly distorted. Together these results suggest that representations that result from statistical learning can be abstracted to some degree, but not in all listening conditions. PMID:22470357

  5. Learning Problem-Solving Rules as Search through a Hypothesis Space

    ERIC Educational Resources Information Center

    Lee, Hee Seung; Betts, Shawn; Anderson, John R.

    2016-01-01

    Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem…

  6. Rule learning enhances structural plasticity of long-range axons in frontal cortex.

    PubMed

    Johnson, Carolyn M; Peckler, Hannah; Tai, Lung-Hao; Wilbrecht, Linda

    2016-01-01

    Rules encompass cue-action-outcome associations used to guide decisions and strategies in a specific context. Subregions of the frontal cortex including the orbitofrontal cortex (OFC) and dorsomedial prefrontal cortex (dmPFC) are implicated in rule learning, although changes in structural connectivity underlying rule learning are poorly understood. We imaged OFC axonal projections to dmPFC during training in a multiple choice foraging task and used a reinforcement learning model to quantify explore-exploit strategy use and prediction error magnitude. Here we show that rule training, but not experience of reward alone, enhances OFC bouton plasticity. Baseline bouton density and gains during training correlate with rule exploitation, while bouton loss correlates with exploration and scales with the magnitude of experienced prediction errors. We conclude that rule learning sculpts frontal cortex interconnectivity and adjusts a thermostat for the explore-exploit balance. PMID:26949122

  7. Rule learning enhances structural plasticity of long-range axons in frontal cortex

    PubMed Central

    Johnson, Carolyn M.; Peckler, Hannah; Tai, Lung-Hao; Wilbrecht, Linda

    2016-01-01

    Rules encompass cue-action-outcome associations used to guide decisions and strategies in a specific context. Subregions of the frontal cortex including the orbitofrontal cortex (OFC) and dorsomedial prefrontal cortex (dmPFC) are implicated in rule learning, although changes in structural connectivity underlying rule learning are poorly understood. We imaged OFC axonal projections to dmPFC during training in a multiple choice foraging task and used a reinforcement learning model to quantify explore–exploit strategy use and prediction error magnitude. Here we show that rule training, but not experience of reward alone, enhances OFC bouton plasticity. Baseline bouton density and gains during training correlate with rule exploitation, while bouton loss correlates with exploration and scales with the magnitude of experienced prediction errors. We conclude that rule learning sculpts frontal cortex interconnectivity and adjusts a thermostat for the explore–exploit balance. PMID:26949122

  8. A self-learning rule base for command following in dynamical systems

    NASA Technical Reports Server (NTRS)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  9. Learning Syntactic Rules and Tags with Genetic Algorithms for Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules.

    ERIC Educational Resources Information Center

    Losee, Robert M.

    1996-01-01

    The grammars of natural languages may be learned by using genetic algorithm systems such as LUST (Linguistics Using Sexual Techniques) that reproduce and mutate grammatical rules and parts-of-speech tags. In document retrieval or filtering systems, applying tags to the list of terms representing a document provides additional information about…

  10. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations

    PubMed Central

    Kaplan, Jonas T.; Man, Kingson; Greening, Steven G.

    2015-01-01

    Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application. PMID:25859202

  11. Multivariate cross-classification: applying machine learning techniques to characterize abstraction in neural representations.

    PubMed

    Kaplan, Jonas T; Man, Kingson; Greening, Steven G

    2015-01-01

    Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC), and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application. PMID:25859202

  12. Costs and benefits of automatization in category learning of ill-defined rules.

    PubMed

    Raijmakers, Maartje E J; Schmittmann, Verena D; Visser, Ingmar

    2014-03-01

    Learning ill-defined categories (such as the structure of Medin & Schaffer, 1978) involves multiple learning systems and different corresponding category representations, which are difficult to detect. Application of latent Markov analysis allows detection and investigation of such multiple latent category representations in a statistically robust way, isolating low performers and quantifying shifts between latent strategies. We reanalyzed data from three experiments presented in Johansen and Palmeri (2002), which comprised prolonged training of ill-defined categories, with the aim of studying the changing interactions between underlying learning systems. Our results broadly confirm the original conclusion that, in most participants, learning involved a shift from a rule-based to an exemplar-based strategy. Separate analyses of latent strategies revealed that (a) shifts from a rule-based to an exemplar-based strategy resulted in an initial decrease of speed and an increase of accuracy; (b) exemplar-based strategies followed a power law of learning, indicating automatization once an exemplar-based strategy was used; (c) rule-based strategies changed from using pure rules to rules-plus-exceptions, which appeared as a dual processes as indicated by the accuracy and response-time profiles. Results suggest an additional pathway of learning ill-defined categories, namely involving a shift from a simple rule to a complex rule after which this complex rule is automatized as an exemplar-based strategy. PMID:24418795

  13. Abstract-concept learning carryover effects from the initial training set in pigeons (Columba livia).

    PubMed

    Nakamura, Tamo; Wright, Anthony A; Katz, Jeffrey S; Bodily, Kent D; Sturz, Bradley R

    2009-02-01

    Three groups of pigeons were trained in a same/different task with 32, 64, or 1,024 color-picture stimuli. They were tested with novel transfer pictures. The training-testing cycle was repeated with training-set doublings. The 32-item group learned the same/different task as rapidly as a previous 8-item group and transferred better than the 8-item group at the 32-item training set. The 64- and 1,024-item groups learned the task only somewhat slower than other groups, but their transfer was better and equivalent to baseline performances. These results show that pigeons trained with small sets (e.g., 8 items) have carryover effects that hamper transfer when the training set is expanded. Without carryover effects (i.e., initial transfer from the 32- and 64-item groups), pigeons show the same degree of transfer as rhesus and capuchin monkeys at these same set sizes. This finding has implications for the general ability of abstract-concept learning across species with different neural architectures. PMID:19236147

  14. Bigger Knows Better: Young Children Selectively Learn Rule Games from Adults Rather than from Peers

    ERIC Educational Resources Information Center

    Rakoczy, Hannes; Hamann, Katharina; Warneken, Felix; Tomasello, Michael

    2010-01-01

    Preschoolers' selective learning from adult versus peer models was investigated. Extending previous research, children from age 3 were shown to selectively learn simple rule games from adult rather than peer models. Furthermore, this selective learning was not confined to preferentially performing certain acts oneself, but more specifically had a…

  15. Criterion learning in rule-based categorization: Simulation of neural mechanism and new data

    PubMed Central

    Helie, Sebastien; Ell, Shawn W.; Filoteo, J. Vincent; Maddox, W. Todd

    2015-01-01

    In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g, categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define ‘long’ and ‘short’). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL’s implications for future research on rule learning. PMID:25682349

  16. Teaching with Concrete and Abstract Visual Representations: Effects on Students' Problem Solving, Problem Representations, and Learning Perceptions

    ERIC Educational Resources Information Center

    Moreno, Roxana; Ozogul, Gamze; Reisslein, Martin

    2011-01-01

    In 3 experiments, we examined the effects of using concrete and/or abstract visual problem representations during instruction on students' problem-solving practice, near transfer, problem representations, and learning perceptions. In Experiments 1 and 2, novice students learned about electrical circuit analysis with an instructional program that…

  17. Incremental learning of probabilistic rules from clinical databases based on rough set theory.

    PubMed Central

    Tsumoto, S.; Tanaka, H.

    1997-01-01

    Several rule induction methods have been introduced in order to discover meaningful knowledge from databases, including medical domain. However, most of the approaches induce rules from all the data in databases and cannot induce incrementally when new samples are derived. In this paper, a new approach to knowledge acquisition, which induce probabilistic rules incrementally by using rough set technique, is introduced and was evaluated on two clinical databases. The results show that this method induces the same rules as those induced by ordinary non-incremental learning methods, which extract rules from all the datasets, but that the former method requires more computational resources than the latter approach. PMID:9357616

  18. Learning Problem-Solving Rules as Search Through a Hypothesis Space.

    PubMed

    Lee, Hee Seung; Betts, Shawn; Anderson, John R

    2016-07-01

    Learning to solve a class of problems can be characterized as a search through a space of hypotheses about the rules for solving these problems. A series of four experiments studied how different learning conditions affected the search among hypotheses about the solution rule for a simple computational problem. Experiment 1 showed that a problem property such as computational difficulty of the rules biased the search process and so affected learning. Experiment 2 examined the impact of examples as instructional tools and found that their effectiveness was determined by whether they uniquely pointed to the correct rule. Experiment 3 compared verbal directions with examples and found that both could guide search. The final experiment tried to improve learning by using more explicit verbal directions or by adding scaffolding to the example. While both manipulations improved learning, learning still took the form of a search through a hypothesis space of possible rules. We describe a model that embodies two assumptions: (1) the instruction can bias the rules participants hypothesize rather than directly be encoded into a rule; (2) participants do not have memory for past wrong hypotheses and are likely to retry them. These assumptions are realized in a Markov model that fits all the data by estimating two sets of probabilities. First, the learning condition induced one set of Start probabilities of trying various rules. Second, should this first hypothesis prove wrong, the learning condition induced a second set of Choice probabilities of considering various rules. These findings broaden our understanding of effective instruction and provide implications for instructional design. PMID:26292648

  19. Using an improved association rules mining optimization algorithm in web-based mobile-learning system

    NASA Astrophysics Data System (ADS)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

    Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

  20. The evolution of social learning rules: payoff-biased and frequency-dependent biased transmission.

    PubMed

    Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin

    2009-09-21

    Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning. PMID:19501102

  1. Learning the Rules: The Anatomy of Children's Relationships.

    ERIC Educational Resources Information Center

    Bigelow, Brian J.; Tesson, Geoffrey; Lewko, John H.

    This book explores the process and characteristics of children's personal and social relationships. To determine what relationships mean to children and how children manage those relationships, a recursive interviewing technique was used with nearly a thousand children to detail children's social rules. Those rules cover a range of social issues,…

  2. Ensemble learning with trees and rules: supervised, semi-supervised, unsupervised

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this article, we propose several new approaches for post processing a large ensemble of conjunctive rules for supervised and semi-supervised learning problems. We show with various examples that for high dimensional regression problems the models constructed by the post processing the rules with ...

  3. RuleML-Based Learning Object Interoperability on the Semantic Web

    ERIC Educational Resources Information Center

    Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

    2008-01-01

    Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

  4. Rule-based and information-integration category learning in normal aging.

    PubMed

    Maddox, W Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M

    2010-08-01

    The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated processes, whereas information-integration is thought to involve implicit, striatally mediated processes. As a group, older adults showed rule-based and information-integration deficits. A series of models were applied that provided insights onto the type of strategy used to solve the task. Interestingly, when the analyses focused only on participants who used the task appropriate strategy in the final block of trials, the age-related rule-based deficit disappeared whereas the information-integration deficit remained. For this group of individuals, the final block information-integration deficit was due to less consistent application of the task appropriate strategy by older adults, and over the course of learning these older adults shifted from an explicit hypothesis-testing strategy to the task appropriate strategy later in learning. In addition, the use of the task appropriate strategy was associated with less interference and better inhibitory control for rule-based and information-information learning, whereas use of the task appropriate strategy was associated with greater working memory and better new verbal learning only for the rule-based task. These results suggest that normal aging impacts both forms of category learning and that there are some important similarities and differences in the explanatory locus of these deficits. The data also support a two-component model of information-integration category learning that includes a striatal component that mediated procedural-based learning, and a prefrontal cortical component that mediates the transition from hypothesis-testing to procedural-based strategies

  5. Learning from Stochastic Rules by Spherical Perceptrons under Finite Temperature ---Optimal Temperature and Asymptotic Learning Curve---

    NASA Astrophysics Data System (ADS)

    Uezu, Tatsuya

    2011-04-01

    In the problem of learning under external disturbance, there is a possibility that the existence of some tolerance or flexibility in the system weakens the effect of noise and helps the system to perform more efficiently. In a previous letter, we gave one example of such phenomena in learning from stochastic rules by spherical perceptrons adopting the Gibbs algorithm using statistical mechanical methods. By the replica method, we showed that, in the output noise model, there exists an optimal temperature at which the generalization error takes its minimum for the stable replica symmetric (RS) solution. On the other hand, for other types of noise including input noise, it was shown that no such temperature exists up to the one-step replica symmetry breaking (1RSB) solution. That is, it was shown that for the asymptotic region of a large number of training sets, the RS solution becomes unstable, and the asymptotic behavior is determined by the 1RSB solution, The asymptotic expressions for learning curves were derived, and it turned out that, within the 1RSB solution, the learning curve does not depend on temperature. In this study, we give a detailed derivation of these results and also the results obtained by simulated annealing and exchange Monte Carlo simulation. The numerical results support the theoretical predictions.

  6. Code-specific learning rules improve action selection by populations of spiking neurons.

    PubMed

    Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

    2014-08-01

    Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space. PMID:24875790

  7. 8-Month-Old Infants Spontaneously Learn and Generalize Hierarchical Rules

    PubMed Central

    Werchan, Denise M.; Collins, Anne G. E.; Frank, Michael J.; Amso, Dima

    2015-01-01

    The ability to extract hierarchically organized rule structures from noisy environments is critical to human cognitive, social, and emotional intelligence. Adults spontaneously create hierarchical rule structures of this sort. In the present research, we conducted two experiments to examine the previously unknown developmental origins of this hallmark skill. In Experiment 1, we exploited a visual paradigm previously shown to elicit incidental hierarchical rule learning in adults. In Experiment 2, we used the same learning structure to examine whether these hierarchical-rule-learning mechanisms are domain general and can help infants learn spoken object-label mappings across different speaker contexts. In both experiments, we found that 8-month-olds created and generalized hierarchical rules during learning. Eyeblink rate, an exploratory indicator of striatal dopamine activity, mirrored behavioral-learning patterns. Our results provide direct evidence that the human brain is predisposed to extract knowledge from noisy environments, and they add a fundamental learning mechanism to what is currently known about the neurocognitive toolbox available to infants. PMID:25878172

  8. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    NASA Technical Reports Server (NTRS)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  9. Inferring learning rules from distributions of firing rates in cortical neurons.

    PubMed

    Lim, Sukbin; McKee, Jillian L; Woloszyn, Luke; Amit, Yali; Freedman, David J; Sheinberg, David L; Brunel, Nicolas

    2015-12-01

    Information about external stimuli is thought to be stored in cortical circuits through experience-dependent modifications of synaptic connectivity. These modifications of network connectivity should lead to changes in neuronal activity as a particular stimulus is repeatedly encountered. Here we ask what plasticity rules are consistent with the differences in the statistics of the visual response to novel and familiar stimuli in inferior temporal cortex, an area underlying visual object recognition. We introduce a method that allows one to infer the dependence of the presumptive learning rule on postsynaptic firing rate, and we show that the inferred learning rule exhibits depression for low postsynaptic rates and potentiation for high rates. The threshold separating depression from potentiation is strongly correlated with both mean and s.d. of the firing rate distribution. Finally, we show that network models implementing a rule extracted from data show stable learning dynamics and lead to sparser representations of stimuli. PMID:26523643

  10. Prefrontal Contributions to Rule-Based and Information-Integration Category Learning

    ERIC Educational Resources Information Center

    Schnyer, David M.; Maddox, W. Todd; Ell, Shawn; Davis, Sarah; Pacheco, Jenni; Verfaellie, Mieke

    2009-01-01

    Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). "Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks." "Neuropsychologia", 44(10), 1737-1751; Maddox, W. T. & Filoteo, J. V. (2007). "Modeling visual…

  11. How Do Infants and Toddlers Learn the Rules? Family Discipline and Young Children

    ERIC Educational Resources Information Center

    Smith, Anne B.

    2004-01-01

    This paper examines the issue of how under three year-olds learn the rules of appropriate behaviour in the light of sociocultural, attachment, social learning, ecological theory and sociology of childhood theories. Discipline involves teaching children how to behave acceptably in their family and society, while physical punishment is the use of…

  12. Dog Is a Dog Is a Dog: Infant Rule Learning Is Not Specific to Language

    ERIC Educational Resources Information Center

    Saffran, Jenny R.; Pollak, Seth D.; Seibel, Rebecca L.; Shkolnik, Anna

    2007-01-01

    Human infants possess powerful learning mechanisms used for the acquisition of language. To what extent are these mechanisms domain specific? One well-known infant language learning mechanism is the ability to detect and generalize rule-like similarity patterns, such as ABA or ABB [Marcus, G. F., Vijayan, S., Rao, S. B., & Vishton, P. M. (1999).…

  13. Dog is a dog is a dog: Infant rule learning is not specific to language

    PubMed Central

    Saffran, Jenny R.; Pollak, Seth D.; Seibel, Rebecca L.; Shkolnik, Anna

    2007-01-01

    Human infants possess powerful learning mechanisms used for the acquisition of language. To what extent are these mechanisms domain-specific? One well-known infant language learning mechanism is the ability to detect and generalize rule-like similarity patterns, such as ABA or ABB (Marcus et al., 1999). The results of three experiments demonstrate that 7-month-old infants can detect and generalize these same patterns when the elements consist of pictures of animals (dogs and cats). These findings indicate that rule learning of this type is not specific to language acquisition. PMID:17188676

  14. Rule-based mechanisms of learning for intelligent adaptive flight control

    NASA Technical Reports Server (NTRS)

    Handelman, David A.; Stengel, Robert F.

    1990-01-01

    How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

  15. Effects of the Memorization of Rule Statements on Performance, Retention, and Transfer in a Computer-Based Learning Task.

    ERIC Educational Resources Information Center

    Towle, Nelson J.

    Research sought to determine whether memorization of rule statements before, during or after instruction in rule application skills would facilitate the acquisition and/or retention of rule-governed behavior as compared to no-rule statement memorization. A computer-assisted instructional (CAI) program required high school students to learn to a…

  16. Multi Objective Dynamic Job Shop Scheduling using Composite Dispatching Rule and Reinforcement Learning

    NASA Astrophysics Data System (ADS)

    Chen, Xili; Hao, Xinchang; Lin, Hao Wen; Murata, Tomohiro

    The applications of composite dispatching rules for multi objective dynamic scheduling have been widely studied in literature. In general, a composite dispatching rule is a combination of several elementary dispatching rules, which is designed to optimize multiple objectives of interest under a certain scheduling environment. The relative importance of elementary dispatching rules is modeled by weight factors. A critical issue for implementation of composite dispatching rule is that the inappropriate weight values may result in poor performance. This paper presents an offline scheduling knowledge acquisition method based on reinforcement learning using simulation technique. The scheduling knowledge is applied to adjust the appropriate weight values of elementary dispatching rules in composite manner with respect to work in process fluctuation of machines during online scheduling. Implementation of the proposed method in a two objectives dynamic job shop scheduling problem is demonstrated and the results are satisfactory.

  17. LDA '94: A Capital IDEA. Poster Session Abstracts of the International Conference of the Learning Disabilities Association of America (Washington, D.C., March 16-19, 1994).

    ERIC Educational Resources Information Center

    Russell, Steven C., Comp.

    This booklet brings together one-page to two-page abstracts from research poster sessions held at a conference on learning disabilities. The 17 research abstracts are presented within four poster session categories: (1) research on assessment and characteristics of students with learning disabilities (with abstracts on handwriting, mainstreaming…

  18. Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

    ERIC Educational Resources Information Center

    Tabor, Whitney; Cho, Pyeong W.; Dankowicz, Harry

    2013-01-01

    Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…

  19. Strengthening the case for stimulus-specificity in artificial grammar learning: no evidence for abstract representations with extended exposure.

    PubMed

    Johansson, Tobias

    2009-01-01

    Different theories have been proposed regarding the nature of the mental representations formed as a result of implicit learning of sequential regularities. Some theories postulate abstract surface-independent representations, while other theories postulate stimulus-specific representations. This article reports three experiments investigating the development of abstract representations in artificial grammar learning (AGL), using a methodological approach developed by Conway and Christiansen (2006). In all the experiments, the number of blocks during the exposure phase was manipulated (6 blocks vs. 18 blocks of exposure to sequences). Experiments 1 and 2 investigated both visual and auditory learning where sequences were presented element-by-element. Experiment 3 investigated visual learning using a sequence-by-sequence presentation technique more commonly used in visual AGL studies. Extending previous research (Conway & Christiansen, 2006) and in support of stimulus-specific accounts, the results of the experiments showed that extended observational learning results in increased stimulus-specific knowledge rather than abstraction towards surface-independent representations. PMID:19289361

  20. Wavefront reconstruction by machine learning using the delta rule

    NASA Astrophysics Data System (ADS)

    Angel, J. Roger P.

    1994-05-01

    In this paper we use phase screen models to illustrate the power of the delta rule, by obtaining the optimum reconstructor for a Shack-Hartmann sensor with just 6 subapertures in the form of pie segments. The dependence of the matrix elements and residual error on measurement noise is determined, and the accuracy compared with theoretical limits. Reconstructors for more complex problems involving time dependence and multiple laser spots are ideal applications for the method.

  1. A learning rule for very simple universal approximators consisting of a single layer of perceptrons.

    PubMed

    Auer, Peter; Burgsteiner, Harald; Maass, Wolfgang

    2008-06-01

    One may argue that the simplest type of neural networks beyond a single perceptron is an array of several perceptrons in parallel. In spite of their simplicity, such circuits can compute any Boolean function if one views the majority of the binary perceptron outputs as the binary output of the parallel perceptron, and they are universal approximators for arbitrary continuous functions with values in [0,1] if one views the fraction of perceptrons that output 1 as the analog output of the parallel perceptron. Note that in contrast to the familiar model of a "multi-layer perceptron" the parallel perceptron that we consider here has just binary values as outputs of gates on the hidden layer. For a long time one has thought that there exists no competitive learning algorithm for these extremely simple neural networks, which also came to be known as committee machines. It is commonly assumed that one has to replace the hard threshold gates on the hidden layer by sigmoidal gates (or RBF-gates) and that one has to tune the weights on at least two successive layers in order to achieve satisfactory learning results for any class of neural networks that yield universal approximators. We show that this assumption is not true, by exhibiting a simple learning algorithm for parallel perceptrons - the parallel delta rule (p-delta rule). In contrast to backprop for multi-layer perceptrons, the p-delta rule only has to tune a single layer of weights, and it does not require the computation and communication of analog values with high precision. Reduced communication also distinguishes our new learning rule from other learning rules for parallel perceptrons such as MADALINE. Obviously these features make the p-delta rule attractive as a biologically more realistic alternative to backprop in biological neural circuits, but also for implementations in special purpose hardware. We show that the p-delta rule also implements gradient descent-with regard to a suitable error measure

  2. Neural learning rules for the vestibulo-ocular reflex

    NASA Technical Reports Server (NTRS)

    Raymond, J. L.; Lisberger, S. G.

    1998-01-01

    Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies from 0.5 to 10 Hz. A comparison of simple-spike and vestibular signals contained the information required to guide learning only at low stimulus frequencies, and a comparison of climbing-fiber and simple-spike signals contained the information required to guide learning only at high stimulus frequencies. Learning could be guided by comparison of climbing-fiber and vestibular signals at all stimulus frequencies tested, but only if climbing fiber responses were compared with the vestibular signals present 100 msec earlier. Computational analysis demonstrated that this conclusion is valid even if there is a broad range of vestibular signals at the site of plasticity. Simulations also indicated that the comparison of vestibular and climbing-fiber signals across the 100 msec delay must be implemented by a subcellular "eligibility" trace rather than by neural circuits that delay the vestibular inputs to the site of plasticity. The results suggest two alternative accounts of learning in the VOR. Either there are multiple mechanisms of learning that use different combinations of neural signals to drive plasticity, or there is a single mechanism tuned to climbing-fiber activity that follows activity in vestibular pathways by approximately 100 msec.

  3. Effects of Age, Reminders, and Task Difficulty on Young Children's Rule-Switching Flexibility

    ERIC Educational Resources Information Center

    Deak, Gedeon O.; Ray, Shanna D.; Pick, Anne D.

    2004-01-01

    To test preschoolers' ability to flexibly switch between abstract rules differing in difficulty, ninety-three 3-, 4-, and 5-year-olds were instructed to switch from an (easier) shape-sorting to a (harder) function-sorting rule, or vice versa. Children learned one rule, sorted four test sets, then learned the other rule, and sorted four more sets.…

  4. Rule-Based Category Learning in Children: The Role of Age and Executive Functioning

    PubMed Central

    Rabi, Rahel; Minda, John Paul

    2014-01-01

    Rule-based category learning was examined in 4–11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning. PMID:24489658

  5. Learning and Innovative Elements of Strategy Adoption Rules Expand Cooperative Network Topologies

    PubMed Central

    Wang, Shijun; Szalay, Máté S.; Zhang, Changshui; Csermely, Peter

    2008-01-01

    Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoner's Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems. PMID:18398453

  6. Lexical distributional cues, but not situational cues, are readily used to learn abstract locative verb-structure associations.

    PubMed

    Twomey, Katherine E; Chang, Franklin; Ambridge, Ben

    2016-08-01

    Children must learn the structural biases of locative verbs in order to avoid making overgeneralisation errors (e.g., (∗)I filled water into the glass). It is thought that they use linguistic and situational information to learn verb classes that encode structural biases. In addition to situational cues, we examined whether children and adults could use the lexical distribution of nouns in the post-verbal noun phrase of transitive utterances to assign novel verbs to locative classes. In Experiment 1, children and adults used lexical distributional cues to assign verb classes, but were unable to use situational cues appropriately. In Experiment 2, adults generalised distributionally-learned classes to novel verb arguments, demonstrating that distributional information can cue abstract verb classes. Taken together, these studies show that human language learners can use a lexical distributional mechanism that is similar to that used by computational linguistic systems that use large unlabelled corpora to learn verb meaning. PMID:27183399

  7. Learning "Rules" of Practice within the Context of the Practicum Triad: A Case Study of Learning to Teach

    ERIC Educational Resources Information Center

    Chalies, Sebastien; Escalie, Guillaume; Stefano, Bertone; Clarke, Anthony

    2012-01-01

    This case study sought to determine the professional development circumstances in which a preservice teacher learned rules of practice (Wittgenstein, 1996) on practicum while interacting with a cooperating teacher and university supervisor. Borrowing from a theoretical conceptualization of teacher professional development based on the postulates…

  8. A biologically plausible learning rule for the Infomax on recurrent neural networks.

    PubMed

    Hayakawa, Takashi; Kaneko, Takeshi; Aoyagi, Toshio

    2014-01-01

    A fundamental issue in neuroscience is to understand how neuronal circuits in the cerebral cortex play their functional roles through their characteristic firing activity. Several characteristics of spontaneous and sensory-evoked cortical activity have been reproduced by Infomax learning of neural networks in computational studies. There are, however, still few models of the underlying learning mechanisms that allow cortical circuits to maximize information and produce the characteristics of spontaneous and sensory-evoked cortical activity. In the present article, we derive a biologically plausible learning rule for the maximization of information retained through time in dynamics of simple recurrent neural networks. Applying the derived learning rule in a numerical simulation, we reproduce the characteristics of spontaneous and sensory-evoked cortical activity: cell-assembly-like repeats of precise firing sequences, neuronal avalanches, spontaneous replays of learned firing sequences and orientation selectivity observed in the primary visual cortex. We further discuss the similarity between the derived learning rule and the spike timing-dependent plasticity of cortical neurons. PMID:25505404

  9. A biologically plausible learning rule for the Infomax on recurrent neural networks

    PubMed Central

    Hayakawa, Takashi; Kaneko, Takeshi; Aoyagi, Toshio

    2014-01-01

    A fundamental issue in neuroscience is to understand how neuronal circuits in the cerebral cortex play their functional roles through their characteristic firing activity. Several characteristics of spontaneous and sensory-evoked cortical activity have been reproduced by Infomax learning of neural networks in computational studies. There are, however, still few models of the underlying learning mechanisms that allow cortical circuits to maximize information and produce the characteristics of spontaneous and sensory-evoked cortical activity. In the present article, we derive a biologically plausible learning rule for the maximization of information retained through time in dynamics of simple recurrent neural networks. Applying the derived learning rule in a numerical simulation, we reproduce the characteristics of spontaneous and sensory-evoked cortical activity: cell-assembly-like repeats of precise firing sequences, neuronal avalanches, spontaneous replays of learned firing sequences and orientation selectivity observed in the primary visual cortex. We further discuss the similarity between the derived learning rule and the spike timing-dependent plasticity of cortical neurons. PMID:25505404

  10. The Aptitude-Treatment Interaction Effects on the Learning of Grammar Rules

    ERIC Educational Resources Information Center

    Hwu, Fenfang; Sun, Shuyan

    2012-01-01

    The present study investigates the interaction between two types of explicit instructional approaches, deduction and explicit-induction, and the level of foreign language aptitude in the learning of grammar rules. Results indicate that on the whole the two equally explicit instructional approaches did not differentially affect learning…

  11. Effectiveness of Visual Imagery versus Rule-Based Strategies in Teaching Spelling to Learning Disabled Students.

    ERIC Educational Resources Information Center

    Darch, Craig; Simpson, Robert G.

    1990-01-01

    Among 28 upper elementary learning-disabled students in a summer remedial program, those that were taught spelling with explicit rule-based strategies out-performed students presented with a visual imagery mnemonic on unit tests, a posttest, and a standardized spelling test. Contains 20 references. (SV)

  12. On the Relationship between Implicit and Explicit Modes in the Learning of a Complex Rule Structure.

    ERIC Educational Resources Information Center

    Reber, Arthur S.; And Others

    1980-01-01

    Reber found that subjects given neutral instructions to memorize letter strings from a synthetic language learned more about the underlying grammar than those instructed to try discovering the rules for letter order. Two experiments explored the relationship between implicit and explicit processes in the acquisition of complex knowledge.…

  13. Should There Be a Three-Strikes Rule against Pure Discovery Learning?

    ERIC Educational Resources Information Center

    Mayer, Richard E.

    2004-01-01

    The author's thesis is that there is sufficient research evidence to make any reasonable person skeptical about the benefits of discovery learning--practiced under the guise of cognitive constructivism or social constructivism--as a preferred instructional method. The author reviews research on discovery of problem-solving rules culminating in the…

  14. An Examination of Strategy Implementation during Abstract Nonlinguistic Category Learning in Aphasia

    ERIC Educational Resources Information Center

    Vallila-Rohter, Sofia; Kiran, Swathi

    2015-01-01

    Purpose: Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method: Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases…

  15. Meaningful Cultural Learning by Imitative Participation: The Case of Abstract Thinking in Primary School

    ERIC Educational Resources Information Center

    van Oers, Bert

    2012-01-01

    The article describes a theory-driven approach to meaningful learning in primary schools, based on the Vygotskian cultural-historical theory of human development and learning. This approach is elaborated into an educational concept called "developmental education" that is implemented in the Netherlands in many primary schools. In this approach,…

  16. Learning of Abstract Concepts through Full-Body Interaction: A Systematic Review

    ERIC Educational Resources Information Center

    Malinverni, Laura; Pares, Narcis

    2014-01-01

    Over the past ten years several learning environments based on novel interaction modalities have been developed. Within this field, Full-body Interaction Learning Environments open promising possibilities given their capacity to involve the users at different levels, such as sensorimotor experience, cognitive aspects and affective factors.…

  17. Explicating a Mechanism for Conceptual Learning: Elaborating the Construct of Reflective Abstraction

    ERIC Educational Resources Information Center

    Simon, Martin A.; Tzur, Ron; Heinz, Karen; Kinzel, Margaret

    2004-01-01

    We articulate and explicate a mechanism for mathematics conceptual learning that can serve as a basis for the design of mathematics lessons. The mechanism, reflection on activity-effect relationships, addresses the learning paradox (Pascual-Leone, 1976), a paradox that derives from careful attention to the construct of assimilation (Piaget, 1970).…

  18. The Distributed Learning Effect for Children's Acquisition of an Abstract Syntactic Construction

    ERIC Educational Resources Information Center

    Ambridge, Ben; Theakston, Anna L.; Lieven, Elena V. M.; Tomasello, Michael

    2006-01-01

    In many cognitive domains, learning is more effective when exemplars are distributed over a number of sessions than when they are all presented within one session. The present study investigated this "distributed learning effect" with respect to English-speaking children's acquisition of a complex grammatical construction. Forty-eight children…

  19. Perceptual Learning Improves Adult Amblyopic Vision Through Rule-Based Cognitive Compensation

    PubMed Central

    Zhang, Jun-Yun; Cong, Lin-Juan; Klein, Stanley A.; Levi, Dennis M.; Yu, Cong

    2014-01-01

    Purpose. We investigated whether perceptual learning in adults with amblyopia could be enabled to transfer completely to an orthogonal orientation, which would suggest that amblyopic perceptual learning results mainly from high-level cognitive compensation, rather than plasticity in the amblyopic early visual brain. Methods. Nineteen adults (mean age = 22.5 years) with anisometropic and/or strabismic amblyopia were trained following a training-plus-exposure (TPE) protocol. The amblyopic eyes practiced contrast, orientation, or Vernier discrimination at one orientation for six to eight sessions. Then the amblyopic or nonamblyopic eyes were exposed to an orthogonal orientation via practicing an irrelevant task. Training was first performed at a lower spatial frequency (SF), then at a higher SF near the cutoff frequency of the amblyopic eye. Results. Perceptual learning was initially orientation specific. However, after exposure to the orthogonal orientation, learning transferred to an orthogonal orientation completely. Reversing the exposure and training order failed to produce transfer. Initial lower SF training led to broad improvement of contrast sensitivity, and later higher SF training led to more specific improvement at high SFs. Training improved visual acuity by 1.5 to 1.6 lines (P < 0.001) in the amblyopic eyes with computerized tests and a clinical E acuity chart. It also improved stereoacuity by 53% (P < 0.001). Conclusions. The complete transfer of learning suggests that perceptual learning in amblyopia may reflect high-level learning of rules for performing a visual discrimination task. These rules are applicable to new orientations to enable learning transfer. Therefore, perceptual learning may improve amblyopic vision mainly through rule-based cognitive compensation. PMID:24550359

  20. The Effectiveness of Education and Schooling Activities with Respect to Learning Styles on the Learning of Abstract and Tangible Concepts of Social Studies by Students

    ERIC Educational Resources Information Center

    Seker, Mustafa

    2013-01-01

    This research reviews the effects of education and schooling activities that are conducted with respect to different learning styles on the success of teaching abstract and tangible concepts of 6th Grade Social Studies, and researches whether the demographic variables (age, gender) of the students had any effect on this success levels. To do so, 2…

  1. Enabling Active Learning. Conference Programme and Abstracts of the Association for Learning Technology Conference (1st, Hull, England, United Kingdom, September 19-21, 1994).

    ERIC Educational Resources Information Center

    Heath, Simon, Ed.

    This program for the 1994 Association for Learning Technology Conference provides a conference schedule and summarizes the presentations of the discussion workshops, hands-on workshops, live demonstrations, and poster sessions. Abstracts of the following papers presented at the conference are included: "The Conceptualisation Cycle" (J. Mayes & L.…

  2. Three machine learning techniques for automatic determination of rules to control locomotion.

    PubMed

    Jonić, S; Janković, T; Gajić, V; Popović, D

    1999-03-01

    Automatic prediction of gait events (e.g., heel contact, flat foot, initiation of the swing, etc.) and corresponding profiles of the activations of muscles is important for real-time control of locomotion. This paper presents three supervised machine learning (ML) techniques for prediction of the activation patterns of muscles and sensory data, based on the history of sensory data, for walking assisted by a functional electrical stimulation (FES). Those ML's are: 1) a multilayer perceptron with Levenberg-Marquardt modification of backpropagation learning algorithm; 2) an adaptive-network-based fuzzy inference system (ANFIS); and 3) a combination of an entropy minimization type of inductive learning (IL) technique and a radial basis function (RBF) type of artificial neural network with orthogonal least squares learning algorithm. Here we show the prediction of the activation of the knee flexor muscles and the knee joint angle for seven consecutive strides based on the history of the knee joint angle and the ground reaction forces. The data used for training and testing of ML's was obtained from a simulation of walking assisted with an FES system [39]. The ability of generating rules for an FES controller was selected as the most important criterion when comparing the ML's. Other criteria such as generalization of results, computational complexity, and learning rate were also considered. The minimal number of rules and the most explicit and comprehensible rules were obtained by ANFIS. The best generalization was obtained by the IL and RBF network. PMID:10097465

  3. Imitation as a mechanism in cognitive development: a cross-cultural investigation of 4-year-old children’s rule learning

    PubMed Central

    Wang, Zhidan; Williamson, Rebecca A.; Meltzoff, Andrew N.

    2015-01-01

    Children learn about the social and physical world by observing other people’s acts. This experiment tests both Chinese and American children’s learning of a rule. For theoretical reasons we chose the rule of categorizing objects by the weight. Children, age 4 years, saw an adult heft four visually-identical objects and sort them into two bins based on an invisible property—the object’s weight. Children who saw this categorization behavior were more likely to sort those objects by weight than were children who saw control actions using the same objects and the same bins. Crucially, children also generalized to a novel set of objects with no further demonstration, suggesting rule learning. We also report that high-fidelity imitation of the adult’s “hefting” acts may give children crucial experience with the objects’ weights, which could then be used to infer the more abstract rule. The connection of perception, action, and cognition was found in children from both cultures, which leads to broad implications for how the imitation of adults’ acts functions as a lever in cognitive development. PMID:26029132

  4. Mining Formative Evaluation Rules Using Web-Based Learning Portfolios for Web-Based Learning Systems

    ERIC Educational Resources Information Center

    Chen, Chih-Ming; Hong, Chin-Ming; Chen, Shyuan-Yi; Liu, Chao-Yu

    2006-01-01

    Learning performance assessment aims to evaluate what knowledge learners have acquired from teaching activities. Objective technical measures of learning performance are difficult to develop, but are extremely important for both teachers and learners. Learning performance assessment using learning portfolios or web server log data is becoming an…

  5. The application of top-down abstraction learning using prediction as a supervisory signal to cyber security

    NASA Astrophysics Data System (ADS)

    Mugan, Jonathan; Khalili, Aram E.

    2014-05-01

    Current computer systems are dumb automatons, and their blind execution of instructions makes them open to attack. Their inability to reason means that they don't consider the larger, constantly changing context outside their immediate inputs. Their nearsightedness is particularly dangerous because, in our complex systems, it is difficult to prevent all exploitable situations. Additionally, the lack of autonomous oversight of our systems means they are unable to fight through attacks. Keeping adversaries completely out of systems may be an unreasonable expectation, and our systems need to adapt to attacks and other disruptions to achieve their objectives. What is needed is an autonomous controller within the computer system that can sense the state of the system and reason about that state. In this paper, we present Self-Awareness Through Predictive Abstraction Modeling (SATPAM). SATPAM uses prediction to learn abstractions that allow it to recognize the right events at the right level of detail. These abstractions allow SATPAM to break the world into small, relatively independent, pieces that allow employment of existing reasoning methods. SATPAM goes beyond classification-based machine learning and statistical anomaly detection to be able to reason about the system, and SATPAM's knowledge representation and reasoning is more like that of a human. For example, humans intuitively know that the color of a car is not relevant to any mechanical problem, and SATPAM provides a plausible method whereby a machine can acquire such reasoning patterns. In this paper, we present the initial experimental results using SATPAM.

  6. Children with Specific Language Impairment Show Rapid, Implicit Learning of Stress Assignment Rules

    ERIC Educational Resources Information Center

    Plante, Elena; Bahl, Megha; Vance, Rebecca; Gerken, LouAnn

    2010-01-01

    An implicit learning paradigm was used to assess children's sensitivity to syllable stress information in an artificial language. Study 1 demonstrated that preschool children, with and without specific language impairment (SLI), can generalize patterns of stress heard during a brief period of familiarization, and can also abstract underlying…

  7. Effects of Inter- and Intra-Modal Redundancy on Infants' Rule Learning

    ERIC Educational Resources Information Center

    Thiessen, Erik D.

    2012-01-01

    Previous research indicates that infants generalize syntactic-like structures to novel exemplars in a way that has been characterized as abstract and algebraic (Marcus et al., 1999). Infants appear to learn and generalize from speech more successfully than from nonspeech stimuli (Marcus, Fernandes, & Johnson, 2007). In this series of experiments,…

  8. Implementation of Abstract Data Types in Dynamic Sketches for Learning Geometry

    ERIC Educational Resources Information Center

    Jasute, Egle; Dagiene, Valentina

    2014-01-01

    A long-term observation of students' usage of a dynamic geometry in a classroom at all grade levels has challenged to develop an approach for learning and understanding mathematics in an easier way for both students and teachers. The paper deals with the results of a study that investigates the process and outcomes of the implementation of…

  9. Identification and Descriptions of the Momentum Effect in Studies of Learning: An Abstract Science Concept.

    ERIC Educational Resources Information Center

    Kwon, Jae-Sool; Mayer, Victor J.

    1985-01-01

    Several studies of the validity of the intensive time-series design have revealed a post-intervention increase in the level of achievement data (the "momentum effect"). Reports on the development and use of a technique to study the effect as it is observed in several data sets on the learning of plate tectonics. (Author/JN)

  10. Analogical Scaffolding and the Learning of Abstract Ideas in Physics: An Example from Electromagnetic Waves

    ERIC Educational Resources Information Center

    Podolefsky, Noah S.; Finkelstein, Noah D.

    2007-01-01

    This paper describes a model of analogy, analogical scaffolding, which explains present and prior results of student learning with analogies. We build on prior models of representation, blending, and layering of ideas. Extending this model's explanatory power, we propose ways in which the model can be applied to design a curriculum directed at…

  11. Individual Versus Paired Learning of an Abstract Algebra Presented by Computer Assisted Instruction.

    ERIC Educational Resources Information Center

    Love, William P.

    A nine-day study was designed to investigate the learning achievement differences between paired and individual high school students in a Computer Assisted Instruction course in Boolean Algebra. Within the format of five 40-minute lessons (including preview frames, instruction, examples, practice problems, criterion frames, and daily quizzes), 23…

  12. Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes.

    PubMed

    Han, Longfei; Luo, Senlin; Yu, Jianmin; Pan, Limin; Chen, Songjing

    2015-03-01

    Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown that 50-80% proportion of T2DM is undiagnosed. In this paper, support vector machines are utilized to screen diabetes, and an ensemble learning module is added, which turns the "black box" of SVM decisions into comprehensible and transparent rules, and it is also useful for solving imbalance problem. Results on China Health and Nutrition Survey data show that the proposed ensemble learning method generates rule sets with weighted average precision 94.2% and weighted average recall 93.9% for all classes. Furthermore, the hybrid system can provide a tool for diagnosis of diabetes, and it supports a second opinion for lay users. PMID:24860043

  13. Implementation of a spike-based perceptron learning rule using TiO2-x memristors.

    PubMed

    Mostafa, Hesham; Khiat, Ali; Serb, Alexander; Mayr, Christian G; Indiveri, Giacomo; Prodromakis, Themis

    2015-01-01

    Synaptic plasticity plays a crucial role in allowing neural networks to learn and adapt to various input environments. Neuromorphic systems need to implement plastic synapses to obtain basic "cognitive" capabilities such as learning. One promising and scalable approach for implementing neuromorphic synapses is to use nano-scale memristors as synaptic elements. In this paper we propose a hybrid CMOS-memristor system comprising CMOS neurons interconnected through TiO2-x memristors, and spike-based learning circuits that modulate the conductance of the memristive synapse elements according to a spike-based Perceptron plasticity rule. We highlight a number of advantages for using this spike-based plasticity rule as compared to other forms of spike timing dependent plasticity (STDP) rules. We provide experimental proof-of-concept results with two silicon neurons connected through a memristive synapse that show how the CMOS plasticity circuits can induce stable changes in memristor conductances, giving rise to increased synaptic strength after a potentiation episode and to decreased strength after a depression episode. PMID:26483629

  14. Learning about time within the spinal cord: evidence that spinal neurons can abstract and store an index of regularity

    PubMed Central

    Lee, Kuan H.; Turtle, Joel D.; Huang, Yung-Jen; Strain, Misty M.; Baumbauer, Kyle M.; Grau, James W.

    2015-01-01

    Prior studies have shown that intermittent noxious stimulation has divergent effects on spinal cord plasticity depending upon whether it occurs in a regular (fixed time, FT) or irregular (variable time, VT) manner: In spinally transected animals, VT stimulation to the tail or hind leg impaired spinal learning whereas an extended exposure to FT stimulation had a restorative/protective effect. These observations imply that lower level systems are sensitive to temporal relations. Using spinally transected rats, it is shown that the restorative effect of FT stimulation emerges after 540 shocks; fewer shocks generate a learning impairment. The transformative effect of FT stimulation is related to the number of shocks administered, not the duration of exposure. Administration of 360 FT shocks induces a learning deficit that lasts 24 h. If a second bout of FT stimulation is given a day after the first, it restores the capacity to learn. This savings effect implies that the initial training episode had a lasting (memory-like) effect. Two bouts of shock have a transformative effect when applied at different locations or at difference frequencies, implying spinal systems abstract and store an index of regularity (rather than a specific interval). Implications of the results for step training and rehabilitation after injury are discussed. PMID:26539090

  15. Category Number Impacts Rule-Based "and" Information-Integration Category Learning: A Reassessment of Evidence for Dissociable Category-Learning Systems

    ERIC Educational Resources Information Center

    Stanton, Roger D.; Nosofsky, Robert M.

    2013-01-01

    Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on…

  16. Mixing Languages during Learning? Testing the One Subject—One Language Rule

    PubMed Central

    2015-01-01

    In bilingual communities, mixing languages is avoided in formal schooling: even if two languages are used on a daily basis for teaching, only one language is used to teach each given academic subject. This tenet known as the one subject-one language rule avoids mixing languages in formal schooling because it may hinder learning. The aim of this study was to test the scientific ground of this assumption by investigating the consequences of acquiring new concepts using a method in which two languages are mixed as compared to a purely monolingual method. Native balanced bilingual speakers of Basque and Spanish—adults (Experiment 1) and children (Experiment 2)—learnt new concepts by associating two different features to novel objects. Half of the participants completed the learning process in a multilingual context (one feature was described in Basque and the other one in Spanish); while the other half completed the learning phase in a purely monolingual context (both features were described in Spanish). Different measures of learning were taken, as well as direct and indirect indicators of concept consolidation. We found no evidence in favor of the non-mixing method when comparing the results of two groups in either experiment, and thus failed to give scientific support for the educational premise of the one subject—one language rule. PMID:26107624

  17. A stimulus-location effect in contingency-governed, but not rule-based, discrimination learning.

    PubMed

    Meier, Christina; Lea, Stephen E G; McLaren, Ian P L

    2016-04-01

    We tested pigeons' acquisition of a conditional discrimination task between colored grating stimuli that included choosing 1 of 2 response keys, which either appeared as white keys to the left and right of the discriminative stimulus, or were replicas of the stimulus. Pigeons failed to acquire the discrimination when the response keys were white disks but succeeded when directly responding to a replica of the stimulus. These results highlight how conditioning processes shape learning in pigeons: The results can be accounted for by supposing that, when pigeons were allowed to respond directly toward the stimulus, learning was guided by classical conditioning, but that responding to white keys demanded instrumental learning, which impaired task acquisition for pigeons. In contrast, humans completing the same paradigm showed no differential learning success depending on whether figure or position indicated the correct key. However, only participants who could state the underlying discrimination rule acquired the task, which implies that human performance in this situation relied on the deduction and application of task rules instead of associative processes. (PsycINFO Database Record PMID:26866376

  18. A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.

    PubMed

    Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

    2015-08-01

    Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored

  19. Learning grammar rules of building parts from precise models and noisy observations

    NASA Astrophysics Data System (ADS)

    Dehbi, Y.; Plümer, L.

    The automatic interpretation of dense three-dimensional (3D) point clouds is still an open research problem. The quality and usability of the derived models depend to a large degree on the availability of highly structured models which represent semantics explicitly and provide a priori knowledge to the interpretation process. The usage of formal grammars for modelling man-made objects has gained increasing interest in the last few years. In order to cope with the variety and complexity of buildings, a large number of fairly sophisticated grammar rules are needed. As yet, such rules mostly have to be designed by human experts. This article describes a novel approach to machine learning of attribute grammar rules based on the Inductive Logic Programming paradigm. Apart from syntactic differences, logic programs and attribute grammars are basically the same language. Attribute grammars extend context-free grammars by attributes and semantic rules and provide a much larger expressive power. Our approach to derive attribute grammars is able to deal with two kinds of input data. On the one hand, we show how attribute grammars can be derived from precise descriptions in the form of examples provided by a human user as the teacher. On the other hand, we present the acquisition of models from noisy observations such as 3D point clouds. This includes the learning of geometric and topological constraints by taking measurement errors into account. The feasibility of our approach is proven exemplarily by stairs, and a generic framework for learning other building parts is discussed. Stairs aggregate an arbitrary number of steps in a manner which is specified by topological and geometric constraints and can be modelled in a recursive way. Due to this recursion, they pose a special challenge to machine learning. In order to learn the concept of stairs, only a small number of examples were required. Our approach represents and addresses the quality of the given observations and

  20. Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules

    PubMed Central

    Frémaux, Nicolas; Gerstner, Wulfram

    2016-01-01

    Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide “when” to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators. PMID:26834568

  1. Teaching Spelling to Students with Learning Disabilities: A Comparison of Rule-Based Strategies versus Traditional Instruction

    ERIC Educational Resources Information Center

    Darch, Craig; Eaves, Ronald C.; Crowe, D. Alan; Simmons, Kate; Conniff, Alexandra

    2006-01-01

    This study compared two instructional methods for teaching spelling to elementary students with learning disabilities (LD). Forty-two elementary students with LD were randomly assigned to one of two instructional groups to teach spelling words: (a) a rule-based strategy group that focused on teaching students spelling rules (based on the "Spelling…

  2. Rules and construction effects in learning the argument structure of verbs.

    PubMed

    Demuth, Katherine; Machobane, Malillo; Moloi, Francina

    2003-11-01

    Theorists of language acquisition have long debated the means by which children learn the argument structure of verbs (e.g. Bowerman, 1974, 1990; Pinker, 1984, 1989; Tomasello, 1992). Central to this controversy has been the possible role of verb semantics, especially in learning which verbs undergo dative-shift alternation in languages like English. The learning problem is somewhat simplified in Bantu double object constructions, where all applicative verbs show the same order of postverbal objects. However, Bantu languages differ as to what that order is, some placing the benefactive argument first, and others placing the animate argument first. Learning the language-specific word-order restrictions on Bantu double object applicative constructions is therefore more akin to setting a parameter (cf. Hyams, 1986). This study examined 100 three- to eight-year-old children's knowledge of word order restrictions in Sesotho double object applicatives. Performance on forced choice elicited production tasks found that four-year-olds showed evidence of rule learning, although eight-year-olds had not yet attained adult levels of performance. Further investigation found lexical construction effects for three-year-olds. These findings suggest that learning the argument structure of verbs, even when lexical semantics is not involved, may be more sensitive to lexical construction effects than previously thought. PMID:14686085

  3. Reading to learn experimental practice: The role of text and firsthand experience in the acquisition of an abstract science principle

    NASA Astrophysics Data System (ADS)

    Richmond, Erica Kesin

    2008-10-01

    From the onset of schooling, texts are used as important educational tools. In the primary years, they are integral to learning how to decode and develop fluency. In the later elementary years, they are often essential to the acquisition of academic content. Unfortunately, many children experience difficulties with this process, which is due in large part to their unfamiliarity with the genre of academic texts. The articles presented in this dissertation share an underlying theme of how to develop children's ability to comprehend and learn from academic, and specifically, non-narrative texts. The first article reviews research on the development of non-narrative discourse to elucidate the linguistic precursors to non-narrative text comprehension. The second and third articles draw from an empirical study that investigated the best way to integrate text, manipulation, and first-hand experience for children's acquisition and application of an abstract scientific principle. The scientific principle introduced in the study was the Control of Variables Strategy (CVS), a fundamental idea underlying scientific reasoning and a strategy for designing unconfounded experiments. Eight grade 4 classes participated in the study (N = 129), in one of three conditions: (a) read procedural text and manipulate experimental materials, (b) listen to procedural text and manipulate experimental materials, or (c) read procedural text with no opportunity to manipulate experimental materials. Findings from the study indicate that children who had the opportunity to read and manipulate materials were most effective at applying the strategy to designing and justifying unconfounded experiments, and evaluating written and physical experimental designs; however, there was no effect of instructional condition on a written assessment of evaluating familiar and unfamiliar experimental designs one week after the intervention. These results suggest that the acquisition and application of an abstract

  4. Striving for Excellence. The International Conference of the Learning Disabilities Association of America (Atlanta, Georgia, March 4-7, 1992). Research Poster Session Abstract. Volume 1.

    ERIC Educational Resources Information Center

    Russell, Steven C., Comp.

    Eleven abstracts of research projects related to individuals with learning disabilities are compiled in this booklet. The research projects were presented in poster sessions at the March 1992 International Conference of the Learning Disabilities Association of America. Titles and authors of poster sessions include: "Perceptual and Verbal Skills of…

  5. Category Number Impacts Rule-Based but Not Information-Integration Category Learning: Further Evidence for Dissociable Category-Learning Systems

    ERIC Educational Resources Information Center

    Maddox, W. Todd; Filoteo, J. Vincent; Hejl, Kelli D.; Ing, A. David

    2004-01-01

    Category number effects on rule-based and information-integration category learning were investigated. Category number affected accuracy and the distribution of best-fitting models in the rule-based task but had no effect on accuracy and little effect on the distribution of best-fining models in the information-integration task. In the 2 category…

  6. Applying cognitive developmental psychology to middle school physics learning: The rule assessment method

    NASA Astrophysics Data System (ADS)

    Hallinen, Nicole R.; Chi, Min; Chin, Doris B.; Prempeh, Joe; Blair, Kristen P.; Schwartz, Daniel L.

    2013-01-01

    Cognitive developmental psychology often describes children's growing qualitative understanding of the physical world. Physics educators may be able to use the relevant methods to advantage for characterizing changes in students' qualitative reasoning. Siegler developed the "rule assessment" method for characterizing levels of qualitative understanding for two factor situations (e.g., volume and mass for density). The method assigns children to rule levels that correspond to the degree they notice and coordinate the two factors. Here, we provide a brief tutorial plus a demonstration of how we have used this method to evaluate instructional outcomes with middle-school students who learned about torque, projectile motion, and collisions using different instructional methods with simulations.

  7. Numerical rule-learning in ring-tailed lemurs (lemur catta).

    PubMed

    Merritt, Dustin J; Maclean, Evan L; Crawford, Jeremy Chase; Brannon, Elizabeth M

    2011-01-01

    We investigated numerical discrimination and numerical rule-learning in ring-tailed lemurs (Lemur catta). Two ring-tailed lemurs were trained to respond to two visual arrays, each of which contained between one and four elements, in numerically ascending order. In Experiment 1, lemurs were trained with 36 exemplars of each of the numerosities 1-4 and then showed positive transfer to trial-unique novel exemplars of the values 1-4. In Experiments 2A and 2B, lemurs were tested on their ability to transfer an ascending numerical rule from the values 1-4 to novel values 5-9. Both lemurs successfully ordered the novel values with above chance accuracy. Accuracy was modulated by the ratio between the two numerical values suggesting that lemurs accessed the approximate number system when performing the task. PMID:21713071

  8. Spike Timing Dependent Plasticity: A Consequence of More Fundamental Learning Rules

    PubMed Central

    Shouval, Harel Z.; Wang, Samuel S.-H.; Wittenberg, Gayle M.

    2010-01-01

    Spike timing dependent plasticity (STDP) is a phenomenon in which the precise timing of spikes affects the sign and magnitude of changes in synaptic strength. STDP is often interpreted as the comprehensive learning rule for a synapse – the “first law” of synaptic plasticity. This interpretation is made explicit in theoretical models in which the total plasticity produced by complex spike patterns results from a superposition of the effects of all spike pairs. Although such models are appealing for their simplicity, they can fail dramatically. For example, the measured single-spike learning rule between hippocampal CA3 and CA1 pyramidal neurons does not predict the existence of long-term potentiation one of the best-known forms of synaptic plasticity. Layers of complexity have been added to the basic STDP model to repair predictive failures, but they have been outstripped by experimental data. We propose an alternate first law: neural activity triggers changes in key biochemical intermediates, which act as a more direct trigger of plasticity mechanisms. One particularly successful model uses intracellular calcium as the intermediate and can account for many observed properties of bidirectional plasticity. In this formulation, STDP is not itself the basis for explaining other forms of plasticity, but is instead a consequence of changes in the biochemical intermediate, calcium. Eventually a mechanism-based framework for learning rules should include other messengers, discrete change at individual synapses, spread of plasticity among neighboring synapses, and priming of hidden processes that change a synapse's susceptibility to future change. Mechanism-based models provide a rich framework for the computational representation of synaptic plasticity. PMID:20725599

  9. Knowledge-Based Abstracting.

    ERIC Educational Resources Information Center

    Black, William J.

    1990-01-01

    Discussion of automatic abstracting of technical papers focuses on a knowledge-based method that uses two sets of rules. Topics discussed include anaphora; text structure and discourse; abstracting techniques, including the keyword method and the indicator phrase method; and tools for text skimming. (27 references) (LRW)

  10. Modulated Hebb-Oja learning rule--a method for principal subspace analysis.

    PubMed

    Jankovic, Marko V; Ogawa, Hidemitsu

    2006-03-01

    This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view--synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method. PMID:16566463

  11. Trading Rules on Stock Markets Using Genetic Network Programming with Reinforcement Learning and Importance Index

    NASA Astrophysics Data System (ADS)

    Mabu, Shingo; Hirasawa, Kotaro; Furuzuki, Takayuki

    Genetic Network Programming (GNP) is an evolutionary computation which represents its solutions using graph structures. Since GNP can create quite compact programs and has an implicit memory function, it has been clarified that GNP works well especially in dynamic environments. In addition, a study on creating trading rules on stock markets using GNP with Importance Index (GNP-IMX) has been done. IMX is a new element which is a criterion for decision making. In this paper, we combined GNP-IMX with Actor-Critic (GNP-IMX&AC) and create trading rules on stock markets. Evolution-based methods evolve their programs after enough period of time because they must calculate fitness values, however reinforcement learning can change programs during the period, therefore the trading rules can be created efficiently. In the simulation, the proposed method is trained using the stock prices of 10 brands in 2002 and 2003. Then the generalization ability is tested using the stock prices in 2004. The simulation results show that the proposed method can obtain larger profits than GNP-IMX without AC and Buy&Hold.

  12. Inter-synaptic learning of combination rules in a cortical network model

    PubMed Central

    Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

    2014-01-01

    Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

  13. A reward-modulated Hebbian learning rule can explain experimentally observed network reorganization in a brain control task

    PubMed Central

    Legenstein, Robert; Chase, Steven M.; Schwartz, Andrew B.; Maass, Wolfgang

    2010-01-01

    It has recently been shown in a brain-computer interface experiment that motor cortical neurons change their tuning properties selectively to compensate for errors induced by displaced decoding parameters. In particular, it was shown that the 3D tuning curves of neurons whose decoding parameters were re-assigned changed more than those of neurons whose decoding parameters had not been re-assigned. In this article, we propose a simple learning rule that can reproduce this effect. Our learning rule uses Hebbian weight updates driven by a global reward signal and neuronal noise. In contrast to most previously proposed learning rules, this approach does not require extrinsic information to separate noise from signal. The learning rule is able to optimize the performance of a model system within biologically realistic periods of time under high noise levels. Furthermore, when the model parameters are matched to data recorded during the brain-computer interface learning experiments described above, the model produces learning effects strikingly similar to those found in the experiments. PMID:20573887

  14. Rules and Resemblance: Their Changing Balance in the Category Learning of Humans (Homo sapiens) and Monkeys (Macaca mulatta)

    PubMed Central

    Couchman, Justin J.; Coutinho, Mariana V. C.; Smith, J. David

    2010-01-01

    In an early dissociation between intentional and incidental category learning, Kemler Nelson (1984) gave participants a categorization task that could be performed by responding either to a single-dimensional rule or to overall family resemblance. Humans learning intentionally deliberately adopted rule-based strategies; humans learning incidentally adopted family-resemblance strategies. The present authors replicated Kemler Nelson’s human experiment and found a similar dissociation. They also extended her paradigm so as to evaluate the balance between rules and family-resemblance in determining the category decisions of rhesus monkeys. Monkeys heavily favored the family-resemblance strategy. Formal models showed that even after many sessions and thousands of trials, they spread attention across all stimulus dimensions rather than focus on a single, criterial dimension that could also produce perfect categorization. PMID:20384398

  15. A novel artificial immune clonal selection classification and rule mining with swarm learning model

    NASA Astrophysics Data System (ADS)

    Al-Sheshtawi, Khaled A.; Abdul-Kader, Hatem M.; Elsisi, Ashraf B.

    2013-06-01

    Metaheuristic optimisation algorithms have become popular choice for solving complex problems. By integrating Artificial Immune clonal selection algorithm (CSA) and particle swarm optimisation (PSO) algorithm, a novel hybrid Clonal Selection Classification and Rule Mining with Swarm Learning Algorithm (CS2) is proposed. The main goal of the approach is to exploit and explore the parallel computation merit of Clonal Selection and the speed and self-organisation merits of Particle Swarm by sharing information between clonal selection population and particle swarm. Hence, we employed the advantages of PSO to improve the mutation mechanism of the artificial immune CSA and to mine classification rules within datasets. Consequently, our proposed algorithm required less training time and memory cells in comparison to other AIS algorithms. In this paper, classification rule mining has been modelled as a miltiobjective optimisation problem with predictive accuracy. The multiobjective approach is intended to allow the PSO algorithm to return an approximation to the accuracy and comprehensibility border, containing solutions that are spread across the border. We compared our proposed algorithm classification accuracy CS2 with five commonly used CSAs, namely: AIRS1, AIRS2, AIRS-Parallel, CLONALG, and CSCA using eight benchmark datasets. We also compared our proposed algorithm classification accuracy CS2 with other five methods, namely: Naïve Bayes, SVM, MLP, CART, and RFB. The results show that the proposed algorithm is comparable to the 10 studied algorithms. As a result, the hybridisation, built of CSA and PSO, can develop respective merit, compensate opponent defect, and make search-optimal effect and speed better.

  16. The Roles of Innate Information, Learning Rules and Plasticity in Migratory Bird Orientation

    NASA Astrophysics Data System (ADS)

    Able, Kenneth P.; Able, Mary A.

    This paper and the following three papers were presented at the RIN97 Conference held in Oxford under the auspices of the Animal Navigation Special Interest Group, April 1997. The full proceedings, under the title Orientation and Navigation - Birds, Humans and Other Animals, can be obtained from the Director (£30 to Members, £50 to non-Members).Studies of the compass mechanisms involved in the migratory orientation of birds have revealed a complex web of interactions, both during the development of orientation behaviour in young birds and in mature individuals exhibiting migratory activity. In young birds, the acquisition of compass orientation capabilities involves the interplay of apparently genetically programmed information with a suite of innate learning rules. The latter canalise the ways in which experience with relevant orientation information from the environment impinges on development. There are many general similarities with the development of singing behaviour in songbirds, although that system is more thoroughly understood, especially at the neuronal level.Here we shall attempt to synthesise what is known about the development of compass mechanisms in a framework of innate information and learning rules. The way in which orientation behaviour develops leaves open the possibility for plasticity that enables birds to compensate for variability in the environmental cues that form the basis of their compasses. For at least some components of the system, behavioural plasticity remains into adulthood, allowing the bird on migration to respond in apparently adaptive ways to spatial and temporal variability in orientation information that it may encounter while enroute. We have studied these questions in the Savannah sparrow (Passerculus sandwichensis), a medium-distance North American emberizine nocturnal migrant. We will focus on that species, relating the results of our work to relevant studies on others.

  17. Abstract Painting

    ERIC Educational Resources Information Center

    Henkes, Robert

    1978-01-01

    Abstract art provokes numerous interpretations, and as many misunderstandings. The adolescent reaction is no exception. The procedure described here can help the student to understand the abstract from at least one direction. (Author/RK)

  18. The Effects of the Concrete-Representational-Abstract Integration Strategy on the Ability of Students with Learning Disabilities to Multiply Linear Expressions within Area Problems

    ERIC Educational Resources Information Center

    Strickland, Tricia K.; Maccini, Paula

    2013-01-01

    We examined the effects of the Concrete-Representational-Abstract Integration strategy on the ability of secondary students with learning disabilities to multiply linear algebraic expressions embedded within contextualized area problems. A multiple-probe design across three participants was used. Results indicated that the integration of the…

  19. Is It Really Abstract?

    ERIC Educational Resources Information Center

    Kernan, Christine

    2011-01-01

    For this author, one of the most enjoyable aspects of teaching elementary art is the willingness of students to embrace the different styles of art introduced to them. In this article, she describes a project that allows upper-elementary students to learn about abstract art and the lives of some of the master abstract artists, implement the idea…

  20. Making Implicit Metalevel Rules of the Discourse on Function Explicit Topics of Reflection in the Classroom to Foster Student Learning

    ERIC Educational Resources Information Center

    Güçler, Beste

    2016-01-01

    Despite the existence of extensive literature on functions, fewer studies used sociocultural views to explore the development of student learning about the concept. This study uses a discursive lens to examine whether an instructional approach that specifically attends to particular metalevel rules in the mathematical discourse on functions…

  1. Brain Regions Involved in the Learning and Application of Reward Rules in a Two-Deck Gambling Task

    ERIC Educational Resources Information Center

    Hartstra, E.; Oldenburg, J. F. E.; Van Leijenhorst, L.; Rombouts, S. A. R. B.; Crone, E. A.

    2010-01-01

    Decision-making involves the ability to choose between competing actions that are associated with uncertain benefits and penalties. The Iowa Gambling Task (IGT), which mimics real-life decision-making, involves learning a reward-punishment rule over multiple trials. Patients with damage to ventromedial prefrontal cortex (VMPFC) show deficits…

  2. Abstraction in mathematics.

    PubMed

    Ferrari, Pier Luigi

    2003-07-29

    Some current interpretations of abstraction in mathematical settings are examined from different perspectives, including history and learning. It is argued that abstraction is a complex concept and that it cannot be reduced to generalization or decontextualization only. In particular, the links between abstraction processes and the emergence of new objects are shown. The role that representations have in abstraction is discussed, taking into account both the historical and the educational perspectives. As languages play a major role in mathematics, some ideas from functional linguistics are applied to explain to what extent mathematical notations are to be considered abstract. Finally, abstraction is examined from the perspective of mathematics education, to show that the teaching ideas resulting from one-dimensional interpretations of abstraction have proved utterly unsuccessful. PMID:12903658

  3. Input-specific learning rules at excitatory synapses onto hippocampal parvalbumin-expressing interneurons

    PubMed Central

    Le Roux, Nicolas; Cabezas, Carolina; Böhm, Urs Lucas; Poncer, Jean Christophe

    2013-01-01

    Hippocampal parvalbumin-expressing interneurons (PV INs) provide fast and reliable GABAergic signalling to principal cells and orchestrate hippocampal ensemble activities. Precise coordination of principal cell activity by PV INs relies in part on the efficacy of excitatory afferents that recruit them in the hippocampal network. Feed-forward (FF) inputs in particular from Schaffer collaterals influence spike timing precision in CA1 principal cells whereas local feedback (FB) inputs may contribute to pacemaker activities. Although PV INs have been shown to undergo activity-dependent long term plasticity, how both inputs are modulated during principal cell firing is unknown. Here we show that FF and FB synapses onto PV INs are endowed with distinct postsynaptic glutamate receptors which set opposing long-term plasticity rules. Inward-rectifying AMPA receptors (AMPARs) expressed at both FF and FB inputs mediate a form of anti-Hebbian long term potentiation (LTP), relying on coincident membrane hyperpolarization and synaptic activation. In contrast, FF inputs are largely devoid of NMDA receptors (NMDARs) which are more abundant at FB afferents and confer on them an additional form of LTP with Hebbian properties. Both forms of LTP are expressed with no apparent change in presynaptic function. The specific endowment of FF and FB inputs with distinct coincidence detectors allow them to be differentially tuned upon high frequency afferent activity. Thus, high frequency (>20 Hz) stimulation specifically potentiates FB, but not FF afferents. We propose that these differential, input-specific learning rules may allow PV INs to adapt to changes in hippocampal activity while preserving their precisely timed, clockwork operation. PMID:23339172

  4. On the use of machine learning to identify topological rules in the packing of beta-strands.

    PubMed

    King, R D; Clark, D A; Shirazi, J; Sternberg, M J

    1994-11-01

    The machine learning program GOLEM was applied to discover topological rules in the packing of beta-sheets in alpha/beta-domain proteins. Rules (constraints) were determined for four features of beta-sheet packing: (i) whether a beta-strand is at an edge; (ii) whether two consecutive beta-strands pack parallel or anti-parallel; (iii) whether two beta-strands pack adjacently; and (iv) the winding direction of two consecutive beta-strands. Rules were found with high predictive accuracy and coverage. The errors were generally associated with complications in domain folds, especially in one doubly would domains. Investigation of the rules revealed interesting patterns, some of which were known previously, others that are novel. Novel features include (i) the relationship between pairs of sequential strands is in general one of decreasing size; (ii) more sequential pairs of strands wind in the direction out than in; and (iii) it takes a larger alteration in hydrophobicity to change a strand from winding in the direction out than in. These patterns in the data may be the result of folding pathways in the domains. The rules found are of predictive value and could be used in the combinatorial prediction of protein structure, or as a general test of model structures, e.g. those produced by threading. We conclude that machine learning has a useful role in the analysis of protein structures. PMID:7700861

  5. Finite state automata resulting from temporal information maximization and a temporal learning rule.

    PubMed

    Wennekers, Thomas; Ay, Nihat

    2005-10-01

    We extend Linkser's Infomax principle for feedforward neural networks to a measure for stochastic interdependence that captures spatial and temporal signal properties in recurrent systems. This measure, stochastic interaction, quantifies the Kullback-Leibler divergence of a Markov chain from a product of split chains for the single unit processes. For unconstrained Markov chains, the maximization of stochastic interaction, also called Temporal Infomax, has been previously shown to result in almost deterministic dynamics. This letter considers Temporal Infomax on constrained Markov chains, where some of the units are clamped to prescribed stochastic processes providing input to the system. Temporal Infomax in that case leads to finite state automata, either completely deterministic or weakly nondeterministic. Transitions between internal states of these systems are almost perfectly predictable given the complete current state and the input, but the activity of each single unit alone is virtually random. The results are demonstrated by means of computer simulations and confirmed analytically. It is furthermore shown numerically that Temporal Infomax leads to a high information flow from the input to internal units and that a simple temporal learning rule can approximately achieve the optimization of temporal interaction. We relate these results to experimental data concerning the correlation dynamics and functional connectivities observed in multiple electrode recordings. PMID:16105225

  6. A Hebbian learning rule mediates asymmetric plasticity in aligning sensory representations.

    PubMed

    Witten, Ilana B; Knudsen, Eric I; Sompolinsky, Haim

    2008-08-01

    In the brain, mutual spatial alignment across different sensory representations can be shaped and maintained through plasticity. Here, we use a Hebbian model to account for the synaptic plasticity that results from a displacement of the space representation for one input channel relative to that of another, when the synapses from both channels are equally plastic. Surprisingly, although the synaptic weights for the two channels obeyed the same Hebbian learning rule, the amount of plasticity exhibited by the respective channels was highly asymmetric and depended on the relative strength and width of the receptive fields (RFs): the channel with the weaker or broader RFs always exhibited most or all of the plasticity. A fundamental difference between our Hebbian model and most previous models is that in our model synaptic weights were normalized separately for each input channel, ensuring that the circuit would respond to both sensory inputs. The model produced three distinct regimes of plasticity dynamics (winner-take-all, mixed-shift, and no-shift), with the transition between the regimes depending on the size of the spatial displacement and the degree of correlation between the sensory channels. In agreement with experimental observations, plasticity was enhanced by the accumulation of incremental adaptive adjustments to a sequence of small displacements. These same principles would apply not only to the maintenance of spatial registry across input channels, but also to the experience-dependent emergence of aligned representations in developing circuits. PMID:18525023

  7. Rules, Technique, and Practical Knowledge: A Wittgensteinian Exploration of Vocational Learning

    ERIC Educational Resources Information Center

    Winch, Christopher

    2006-01-01

    In this essay, Christopher Winch explores the relevance of Ludwig Wittgenstein's account of rule-following to vocational education with particular reference to the often-made claim that any account of an activity in terms of rule-following implies rigidity and inflexibility. He argues that most rule-following is only successful when it involves a…

  8. Learning of Aurally Received Verbal Material. Including Comparisons with Learning and Memory Under Visual Conditions of Reception as a Function of Meaningfulness, Abstractness or Similarity.

    ERIC Educational Resources Information Center

    Schulz, Rudolph W.

    The objectives of this study were to determine: (1) the variables that influence the learning of verbal material received by subjects via the aural modality, (2) how learning under conditions of aural reception compare with learning of the same materials under appropriately equivalent visual conditions, and (3) in what combinations learning is…

  9. "Stars Shine Bright Deep in the Heart of LDA." Poster Session Abstracts of the International Conference of the Learning Disabilities Association of America (Dallas, Texas, March 6-9, 1996).

    ERIC Educational Resources Information Center

    Russell, Steven C., Comp.

    This monograph brings together 16 one- to two-page abstracts from research poster sessions held at the March 1996 international conference of the Learning Disabilities Association of America. The first section, addressing research on assessment and characteristics of students with learning disabilities, includes abstracts on the Woodcock-Johnson…

  10. Habituation: a non-associative learning rule design for spiking neurons and an autonomous mobile robots implementation.

    PubMed

    Cyr, André; Boukadoum, Mounir

    2013-03-01

    This paper presents a novel bio-inspired habituation function for robots under control by an artificial spiking neural network. This non-associative learning rule is modelled at the synaptic level and validated through robotic behaviours in reaction to different stimuli patterns in a dynamical virtual 3D world. Habituation is minimally represented to show an attenuated response after exposure to and perception of persistent external stimuli. Based on current neurosciences research, the originality of this rule includes modulated response to variable frequencies of the captured stimuli. Filtering out repetitive data from the natural habituation mechanism has been demonstrated to be a key factor in the attention phenomenon, and inserting such a rule operating at multiple temporal dimensions of stimuli increases a robot's adaptive behaviours by ignoring broader contextual irrelevant information. PMID:23385344

  11. A new modulated Hebbian learning rule--biologically plausible method for local computation of a principal subspace.

    PubMed

    Jankovic, Marko; Ogawa, Hidemitsu

    2003-08-01

    This paper presents one possible implementation of a transformation that performs linear mapping to a lower-dimensional subspace. Principal component subspace will be the one that will be analyzed. Idea implemented in this paper represents generalization of the recently proposed infinity OH neural method for principal component extraction. The calculations in the newly proposed method are performed locally--a feature which is usually considered as desirable from the biological point of view. Comparing to some other wellknown methods, proposed synaptic efficacy learning rule requires less information about the value of the other efficacies to make single efficacy modification. Synaptic efficacies are modified by implementation of Modulated Hebb-type (MH) learning rule. Slightly modified MH algorithm named Modulated Hebb Oja (MHO) algorithm, will be also introduced. Structural similarity of the proposed network with part of the retinal circuit will be presented, too. PMID:12964209

  12. Abstraction and Problem Reformulation

    NASA Technical Reports Server (NTRS)

    Giunchiglia, Fausto

    1992-01-01

    In work done jointly with Toby Walsh, the author has provided a sound theoretical foundation to the process of reasoning with abstraction (GW90c, GWS9, GW9Ob, GW90a). The notion of abstraction formalized in this work can be informally described as: (property 1), the process of mapping a representation of a problem, called (following historical convention (Sac74)) the 'ground' representation, onto a new representation, called the 'abstract' representation, which, (property 2) helps deal with the problem in the original search space by preserving certain desirable properties and (property 3) is simpler to handle as it is constructed from the ground representation by "throwing away details". One desirable property preserved by an abstraction is provability; often there is a relationship between provability in the ground representation and provability in the abstract representation. Another can be deduction or, possibly inconsistency. By 'throwing away details' we usually mean that the problem is described in a language with a smaller search space (for instance a propositional language or a language without variables) in which formulae of the abstract representation are obtained from the formulae of the ground representation by the use of some terminating rewriting technique. Often we require that the use of abstraction results in more efficient .reasoning. However, it might simply increase the number of facts asserted (eg. by allowing, in practice, the exploration of deeper search spaces or by implementing some form of learning). Among all abstractions, three very important classes have been identified. They relate the set of facts provable in the ground space to those provable in the abstract space. We call: TI abstractions all those abstractions where the abstractions of all the provable facts of the ground space are provable in the abstract space; TD abstractions all those abstractions wllere the 'unabstractions' of all the provable facts of the abstract space are

  13. Physiological expression of olfactory discrimination rule learning balances whole-population modulation and circuit stability in the piriform cortex network.

    PubMed

    Jammal, Luna; Whalley, Ben; Ghosh, Sourav; Lamrecht, Raphael; Barkai, Edi

    2016-07-01

    Once trained, rats are able to execute particularly difficult olfactory discrimination tasks with exceptional accuracy. Such skill acquisition, termed "rule learning", is accompanied by a series of long-lasting modifications to three cellular properties which modulate pyramidal neuron activity in piriform cortex; intrinsic excitability, synaptic excitation, and synaptic inhibition. Here, we explore how these changes, which are seemingly contradictory at the single-cell level in terms of their effect on neuronal excitation, are manifested within the piriform cortical neuronal network to store the memory of the rule, while maintaining network stability. To this end, we monitored network activity via multisite extracellular recordings of field postsynaptic potentials (fPSPS) and with single-cell recordings of miniature inhibitory and excitatory synaptic events in piriform cortex slices. We show that although 5 days after rule learning the cortical network maintains its basic activity patterns, synaptic connectivity is strengthened specifically between spatially proximal cells. Moreover, while the enhancement of inhibitory and excitatory synaptic connectivity is nearly identical, strengthening of synaptic inhibition is equally distributed between neurons while synaptic excitation is particularly strengthened within a specific subgroup of cells. We suggest that memory for the acquired rule is stored mainly by strengthening excitatory synaptic connection between close pyramidal neurons and runaway synaptic activity arising from this change is prevented by a nonspecific enhancement of synaptic inhibition. PMID:27449811

  14. Implementation of a spike-based perceptron learning rule using TiO2−x memristors

    PubMed Central

    Mostafa, Hesham; Khiat, Ali; Serb, Alexander; Mayr, Christian G.; Indiveri, Giacomo; Prodromakis, Themis

    2015-01-01

    Synaptic plasticity plays a crucial role in allowing neural networks to learn and adapt to various input environments. Neuromorphic systems need to implement plastic synapses to obtain basic “cognitive” capabilities such as learning. One promising and scalable approach for implementing neuromorphic synapses is to use nano-scale memristors as synaptic elements. In this paper we propose a hybrid CMOS-memristor system comprising CMOS neurons interconnected through TiO2−x memristors, and spike-based learning circuits that modulate the conductance of the memristive synapse elements according to a spike-based Perceptron plasticity rule. We highlight a number of advantages for using this spike-based plasticity rule as compared to other forms of spike timing dependent plasticity (STDP) rules. We provide experimental proof-of-concept results with two silicon neurons connected through a memristive synapse that show how the CMOS plasticity circuits can induce stable changes in memristor conductances, giving rise to increased synaptic strength after a potentiation episode and to decreased strength after a depression episode. PMID:26483629

  15. Automated Assume-Guarantee Reasoning by Abstraction Refinement

    NASA Technical Reports Server (NTRS)

    Pasareanu, Corina S.; Giannakopoulous, Dimitra; Glannakopoulou, Dimitra

    2008-01-01

    Current automated approaches for compositional model checking in the assume-guarantee style are based on learning of assumptions as deterministic automata. We propose an alternative approach based on abstraction refinement. Our new method computes the assumptions for the assume-guarantee rules as conservative and not necessarily deterministic abstractions of some of the components, and refines those abstractions using counter-examples obtained from model checking them together with the other components. Our approach also exploits the alphabets of the interfaces between components and performs iterative refinement of those alphabets as well as of the abstractions. We show experimentally that our preliminary implementation of the proposed alternative achieves similar or better performance than a previous learning-based implementation.

  16. Retention of Minorities in Higher Education: An Abstracted Bibliographic Review (1978-82). EXCEL (EXChange for Enrichment of Learning) Report.

    ERIC Educational Resources Information Center

    Sullivan, LeRoy L.

    Abstracts of 76 documents on retention of minorities in higher education are presented in a bibliography created to provide faculty and administrators access to unpublished works and journal articles on minority retention. The materials, which were produced between 1978-1982, include unpublished reports, conference papers, and dissertations.…

  17. Learning with Technology: Video Modeling with Concrete-Representational-Abstract Sequencing for Students with Autism Spectrum Disorder

    ERIC Educational Resources Information Center

    Yakubova, Gulnoza; Hughes, Elizabeth M.; Shinaberry, Megan

    2016-01-01

    The purpose of this study was to determine the effectiveness of a video modeling intervention with concrete-representational-abstract instructional sequence in teaching mathematics concepts to students with autism spectrum disorder (ASD). A multiple baseline across skills design of single-case experimental methodology was used to determine the…

  18. Abstract coherent categories.

    PubMed

    Rehder, B; Ross, B H

    2001-09-01

    Many studies have demonstrated the importance of the knowledge that interrelates features in people's mental representation of categories and that makes our conception of categories coherent. This article focuses on abstract coherent categories, coherent categories that are also abstract because they are defined by relations independently of any features. Four experiments demonstrate that abstract coherent categories are learned more easily than control categories with identical features and statistical structure, and also that participants induced an abstract representation of the category by granting category membership to exemplars with completely novel features. The authors argue that the human conceptual system is heavily populated with abstract coherent concepts, including conceptions of social groups, societal institutions, legal, political, and military scenarios, and many superordinate categories, such as classes of natural kinds. PMID:11550753

  19. A Rule-Based System for Hybrid Search and Delivery of Learning Objects to Learners

    ERIC Educational Resources Information Center

    Biletskiy, Yevgen; Baghi, Hamidreza; Steele, Jarrett; Vovk, Ruslan

    2012-01-01

    Purpose: Presently, searching the internet for learning material relevant to ones own interest continues to be a time-consuming task. Systems that can suggest learning material (learning objects) to a learner would reduce time spent searching for material, and enable the learner to spend more time for actual learning. The purpose of this paper is…

  20. Abstract Constructions.

    ERIC Educational Resources Information Center

    Pietropola, Anne

    1998-01-01

    Describes a lesson designed to culminate a year of eighth-grade art classes in which students explore elements of design and space by creating 3-D abstract constructions. Outlines the process of using foam board and markers to create various shapes and optical effects. (DSK)

  1. Innovation Abstracts, Volume XV, 1993.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1993-01-01

    This volume of 30 one- to two-page abstracts from 1993 highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) role-playing to encourage critical thinking; (2) team learning techniques to cultivate business skills; (3) librarian-instructor partnerships to create…

  2. Effects of abstract versus concrete visual representations in an instructional simulation on students' declarative knowledge, learning transfer, and perceptions of the simulation

    NASA Astrophysics Data System (ADS)

    Mejia, William Ernesto

    2011-12-01

    Thanks to different multimedia authoring tools and specialized software that facilitate the design and development of computer-based simulations, science teachers and instructional media designers have a variety of simulations to support instructional delivery. However, there is a lack of research on how instructional designers and science teachers can select, design, and implement science simulations most effectively based on the simulations' visual attributes. One of the design principles that play an important part in the simulation design process is the visual representation of on-screen objects used to describe science concepts or principles. The purpose of this study was to investigate the effects of abstract and concrete visual representation of electricity concepts and principles in an instructional simulation on students' declarative knowledge, learning transfer, and perceptions of the simulation. The participants in this study were 39 elementary education pre-service teachers who were randomly assigned to either the concrete or the abstract treatment. The educational intervention was conducted over three 100-minute sessions. Since the sample violated the normality assumption, Mann-Whitney tests were conducted to verify whether the independent variable had significant effects on the three dependent variables. The data analysis found no statistically significant difference on learners' declarative knowledge, learning transfer, and perceptions about the simulation's attributes between those assigned to the concrete treatment and those assigned to the abstract treatment (p>.05). This finding did not favor one type of visual representation over the other.

  3. Abstract Interpreters for Free

    NASA Astrophysics Data System (ADS)

    Might, Matthew

    In small-step abstract interpretations, the concrete and abstract semantics bear an uncanny resemblance. In this work, we present an analysis-design methodology that both explains and exploits that resemblance. Specifically, we present a two-step method to convert a small-step concrete semantics into a family of sound, computable abstract interpretations. The first step re-factors the concrete state-space to eliminate recursive structure; this refactoring of the state-space simultaneously determines a store-passing-style transformation on the underlying concrete semantics. The second step uses inference rules to generate an abstract state-space and a Galois connection simultaneously. The Galois connection allows the calculation of the "optimal" abstract interpretation. The two-step process is unambiguous, but nondeterministic: at each step, analysis designers face choices. Some of these choices ultimately influence properties such as flow-, field- and context-sensitivity. Thus, under the method, we can give the emergence of these properties a graph-theoretic characterization. To illustrate the method, we systematically abstract the continuation-passing style lambda calculus to arrive at two distinct families of analyses. The first is the well-known k-CFA family of analyses. The second consists of novel "environment-centric" abstract interpretations, none of which appear in the literature on static analysis of higher-order programs.

  4. Multimedia Football Viewing: Embedded Rules, Practice, and Video Context in IVD Procedural Learning.

    ERIC Educational Resources Information Center

    Kim, Eunsoon; Young, Michael F.

    This study investigated the effects of interactive video (IVD) instruction with embedded rules (production system rules) and practice with feedback on learners' academic achievement and perceived self efficacy in the domain of procedural knowledge for watching professional football. Subjects were 71 female volunteers from undergraduate education…

  5. Should there be a three-strikes rule against pure discovery learning? The case for guided methods of instruction.

    PubMed

    Mayer, Richard E

    2004-01-01

    The author's thesis is that there is sufficient research evidence to make any reasonable person skeptical about the benefits of discovery learning--practiced under the guise of cognitive constructivism or social constructivism--as a preferred instructional method. The author reviews research on discovery of problem-solving rules culminating in the 1960s, discovery of conservation strategies culminating in the 1970s, and discovery of LOGO programming strategies culminating in the 1980s. In each case, guided discovery was more effective than pure discovery in helping students learn and transfer. Overall, the constructivist view of learning may be best supported by methods of instruction that involve cognitive activity rather than behavioral activity, instructional guidance rather than pure discovery, and curricular focus rather than unstructured exploration. PMID:14736316

  6. Aqui y Alla (Here and There) Information-Based Learning Corridors between Tennessee and Puerto Rico: The Five Golden Rules in Intercultural Education

    ERIC Educational Resources Information Center

    Mehra, Bharat; Allard, Suzie; Qayyum, M. Asim; Barclay-McLaughlin, Gina

    2008-01-01

    This article proposes five information-based Golden Rules in intercultural education that represent a holistic approach to creating learning corridors across geographically dispersed academic communities. The Golden Rules are generated through qualitative analysis, grounded theory application, reflective practice, and critical research to…

  7. Modeling fast stimulus-response association learning along the occipito-parieto-frontal pathway following rule instructions.

    PubMed

    Bugmann, Guido

    2012-01-24

    On the basis of instructions, humans are able to set up associations between sensory and motor areas of the brain separated by several neuronal relays, within a few seconds. This paper proposes a model of fast learning along the dorsal pathway, from primary visual areas to pre-motor cortex. A new synaptic learning rule is proposed where synaptic efficacies converge rapidly toward a specific value determined by the number of active inputs of a neuron, respecting a principle of resource limitation in terms of total synaptic input efficacy available to a neuron. The efficacies are stable with regards to repeated arrival of spikes in a spike train. This rule reproduces the inverse relationship between initial and final synaptic efficacy observed in long-term potentiation (LTP) experiments. Simulations of learning experiments are conducted in a multilayer network of leaky integrate-and-fire (LIF) spiking neuron models. It is proposed that cortical feedback connections convey a top-down learning-enabling signal that guides bottom-up learning in "hidden" neurons that are not directly exposed to input or output activity. Simulations of repeated presentation of the same stimulus-response pair, show that, under conditions of fast learning with probabilistic synaptic transmission, the networks tend to recruit a new sub-network at each presentation to represent the association, rather than re-using a previously trained one. This increasing allocation of neural resources results in progressively shorter execution times, in line with experimentally observed reduction in response time with practice. This article is part of a Special Issue entitled: Neural Coding. PMID:22041227

  8. 2002 NASPSA Conference Abstracts.

    ERIC Educational Resources Information Center

    Journal of Sport & Exercise Psychology, 2002

    2002-01-01

    Contains abstracts from the 2002 conference of the North American Society for the Psychology of Sport and Physical Activity. The publication is divided into three sections: the preconference workshop, "Effective Teaching Methods in the Classroom;" symposia (motor development, motor learning and control, and sport psychology); and free…

  9. Rules and mechanisms of punishment learning in honey bees: the aversive conditioning of the sting extension response.

    PubMed

    Tedjakumala, Stevanus Rio; Giurfa, Martin

    2013-08-15

    Honeybees constitute established model organisms for the study of appetitive learning and memory. In recent years, the establishment of the technique of olfactory conditioning of the sting extension response (SER) has yielded new insights into the rules and mechanisms of aversive learning in insects. In olfactory SER conditioning, a harnessed bee learns to associate an olfactory stimulus as the conditioned stimulus with the noxious stimulation of an electric shock as the unconditioned stimulus. Here, we review the multiple aspects of honeybee aversive learning that have been uncovered using Pavlovian conditioning of the SER. From its behavioral principles and sensory variants to its cellular bases and implications for understanding social organization, we present the latest advancements in the study of punishment learning in bees and discuss its perspectives in order to define future research avenues and necessary improvements. The studies presented here underline the importance of studying honeybee learning not only from an appetitive but also from an aversive perspective, in order to uncover behavioral and cellular mechanisms of individual and social plasticity. PMID:23885086

  10. Event-related potentials reveal the relations between feature representations at different levels of abstraction.

    PubMed

    Hannah, Samuel D; Shedden, Judith M; Brooks, Lee R; Grundy, John G

    2016-11-01

    In this paper, we use behavioural methods and event-related potentials (ERPs) to explore the relations between informational and instantiated features, as well as the relation between feature abstraction and rule type. Participants are trained to categorize two species of fictitious animals and then identify perceptually novel exemplars. Critically, two groups are given a perfectly predictive counting rule that, according to Hannah and Brooks (2009. Featuring familiarity: How a familiar feature instantiation influences categorization. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale, 63, 263-275. Retrieved from http://doi.org/10.1037/a0017919), should orient them to using abstract informational features when categorizing the novel transfer items. A third group is taught a feature list rule, which should orient them to using detailed instantiated features. One counting-rule group were taught their rule before any exposure to the actual stimuli, and the other immediately after training, having learned the instantiations first. The feature-list group were also taught their rule after training. The ERP results suggest that at test, the two counting-rule groups processed items differently, despite their identical rule. This not only supports the distinction that informational and instantiated features are qualitatively different feature representations, but also implies that rules can readily operate over concrete inputs, in contradiction to traditional approaches that assume that rules necessarily act on abstract inputs. PMID:26513169

  11. Learning with Technology: Video Modeling with Concrete-Representational-Abstract Sequencing for Students with Autism Spectrum Disorder.

    PubMed

    Yakubova, Gulnoza; Hughes, Elizabeth M; Shinaberry, Megan

    2016-07-01

    The purpose of this study was to determine the effectiveness of a video modeling intervention with concrete-representational-abstract instructional sequence in teaching mathematics concepts to students with autism spectrum disorder (ASD). A multiple baseline across skills design of single-case experimental methodology was used to determine the effectiveness of the intervention on the acquisition and maintenance of addition, subtraction, and number comparison skills for four elementary school students with ASD. Findings supported the effectiveness of the intervention in improving skill acquisition and maintenance at a 3-week follow-up. Implications for practice and future research are discussed. PMID:26983919

  12. General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

    SciTech Connect

    Bornholdt, S.; Graudenz, D.

    1993-07-01

    A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

  13. Young Children's Selective Learning of Rule Games from Reliable and Unreliable Models

    ERIC Educational Resources Information Center

    Rakoczy, Hannes; Warneken, Felix; Tomasello, Michael

    2009-01-01

    We investigated preschoolers' selective learning from models that had previously appeared to be reliable or unreliable. Replicating previous research, children from 4 years selectively learned novel words from reliable over unreliable speakers. Extending previous research, children also selectively learned other kinds of acts--novel games--from…

  14. A Journey on Refining Rules for Online Discussion: Implications for the Design of Learning Management Systems

    ERIC Educational Resources Information Center

    Chen, Der-Thanq; Wang, Yu-Mei; Hung, David

    2009-01-01

    Research on asynchronous online discussions has primarily focused on their efficacy in relation to learning outcomes. Rarely are there investigations on how the design of online learning activities or how discussions could be incorporated into student learning experience. We contend that successful online activities need careful and meticulous…

  15. Online Learning Behaviors for Radiology Interns Based on Association Rules and Clustering Technique

    ERIC Educational Resources Information Center

    Chen, Hsing-Shun; Liou, Chuen-He

    2014-01-01

    In a hospital, clinical teachers must also care for patients, so there is less time for the teaching of clinical courses, or for discussing clinical cases with interns. However, electronic learning (e-learning) can complement clinical skills education for interns in a blended-learning process. Students discuss and interact with classmates in an…

  16. INVENTORY ABSTRACTION

    SciTech Connect

    G. Ragan

    2001-12-19

    The purpose of the inventory abstraction, which has been prepared in accordance with a technical work plan (CRWMS M&O 2000e for ICN 02 of the present analysis, and BSC 2001e for ICN 03 of the present analysis), is to: (1) Interpret the results of a series of relative dose calculations (CRWMS M&O 2000c, 2000f). (2) Recommend, including a basis thereof, a set of radionuclides that should be modeled in the Total System Performance Assessment in Support of the Site Recommendation (TSPA-SR) and the Total System Performance Assessment in Support of the Final Environmental Impact Statement (TSPA-FEIS). (3) Provide initial radionuclide inventories for the TSPA-SR and TSPA-FEIS models. (4) Answer the U.S. Nuclear Regulatory Commission (NRC)'s Issue Resolution Status Report ''Key Technical Issue: Container Life and Source Term'' (CLST IRSR) key technical issue (KTI): ''The rate at which radionuclides in SNF [spent nuclear fuel] are released from the EBS [engineered barrier system] through the oxidation and dissolution of spent fuel'' (NRC 1999, Subissue 3). The scope of the radionuclide screening analysis encompasses the period from 100 years to 10,000 years after the potential repository at Yucca Mountain is sealed for scenarios involving the breach of a waste package and subsequent degradation of the waste form as required for the TSPA-SR calculations. By extending the time period considered to one million years after repository closure, recommendations are made for the TSPA-FEIS. The waste forms included in the inventory abstraction are Commercial Spent Nuclear Fuel (CSNF), DOE Spent Nuclear Fuel (DSNF), High-Level Waste (HLW), naval Spent Nuclear Fuel (SNF), and U.S. Department of Energy (DOE) plutonium waste. The intended use of this analysis is in TSPA-SR and TSPA-FEIS. Based on the recommendations made here, models for release, transport, and possibly exposure will be developed for the isotopes that would be the highest contributors to the dose given a release to the

  17. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment

    EPA Science Inventory

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  18. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment (Presentation)

    EPA Science Inventory

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  19. Automatic Learning of Fine Operating Rules for Online Power System Security Control.

    PubMed

    Sun, Hongbin; Zhao, Feng; Wang, Hao; Wang, Kang; Jiang, Weiyong; Guo, Qinglai; Zhang, Boming; Wehenkel, Louis

    2016-08-01

    Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min. PMID:25680217

  20. Statistical Learning of Origin-Specific Statically Optimal Individualized Treatment Rules

    PubMed Central

    van der Laan, Mark J.; Petersen, Maya L.

    2008-01-01

    Consider a longitudinal observational or controlled study in which one collects chronological data over time on a random sample of subjects. The time-dependent process one observes on each subject contains time-dependent covariates, time-dependent treatment actions, and an outcome process or single final outcome of interest. A statically optimal individualized treatment rule (as introduced in van der Laan et. al. (2005), Petersen et. al. (2007)) is a treatment rule which at any point in time conditions on a user-supplied subset of the past, computes the future static treatment regimen that maximizes a (conditional) mean future outcome of interest, and applies the first treatment action of the latter regimen. In particular, Petersen et. al. (2007) clarified that, in order to be statically optimal, an individualized treatment rule should not depend on the observed treatment mechanism. Petersen et. al. (2007) further developed estimators of statically optimal individualized treatment rules based on a past capturing all confounding of past treatment history on outcome. In practice, however, one typically wishes to find individualized treatment rules responding to a user-supplied subset of the complete observed history, which may not be sufficient to capture all confounding. The current article provides an important advance on Petersen et. al. (2007) by developing locally efficient double robust estimators of statically optimal individualized treatment rules responding to such a user-supplied subset of the past. However, failure to capture all confounding comes at a price; the static optimality of the resulting rules becomes origin-specific. We explain origin-specific static optimality, and discuss the practical importance of the proposed methodology. We further present the results of a data analysis in which we estimate a statically optimal rule for switching antiretroviral therapy among patients infected with resistant HIV virus. PMID:19122792

  1. A Rule-Based and Hypertextual Electronic Mail System for Electronic Learning Environments: Applying the Distributed Network Learning Framework.

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Levin, James A.

    This paper discusses issues related to the design of software tools that support learners in their participation in network-based learning activities. To guide the development and use of a new class of educationally-oriented network tools, this paper proposes a cognitively-based, distributed network learning framework (DNLF). This framework has…

  2. Flexibility for Fairness: Crafting Business Rules for Student Learning Objectives. Ask the Team

    ERIC Educational Resources Information Center

    Potemski, Amy

    2013-01-01

    Across the United States, a wide cross-section of administrators and teachers are learning the ins and outs of setting, assessing, and scoring student learning objectives (SLOs). An SLO is a set of goals that measures an educator's progress in achieving student growth targets. SLOs are particularly helpful for teachers in nontested subjects and…

  3. Rules and Construction Effects in Learning the Argument Structure of Verbs

    ERIC Educational Resources Information Center

    Demuth, Katherine; Machobane, 'Malillo; Moloi, Francina

    2003-01-01

    Theorists of language acquisition have long debated the means by which children learn the argument structure of verbs (e.g. Bowerman, 1974, 1990; Pinker, 1984, 1989; Tomasello, 1992). Central to this controversy has been the possible role of verb semantics, especially in learning which verbs undergo dative-shift alternation in languages like…

  4. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment

    PubMed Central

    Li, Yang; Li, Guoqing; Wang, Zhenhao

    2015-01-01

    In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system — the southern power system of Hebei province. PMID:26091524

  5. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

    PubMed

    Li, Yang; Li, Guoqing; Wang, Zhenhao

    2015-01-01

    In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province. PMID:26091524

  6. It Won't Be Easy, but You Must Learn the Arcane New Rules of Arbitrage.

    ERIC Educational Resources Information Center

    Anderson, David; Brennan, William

    1988-01-01

    With passage of the Tax Reform Act of 1986, school systems became liable to the federal government for any profits earned on tax-exempt bonds. Understanding the requirements is essential for any board facing significant capital financing. Outlines requirements, exceptions to the rule, penalties, costs, and debt planning. (MLF)

  7. The Influence of Adjunct Rules and Objectives on Learning from Text Material.

    ERIC Educational Resources Information Center

    Smith, Patrick E.; Kulhavy, Raymond W.

    The purpose of this study was to assess the effects of adjunct objectives (AO) or adjunct rules (AR) on instructional materials. The subjects were 110 undergraduate volunteers attending Arizona State University. As each subject entered the lecture hall for the class, he was given an envelope containing the experimental materials appropriate to a…

  8. Social Interaction Rules in Cooperative Learning Groups for Students at Risk for ADHD

    ERIC Educational Resources Information Center

    Kuester, Deitra A.; Zentall, Sydney S.

    2012-01-01

    This study assessed the effects of providing social participation rules on the performance and social behavior of a school-based sample of 10-14-year-old students at risk for attention deficit hyperactivity disorder (n = 34) who worked cooperatively in same-gender triads with typical peers (n = 92). The design was primarily a 2 (population group)…

  9. Spelling Dutch Doublets: Children's Learning of a Phonological and Morphological Spelling Rule

    ERIC Educational Resources Information Center

    Notenboom, Annelise; Reitsma, Pieter

    2007-01-01

    This study addresses the question of why spellings determined by morphology are relatively hard to acquire by presenting a latent class model of children's acquisition of a doublet of consonants in the spelling of Dutch verbs. This spelling pattern can be determined either by a phonological rule (after a short vowel, a doublet is spelled) or a…

  10. Effects of Explicit Rules in Learning to Spell Open- and Closed-Syllable Words

    ERIC Educational Resources Information Center

    Hilte, Maartje; Reitsma, Pieter

    2011-01-01

    Second graders (N=222; 7.7 years of age) practiced with open- and closed-syllable words in a computer-assisted training program and appropriate spelling rules were either explicitly provided during practice or not. Also, children practiced either with a small set of exemplars or with a large set; the latter condition was expected to promote the…

  11. Rule Learning over Consonants and Vowels in a Non-Human Animal

    ERIC Educational Resources Information Center

    de la Mora, Daniela M.; Toro, Juan M.

    2013-01-01

    Perception studies have shown similarities between humans and other animals in a wide array of language-related processes. However, the components of language that make it uniquely human have not been fully identified. Here we show that nonhuman animals extract rules over speech sequences that are difficult for humans. Specifically, animals easily…

  12. Abstraction and Assume-Guarantee Reasoning for Automated Software Verification

    NASA Technical Reports Server (NTRS)

    Chaki, S.; Clarke, E.; Giannakopoulou, D.; Pasareanu, C. S.

    2004-01-01

    Compositional verification and abstraction are the key techniques to address the state explosion problem associated with model checking of concurrent software. A promising compositional approach is to prove properties of a system by checking properties of its components in an assume-guarantee style. This article proposes a framework for performing abstraction and assume-guarantee reasoning of concurrent C code in an incremental and fully automated fashion. The framework uses predicate abstraction to extract and refine finite state models of software and it uses an automata learning algorithm to incrementally construct assumptions for the compositional verification of the abstract models. The framework can be instantiated with different assume-guarantee rules. We have implemented our approach in the COMFORT reasoning framework and we show how COMFORT out-performs several previous software model checking approaches when checking safety properties of non-trivial concurrent programs.

  13. ALT-C 95: Changing Education, Changing Technology. Conference Abstracts of the Association for Learning Technology Conference (2nd, Milton Keynes, England, United Kingdom, September 11-13, 1995).

    ERIC Educational Resources Information Center

    Hawkridge, David, Ed.

    This program for the 1995 Association for Learning Technology Conference summarizes the presentations of the discussions, demonstrations, workshops, and poster sessions. Abstracts of the following papers presented at the conference are included: "New Structures for Learning" (Patrick Allen & Kate Sankey); "Multiple System Conferencing" (Susan…

  14. Targeted Learning of the Mean Outcome under an Optimal Dynamic Treatment Rule

    PubMed Central

    van der Laan, Mark J.; Luedtke, Alexander R.

    2015-01-01

    We consider estimation of and inference for the mean outcome under the optimal dynamic two time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, where the candidate rules are restricted to depend only on a user-supplied subset of the baseline and intermediate covariates. This estimation problem is addressed in a statistical model for the data distribution that is nonparametric beyond possible knowledge about the treatment and censoring mechanism. This contrasts from the current literature that relies on parametric assumptions. We establish that the mean of the counterfactual outcome under the optimal dynamic treatment is a pathwise differentiable parameter under conditions, and develop a targeted minimum loss-based estimator (TMLE) of this target parameter. We establish asymptotic linearity and statistical inference for this estimator under specified conditions. In a sequentially randomized trial the statistical inference relies upon a second-order difference between the estimator of the optimal dynamic treatment and the optimal dynamic treatment to be asymptotically negligible, which may be a problematic condition when the rule is based on multivariate time-dependent covariates. To avoid this condition, we also develop TMLEs and statistical inference for data adaptive target parameters that are defined in terms of the mean outcome under the estimate of the optimal dynamic treatment. In particular, we develop a novel cross-validated TMLE approach that provides asymptotic inference under minimal conditions, avoiding the need for any empirical process conditions. We offer simulation results to support our theoretical findings. PMID:26236571

  15. The Effects of Variation on Learning Word Order Rules by Adults with and without Language-Based Learning Disabilities

    ERIC Educational Resources Information Center

    Grunow, Hope; Spaulding, Tammie J.; Gomez, Rebecca L.; Plante, Elena

    2006-01-01

    Non-adjacent dependencies characterize numerous features of English syntax, including certain verb tense structures and subject-verb agreement. This study utilized an artificial language paradigm to examine the contribution of item variability to the learning of these types of dependencies. Adult subjects with and without language-based learning…

  16. Epistemological Change through Peer Apprenticeship Learning: From Rule-Based to Idea-Based Social Constructivism.

    ERIC Educational Resources Information Center

    Loong, David Hung Wei

    1998-01-01

    Describes the peer-apprenticeship learning situation between two students in distributed computer-mediated co-construction of mathematical meanings. As a result of assimilating the disposition towards playing with ideas, students were able to engage in meaningful idea-based social constructivism. Contains 60 references. (Author/ASK)

  17. Rules, Roles and Tools: Activity Theory and the Comparative Study of E-Learning

    ERIC Educational Resources Information Center

    Benson, Angela; Lawler, Cormac; Whitworth, Andrew

    2008-01-01

    Activity theory (AT) is a powerful tool for investigating "artefacts in use", ie, the ways technologies interrelate with their local context. AT reveals the interfaces between e-learning at the macro- (strategy, policy, "campus-wide" solutions) and the micro-organisational levels (everyday working practice, iterative change, individual…

  18. Stable Rules: Science and Social Transmission. Studies in the Learning Sciences.

    ERIC Educational Resources Information Center

    Nathan, Henry

    In laying the groundwork for a co-operative scientific inquiry in the field of learning sciences the following five areas of access to the study are considered in this introductory inquiry statement: 1) genetic sociology (symbolic systems and early socialization); 2) experimental ethnography (the effect of literacy on the structure of skill and…

  19. Two fast and accurate heuristic RBF learning rules for data classification.

    PubMed

    Rouhani, Modjtaba; Javan, Dawood S

    2016-03-01

    This paper presents new Radial Basis Function (RBF) learning methods for classification problems. The proposed methods use some heuristics to determine the spreads, the centers and the number of hidden neurons of network in such a way that the higher efficiency is achieved by fewer numbers of neurons, while the learning algorithm remains fast and simple. To retain network size limited, neurons are added to network recursively until termination condition is met. Each neuron covers some of train data. The termination condition is to cover all training data or to reach the maximum number of neurons. In each step, the center and spread of the new neuron are selected based on maximization of its coverage. Maximization of coverage of the neurons leads to a network with fewer neurons and indeed lower VC dimension and better generalization property. Using power exponential distribution function as the activation function of hidden neurons, and in the light of new learning approaches, it is proved that all data became linearly separable in the space of hidden layer outputs which implies that there exist linear output layer weights with zero training error. The proposed methods are applied to some well-known datasets and the simulation results, compared with SVM and some other leading RBF learning methods, show their satisfactory and comparable performance. PMID:26797472

  20. Learning the Rules: Observation and Imitation of a Sorting Strategy by 36-Month-Old Children

    ERIC Educational Resources Information Center

    Williamson, Rebecca A.; Jaswal, Vikram K.; Meltzoff, Andrew N.

    2010-01-01

    Two experiments were used to investigate the scope of imitation by testing whether 36-month-olds can learn to produce a categorization strategy through observation. After witnessing an adult sort a set of objects by a visible property (their color; Experiment 1) or a nonvisible property (the particular sounds produced when the objects were shaken;…

  1. Innovation Abstracts, Volume XIX, 1997.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1997-01-01

    The 52 abstracts in these 29 serial issues describe innovative approaches to teaching and learning in the community college. Sample topics include a checklist for conference presenters, plan to retain students, faculty home page, improvements in writing instruction, cooperative learning, support for high risk students, competitive colleges and the…

  2. Innovation Abstracts, Volume XX, 1998.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1998-01-01

    The 52 abstracts in these 29 serial issues describe innovative approaches to teaching and learning in the community college. Sample topics include reading motivation, barriers to academic success, the learning environment, writing skills, leadership in the criminal justice profession, role-playing strategies, cooperative education, distance…

  3. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models

    PubMed Central

    Hanuschkin, A.; Ganguli, S.; Hahnloser, R. H. R.

    2013-01-01

    Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli. PMID

  4. Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule.

    PubMed

    Beyeler, Michael; Dutt, Nikil D; Krichmar, Jeffrey L

    2013-12-01

    Understanding how the human brain is able to efficiently perceive and understand a visual scene is still a field of ongoing research. Although many studies have focused on the design and optimization of neural networks to solve visual recognition tasks, most of them either lack neurobiologically plausible learning rules or decision-making processes. Here we present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time. The model consists of Izhikevich neurons and conductance-based synapses for realistic approximation of neuronal dynamics, a spike-timing-dependent plasticity (STDP) synaptic learning rule with additional synaptic dynamics for memory encoding, and an accumulator model for memory retrieval and categorization. The full network, which comprised 71,026 neurons and approximately 133 million synapses, ran in real-time on a single off-the-shelf graphics processing unit (GPU). The network was constructed on a publicly available SNN simulator that supports general-purpose neuromorphic computer chips. The network achieved 92% correct classifications on MNIST in 100 rounds of random sub-sampling, which is comparable to other SNN approaches and provides a conservative and reliable performance metric. Additionally, the model correctly predicted reaction times from psychophysical experiments. Because of the scalability of the approach and its neurobiological fidelity, the current model can be extended to an efficient neuromorphic implementation that supports more generalized object recognition and decision-making architectures found in the brain. PMID:23994510

  5. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  6. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  7. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  8. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  9. 37 CFR 1.438 - The abstract.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...

  10. Human-Like Rule Optimization for Continuous Domains

    NASA Astrophysics Data System (ADS)

    Hadzic, Fedja; Dillon, Tharam S.

    When using machine learning techniques for data mining purposes one of the main requirements is that the learned rule set is represented in a comprehensible form. Simpler rules are preferred as they are expected to perform better on unseen data. At the same time the rules should be specific enough so that the misclassification rate is kept to a minimum. In this paper we present a rule optimizing technique motivated by the psychological studies of human concept learning. The technique allows for reasoning to happen at both higher levels of abstraction and lower level of detail in order to optimize the rule set. Information stored at the higher level allows for optimizing processes such as rule splitting, merging and deleting, while the information stored at the lower level allows for determining the attribute relevance for a particular rule. The attributes detected as irrelevant can be removed and the ones previously detected as irrelevant can be reintroduced if necessary. The method is evaluated on the rules extracted from publicly available real world datasets using different classifiers, and the results demonstrate the effectiveness of the presented rule optimizing technique.

  11. Humor, abstraction, and disbelief.

    PubMed

    Hoicka, Elena; Jutsum, Sarah; Gattis, Merideth

    2008-09-01

    We investigated humor as a context for learning about abstraction and disbelief. More specifically, we investigated how parents support humor understanding during book sharing with their toddlers. In Study 1, a corpus analysis revealed that in books aimed at 1-to 2-year-olds, humor is found more often than other forms of doing the wrong thing including mistakes, pretense, lying, false beliefs, and metaphors. In Study 2, 20 parents read a book containing humorous and non-humorous pages to their 19-to 26-month-olds. Parents used a significantly higher percentage of high abstraction extra-textual utterances (ETUs) when reading the humorous pages. In Study 3, 41 parents read either a humorous or non-humorous book to their 18-to 24-month-olds. Parents reading the humorous book made significantly more ETUs coded for a specific form of high abstraction: those encouraging disbelief of prior utterances. Sharing humorous books thus increases toddlers' exposure to high abstraction and belief-based language. PMID:21585438

  12. Learning of an oddity rule by pigeons in a four-choice touch-screen procedure.

    PubMed

    Aust, Ulrike; Steurer, Michael M

    2013-05-01

    Six pigeons were trained to peck at a target (odd stimulus) that was presented on a touch-screen together with three identical distractors (non-odd stimuli). The target could be either a square or a circle that was either blue or green, and the distractors in each trial were always of the opposite form and color to the target. Thus, the birds could solve the task by attending to color, form, or both. Transfer tests showed that performance was not disrupted by novel forms, stimulus sizes, distractor numbers, and display configurations, but broke down with novel stimulus types (textured stimuli, clip art images, and photographs). Transfer to novel colors was, for the most part, restricted to trials in which only one component-target or distractors, but not both-had a novel color. This suggested that the pigeons used a couple of if-then rules rather than an oddity concept to solve the task, and that color differences between target and distractors were the only cue upon which responding was based. A control experiment with the order of color and form tests being reversed excluded the possibility of the prevalence of color being an artifact of task order and reinforcement contingencies. PMID:23111901

  13. Prefrontal cortex organization: dissociating effects of temporal abstraction, relational abstraction, and integration with FMRI.

    PubMed

    Nee, Derek Evan; Jahn, Andrew; Brown, Joshua W

    2014-09-01

    The functions of the prefrontal cortex (PFC) underlie higher-level cognition. Varying proposals suggest that the PFC is organized along a rostral-caudal gradient of abstraction with more abstract representations/processes associated with more rostral areas. However, the operational definition of abstraction is unclear. Here, we contrasted 2 prominent theories of abstraction--temporal and relational--using fMRI. We further examined whether integrating abstract rules--a function common to each theory--recruited the PFC independently of other abstraction effects. While robust effects of relational abstraction were present in the PFC, temporal abstraction effects were absent. Instead, we found activations specific to the integration of relational rules in areas previously shown to be associated with temporal abstraction. We suggest that previous effects of temporal abstraction were due to confounds with integration demands. We propose an integration framework to understand the functions of the PFC that resolves discrepancies in prior data. PMID:23563962

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

    PubMed

    Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias

    2008-12-01

    We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest. PMID:18624656

  15. ALT-C 96: Integrating Technology into the Curriculum. Conference Programme and Abstracts of the Association for Learning Technology Conference (3rd, Glasgow, Scotland, September 16-18, 1996).

    ERIC Educational Resources Information Center

    Cameron, Shona, Ed.

    This program for the 1996 Association for Learning Technology Conference summarizes the poster sessions, discussions, workshops, and software demonstrations, and provides abstracts of the 38 papers presented. Topics covered by the papers include: hand-held technology for mathematics; modeling global warming; computer-mediated communications; Java;…

  16. Identifying users of traditional and Internet-based resources for meal ideas: An association rule learning approach.

    PubMed

    Doub, Allison E; Small, Meg L; Levin, Aron; LeVangie, Kristie; Brick, Timothy R

    2016-08-01

    Increasing home cooking while decreasing the consumption of food prepared away from home is a commonly recommended weight management strategy, however research on where individuals obtain ideas about meals to cook at home is limited. This study examined the characteristics of individuals who reported using traditional and Internet-based resources for meal ideas. 583 participants who were ≥50% responsible for household meal planning were recruited to approximate the 2014 United States Census distribution on sex, age, race/ethnicity, and household income. Participants reported demographic characteristics, home cooking frequency, and their use of 4 traditional resources for meal ideas (e.g., cookbooks), and 7 Internet-based resources for meal ideas (e.g., Pinterest) in an online survey. Independent samples t-tests compared home cooking frequency by resource use. Association rule learning identified those demographic characteristics that were significantly associated with resource use. Family and friends (71%), food community websites (45%), and cookbooks (41%) were the most common resources reported. Cookbook users reported preparing more meals at home per week (M = 9.65, SD = 5.28) compared to non-cookbook users (M = 8.11, SD = 4.93; t = -3.55, p < 0.001). Resource use was generally higher among parents and varied systematically with demographic characteristics. Findings suggest that home cooking interventions may benefit by modifying resources used by their target population. PMID:27067739

  17. Learning from the Experience of Others: The Evolution of Faculty Tenure and Promotion Rules in Comprehensive Institutions

    ERIC Educational Resources Information Center

    Youn, Ted I. K.; Price, Tanya M.

    2009-01-01

    Organizational rules explain organizational stability and change. Using national surveys and fieldwork, we examine changes in tenure and promotion rules at comprehensive colleges and universities from 1969 to 2002. We find that increased rule founding and change arise from the increasingly rationalized environment, such as the academic…

  18. A LARI Experience (Abstract)

    NASA Astrophysics Data System (ADS)

    Cook, M.

    2015-12-01

    (Abstract only) In 2012, Lowell Observatory launched The Lowell Amateur Research Initiative (LARI) to formally involve amateur astronomers in scientific research by bringing them to the attention of and helping professional astronomers with their astronomical research. One of the LARI projects is the BVRI photometric monitoring of Young Stellar Objects (YSOs), wherein amateurs obtain observations to search for new outburst events and characterize the colour evolution of previously identified outbursters. A summary of the scientific and organizational aspects of this LARI project, including its goals and science motivation, the process for getting involved with the project, a description of the team members, their equipment and methods of collaboration, and an overview of the programme stars, preliminary findings, and lessons learned is presented.

  19. Abstract Expressionism. Clip and Save.

    ERIC Educational Resources Information Center

    Hubbard, Guy

    2002-01-01

    Provides information on the art movement, Abstract Expressionism, and includes learning activities. Focuses on the artist Jackson Pollock, offering a reproduction of his artwork, "Convergence: Number 10." Includes background information on the life and career of Pollock and a description of the included artwork. (CMK)

  20. Abstraction in perceptual symbol systems.

    PubMed Central

    Barsalou, Lawrence W

    2003-01-01

    After reviewing six senses of abstraction, this article focuses on abstractions that take the form of summary representations. Three central properties of these abstractions are established: ( i ) type-token interpretation; (ii) structured representation; and (iii) dynamic realization. Traditional theories of representation handle interpretation and structure well but are not sufficiently dynamical. Conversely, connectionist theories are exquisitely dynamic but have problems with structure. Perceptual symbol systems offer an approach that implements all three properties naturally. Within this framework, a loose collection of property and relation simulators develops to represent abstractions. Type-token interpretation results from binding a property simulator to a region of a perceived or simulated category member. Structured representation results from binding a configuration of property and relation simulators to multiple regions in an integrated manner. Dynamic realization results from applying different subsets of property and relation simulators to category members on different occasions. From this standpoint, there are no permanent or complete abstractions of a category in memory. Instead, abstraction is the skill to construct temporary online interpretations of a category's members. Although an infinite number of abstractions are possible, attractors develop for habitual approaches to interpretation. This approach provides new ways of thinking about abstraction phenomena in categorization, inference, background knowledge and learning. PMID:12903648

  1. Feature engineering combined with machine learning and rule-based methods for structured information extraction from narrative clinical discharge summaries

    PubMed Central

    Xu, Yan; Hong, Kai; Tsujii, Junichi

    2012-01-01

    Objective A system that translates narrative text in the medical domain into structured representation is in great demand. The system performs three sub-tasks: concept extraction, assertion classification, and relation identification. Design The overall system consists of five steps: (1) pre-processing sentences, (2) marking noun phrases (NPs) and adjective phrases (APs), (3) extracting concepts that use a dosage-unit dictionary to dynamically switch two models based on Conditional Random Fields (CRF), (4) classifying assertions based on voting of five classifiers, and (5) identifying relations using normalized sentences with a set of effective discriminating features. Measurements Macro-averaged and micro-averaged precision, recall and F-measure were used to evaluate results. Results The performance is competitive with the state-of-the-art systems with micro-averaged F-measure of 0.8489 for concept extraction, 0.9392 for assertion classification and 0.7326 for relation identification. Conclusions The system exploits an array of common features and achieves state-of-the-art performance. Prudent feature engineering sets the foundation of our systems. In concept extraction, we demonstrated that switching models, one of which is especially designed for telegraphic sentences, improved extraction of the treatment concept significantly. In assertion classification, a set of features derived from a rule-based classifier were proven to be effective for the classes such as conditional and possible. These classes would suffer from data scarcity in conventional machine-learning methods. In relation identification, we use two-staged architecture, the second of which applies pairwise classifiers to possible candidate classes. This architecture significantly improves performance. PMID:22586067

  2. Motor Demands Constrain Cognitive Rule Structures.

    PubMed

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-03-01

    Study of human executive function focuses on our ability to represent cognitive rules independently of stimulus or response modality. However, recent findings suggest that executive functions cannot be modularized separately from perceptual and motor systems, and that they instead scaffold on top of motor action selection. Here we investigate whether patterns of motor demands influence how participants choose to implement abstract rule structures. In a learning task that requires integrating two stimulus dimensions for determining appropriate responses, subjects typically structure the problem hierarchically, using one dimension to cue the task-set and the other to cue the response given the task-set. However, the choice of which dimension to use at each level can be arbitrary. We hypothesized that the specific structure subjects adopt would be constrained by the motor patterns afforded within each rule. Across four independent data-sets, we show that subjects create rule structures that afford motor clustering, preferring structures in which adjacent motor actions are valid within each task-set. In a fifth data-set using instructed rules, this bias was strong enough to counteract the well-known task switch-cost when instructions were incongruent with motor clustering. Computational simulations confirm that observed biases can be explained by leveraging overlap in cortical motor representations to improve outcome prediction and hence infer the structure to be learned. These results highlight the importance of sensorimotor constraints in abstract rule formation and shed light on why humans have strong biases to invent structure even when it does not exist. PMID:26966909

  3. Motor Demands Constrain Cognitive Rule Structures

    PubMed Central

    Collins, Anne Gabrielle Eva; Frank, Michael Joshua

    2016-01-01

    Study of human executive function focuses on our ability to represent cognitive rules independently of stimulus or response modality. However, recent findings suggest that executive functions cannot be modularized separately from perceptual and motor systems, and that they instead scaffold on top of motor action selection. Here we investigate whether patterns of motor demands influence how participants choose to implement abstract rule structures. In a learning task that requires integrating two stimulus dimensions for determining appropriate responses, subjects typically structure the problem hierarchically, using one dimension to cue the task-set and the other to cue the response given the task-set. However, the choice of which dimension to use at each level can be arbitrary. We hypothesized that the specific structure subjects adopt would be constrained by the motor patterns afforded within each rule. Across four independent data-sets, we show that subjects create rule structures that afford motor clustering, preferring structures in which adjacent motor actions are valid within each task-set. In a fifth data-set using instructed rules, this bias was strong enough to counteract the well-known task switch-cost when instructions were incongruent with motor clustering. Computational simulations confirm that observed biases can be explained by leveraging overlap in cortical motor representations to improve outcome prediction and hence infer the structure to be learned. These results highlight the importance of sensorimotor constraints in abstract rule formation and shed light on why humans have strong biases to invent structure even when it does not exist. PMID:26966909

  4. Morphological Rules in Russian Conjugation.

    ERIC Educational Resources Information Center

    Thomas, Linda Kopp

    Recent analyses of Russian (Halle 1963, Lightner 1972) have been forced by the criteria of rule "naturalness" and rule "generality" to posit highly abstract underlying forms. These underlying forms and rules are claimed to represent the speaker's competence. Such analyses are now being criticized (Derwing 1973, Hooper 1974) on the following…

  5. Piaget on Abstraction.

    ERIC Educational Resources Information Center

    Moessinger, Pierre; Poulin-Dubois, Diane

    1981-01-01

    Reviews and discusses Piaget's recent work on abstract reasoning. Piaget's distinction between empirical and reflective abstraction is presented; his hypotheses are considered to be metaphorical. (Author/DB)

  6. Cognitive Control over Learning: Creating, Clustering, and Generalizing Task-Set Structure

    ERIC Educational Resources Information Center

    Collins, Anne G. E.; Frank, Michael J.

    2013-01-01

    Learning and executive functions such as task-switching share common neural substrates, notably prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for…

  7. Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework

    NASA Astrophysics Data System (ADS)

    Menon, Prahlad G.; Morris, Lailonny; Staines, Mara; Lima, Joao; Lee, Daniel C.; Gopalakrishnan, Vanathi

    2014-03-01

    Characterization of regional left ventricular (LV) function may have application in prognosticating timely response and informing choice therapy in patients with ischemic cardiomyopathy. The purpose of this study is to characterize LV function through a systematic analysis of 4D (3D + time) endocardial motion over the cardiac cycle in an effort to define objective, clinically useful metrics of pathological remodeling and declining cardiac performance, using standard cardiac MRI data for two distinct patient cohorts accessed from CardiacAtlas.org: a) MESA - a cohort of asymptomatic patients; and b) DETERMINE - a cohort of symptomatic patients with a history of ischemic heart disease (IHD) or myocardial infarction. The LV endocardium was segmented and a signed phase-to-phase Hausdorff distance (HD) was computed at 3D uniformly spaced points tracked on segmented endocardial surface contours, over the cardiac cycle. An LV-averaged index of phase-to-phase endocardial displacement (P2PD) time-histories was computed at each tracked point, using the HD computed between consecutive cardiac phases. Average and standard deviation in P2PD over the cardiac cycle was used to prepare characteristic curves for the asymptomatic and IHD cohort. A novel biomarker of RMS error between mean patient-specific characteristic P2PD over the cardiac cycle for each individual patient and the cumulative P2PD characteristic of a cohort of asymptomatic patients was established as the RMS-P2PD marker. The novel RMS-P2PD marker was tested as a cardiac function based feature for automatic patient classification using a Bayesian Rule Learning (BRL) framework. The RMS-P2PD biomarker indices were significantly different for the symptomatic patient and asymptomatic control cohorts (p<0.001). BRL accurately classified 83.8% of patients correctly from the patient and control populations, with leave-one-out cross validation, using standard indices of LV ejection fraction (LV-EF) and LV end-systolic volume

  8. Changing the Rules: Making Space for Interactive Learning in the Galleries of the Detroit Institute of Arts

    ERIC Educational Resources Information Center

    Czajkowski, Jennifer Wild

    2011-01-01

    Three years after the Detroit Institute of Arts opened with all new, "visitor-centered" galleries, the museum's executive director of learning and interpretation shares the processes, successes, and lessons learned at an institution that embraced an array of hands-on learning models. The models are discussed as components of a comprehensive…

  9. Bibliographies and Abstracts. Clearinghouse for Computer-Assisted Guidance Systems. Project LEARN--Phase II. Lifelong Education, Assessment, and Referral Network.

    ERIC Educational Resources Information Center

    Ryan-Jones, Rebecca E.; And Others

    This document contains four bibliographies and two sets of abstracts of materials on computer-assisted guidance systems. The first bibliography contains references pertaining to the use of the computer-assisted guidance system, DISCOVER. The cited documents are classified as theoretical foundations, evaluation and research reports, program…

  10. Bridging History of the Concept of Function with Learning of Mathematics: Students' Meta-Discursive Rules, Concept Formation and Historical Awareness

    NASA Astrophysics Data System (ADS)

    Kjeldsen, Tinne Hoff; Petersen, Pernille Hviid

    2013-08-01

    In this paper we present a matrix-organised implementation of an experimental course in the history of the concept of a function. The course was implemented in a Danish high school. One of the aims was to bridge history of mathematics with the teaching and learning of mathematics. The course was designed using the theoretical frameworks of a multiple perspective approach to history, Sfard's theory of thinking as communicating, and theories from mathematics education about concept image, concept definition and concept formation. It will be explained how history and extracts of original sources by Euler from 1748 and Dirichlet from 1837 were used to (1) reveal students' meta-discursive rules in mathematics and make them objects of students' reflections, (2) support students' learning of the concept of a function, and (3) develop students' historical awareness. The results show that it is possible to diagnose (some) of students' meta-discursive rules, that some of the students acted according to meta-discursive rules that coincide with Euler's from the 1700s, and that reading a part of a text by Dirichlet from 1837 created obstacles for the students that can be referenced to differences in meta-discursive rules. The experiment revealed that many of the students have a concept image that was in accordance with Euler's rather than with our modern concept definition and that they have process oriented thinking about functions. The students' historical awareness was developed through the course with respect to actors' influence on the formation of mathematical concepts and the notions of internal and external driving forces in the historical development of mathematics.

  11. Collaboration rules.

    PubMed

    Evans, Philip; Wolf, Bob

    2005-01-01

    Corporate leaders seeking to boost growth, learning, and innovation may find the answer in a surprising place: the Linux open-source software community. Linux is developed by an essentially volunteer, self-organizing community of thousands of programmers. Most leaders would sell their grandmothers for workforces that collaborate as efficiently, frictionlessly, and creatively as the self-styled Linux hackers. But Linux is software, and software is hardly a model for mainstream business. The authors have, nonetheless, found surprising parallels between the anarchistic, caffeinated, hirsute world of Linux hackers and the disciplined, tea-sipping, clean-cut world of Toyota engineering. Specifically, Toyota and Linux operate by rules that blend the self-organizing advantages of markets with the low transaction costs of hierarchies. In place of markets' cash and contracts and hierarchies' authority are rules about how individuals and groups work together (with rigorous discipline); how they communicate (widely and with granularity); and how leaders guide them toward a common goal (through example). Those rules, augmented by simple communication technologies and a lack of legal barriers to sharing information, create rich common knowledge, the ability to organize teams modularly, extraordinary motivation, and high levels of trust, which radically lowers transaction costs. Low transaction costs, in turn, make it profitable for organizations to perform more and smaller transactions--and so increase the pace and flexibility typical of high-performance organizations. Once the system achieves critical mass, it feeds on itself. The larger the system, the more broadly shared the knowledge, language, and work style. The greater individuals' reputational capital, the louder the applause and the stronger the motivation. The success of Linux is evidence of the power of that virtuous circle. Toyota's success is evidence that it is also powerful in conventional companies. PMID

  12. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Engineering Education, 1975

    1975-01-01

    Papers abstracted represent those submitted to the distribution center at the 83rd American Society for Engineering Education Convention. Abstracts are grouped under headings corresponding to the main topic of the paper. (Editor/CP)

  13. Born Rule(s)

    NASA Astrophysics Data System (ADS)

    Sinha, Urbasi

    2011-09-01

    This paper is based on work published in [1]. It describes a triple slit experiment using single photons that has been used to provide a bound on one of the most fundamental axioms of quantum mechanics i.e. Born's rule for probabilities [2]. In spite of being one of the most successful theories which describes various natural phenomena, quantum mechanics has enough intricacies and "weirdness" associated with it which makes many physicists believe that it may not be the final theory and hints towards the possibility of more generalized versions. Quantum interference as shown by a double slit diffraction experiment only occurs from pairs of paths. Even in multi-slit versions, interference can only occur between pairs of possibilities and increasing the number of slits does not increase the complexity of the theory that still remains second-order. However, more generalized versions of quantum mechanics may allow for multi-path i.e. higher than second order interference. This experiment also provides a bound on the magnitude of such higher order interference. We have been able to bound the magnitude of three-path interference to less than 10-2 of the expected two-path interference, thus ruling out third and higher order interference and providing a bound on the accuracy of Born's rule.

  14. Abstraction and Consolidation

    ERIC Educational Resources Information Center

    Monaghan, John; Ozmantar, Mehmet Fatih

    2006-01-01

    The framework for this paper is a recently developed theory of abstraction in context. The paper reports on data collected from one student working on tasks concerned with absolute value functions. It examines the relationship between mathematical constructions and abstractions. It argues that an abstraction is a consolidated construction that can…

  15. The Influence of Ground Rules on Chinese Students' Learning of Critical Thinking in Group Work: A Cultural Perspective

    ERIC Educational Resources Information Center

    Fung, Dennis

    2014-01-01

    This article reports the results of a one-year longitudinal study examining a teaching intervention designed to enhance students' learning of critical thinking in Hong Kong. Seventy participating students (age 16-18) learned how to make reasoned arguments through a series of collaborative activities, including critical-thinking modelling…

  16. Playing by the Rules: Researching, Teaching and Learning Sexual Ethics with Young Men in the Australian National Rugby League

    ERIC Educational Resources Information Center

    Albury, Kath; Carmody, Moira; Evers, Clifton; Lumby, Catharine

    2011-01-01

    In 2004, the Australian National Rugby League (NRL) commissioned the Playing By The Rules research project in response to allegations of sexual assault by members of a professional rugby league team. This article offers an overview of the theoretical and methodological approaches adopted by the team, and the subsequent workplace education…

  17. Extracting rate changes in transcriptional regulation from MEDLINE abstracts

    PubMed Central

    2014-01-01

    Background Time delays are important factors that are often neglected in gene regulatory network (GRN) inference models. Validating time delays from knowledge bases is a challenge since the vast majority of biological databases do not record temporal information of gene regulations. Biological knowledge and facts on gene regulations are typically extracted from bio-literature with specialized methods that depend on the regulation task. In this paper, we mine evidences for time delays related to the transcriptional regulation of yeast from the PubMed abstracts. Results Since the vast majority of abstracts lack quantitative time information, we can only collect qualitative evidences of time delays. Specifically, the speed-up or delay in transcriptional regulation rate can provide evidences for time delays (shorter or longer) in GRN. Thus, we focus on deriving events related to rate changes in transcriptional regulation. A corpus of yeast regulation related abstracts was manually labeled with such events. In order to capture these events automatically, we create an ontology of sub-processes that are likely to result in transcription rate changes by combining textual patterns and biological knowledge. We also propose effective feature extraction methods based on the created ontology to identify the direct evidences with specific details of these events. Our ontologies outperform existing state-of-the-art gene regulation ontologies in the automatic rule learning method applied to our corpus. The proposed deterministic ontology rule-based method can achieve comparable performance to the automatic rule learning method based on decision trees. This demonstrates the effectiveness of our ontology in identifying rate-changing events. We also tested the effectiveness of the proposed feature mining methods on detecting direct evidence of events. Experimental results show that the machine learning method on these features achieves an F1-score of 71.43%. Conclusions The manually

  18. Spatial abstraction for autonomous robot navigation.

    PubMed

    Epstein, Susan L; Aroor, Anoop; Evanusa, Matthew; Sklar, Elizabeth I; Parsons, Simon

    2015-09-01

    Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel. PMID:26227680

  19. Loving Those Abstracts

    ERIC Educational Resources Information Center

    Stevens, Lori

    2004-01-01

    The author describes a lesson she did on abstract art with her high school art classes. She passed out a required step-by-step outline of the project process. She asked each of them to look at abstract art. They were to list five or six abstract artists they thought were interesting, narrow their list down to the one most personally intriguing,…

  20. 49 CFR 1113.11 - Abstracts of documents.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 49 Transportation 8 2010-10-01 2010-10-01 false Abstracts of documents. 1113.11 Section 1113.11... OF TRANSPORTATION RULES OF PRACTICE ORAL HEARING § 1113.11 Abstracts of documents. When documents... in orderly fashion to abstract the relevant data from the documents, affording other...

  1. 49 CFR 1113.11 - Abstracts of documents.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 49 Transportation 8 2011-10-01 2011-10-01 false Abstracts of documents. 1113.11 Section 1113.11... OF TRANSPORTATION RULES OF PRACTICE ORAL HEARING § 1113.11 Abstracts of documents. When documents... in orderly fashion to abstract the relevant data from the documents, affording other...

  2. Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules

    NASA Astrophysics Data System (ADS)

    Hassanpour, Saeed; O'Connor, Martin J.; Das, Amar K.

    Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.

  3. Object Classification via Planar Abstraction

    NASA Astrophysics Data System (ADS)

    Oesau, Sven; Lafarge, Florent; Alliez, Pierre

    2016-06-01

    We present a supervised machine learning approach for classification of objects from sampled point data. The main idea consists in first abstracting the input object into planar parts at several scales, then discriminate between the different classes of objects solely through features derived from these planar shapes. Abstracting into planar shapes provides a means to both reduce the computational complexity and improve robustness to defects inherent to the acquisition process. Measuring statistical properties and relationships between planar shapes offers invariance to scale and orientation. A random forest is then used for solving the multiclass classification problem. We demonstrate the potential of our approach on a set of indoor objects from the Princeton shape benchmark and on objects acquired from indoor scenes and compare the performance of our method with other point-based shape descriptors.

  4. Community Development Abstracts.

    ERIC Educational Resources Information Center

    Agency for International Development (Dept. of State), Washington, DC.

    This volume of 1,108 abstracts summarizes the majority of important works on community development during the last ten years. Part I contains abstracts of periodical literature and is classified into 19 sections, including general history, communications, community and area studies, decision-making, leadership, migration and settlement, social…

  5. Leadership Abstracts, Volume 10.

    ERIC Educational Resources Information Center

    Milliron, Mark D., Ed.

    1997-01-01

    The abstracts in this series provide brief discussions of issues related to leadership, administration, professional development, technology, and education in community colleges. Volume 10 for 1997 contains the following 12 abstracts: (1) "On Community College Renewal" (Nathan L. Hodges and Mark D. Milliron); (2) "The Community College Niche in a…

  6. Has Abstractness Been Resolved?

    ERIC Educational Resources Information Center

    Al-Omoush, Ahmad

    1989-01-01

    A discussion focusing on the abstractness of analysis in phonology, debated since the 1960s, describes the issue, reviews the literature on the subject, cites specific natural language examples, and examines the extent to which the issue has been resolved. An underlying representation is said to be abstract if it is different from the derived one,…

  7. Designing for Mathematical Abstraction

    ERIC Educational Resources Information Center

    Pratt, Dave; Noss, Richard

    2010-01-01

    Our focus is on the design of systems (pedagogical, technical, social) that encourage mathematical abstraction, a process we refer to as "designing for abstraction." In this paper, we draw on detailed design experiments from our research on children's understanding about chance and distribution to re-present this work as a case study in designing…

  8. Leadership Abstracts, 1995.

    ERIC Educational Resources Information Center

    Johnson, Larry, Ed.

    1995-01-01

    The abstracts in this series provide two-page discussions of issues related to leadership, administration, and teaching in community colleges. The 12 abstracts for Volume 8, 1995, are: (1) "Redesigning the System To Meet the Workforce Training Needs of the Nation," by Larry Warford; (2) "The College President, the Board, and the Board Chair: A…

  9. Paper Abstract Animals

    ERIC Educational Resources Information Center

    Sutley, Jane

    2010-01-01

    Abstraction is, in effect, a simplification and reduction of shapes with an absence of detail designed to comprise the essence of the more naturalistic images being depicted. Without even intending to, young children consistently create interesting, and sometimes beautiful, abstract compositions. A child's creations, moreover, will always seem to…

  10. Journalism Abstracts. Vol. 15.

    ERIC Educational Resources Information Center

    Popovich, Mark N., Ed.

    This book, the fifteenth volume of an annual publication, contains 373 abstracts of 52 doctoral and 321 master's theses from 50 colleges and universities. The abstracts are arranged alphabetically by author, with the doctoral dissertations appearing first. These cover such topics as advertising, audience analysis, content analysis of news issues…

  11. Leadership Abstracts, 1996.

    ERIC Educational Resources Information Center

    Johnson, Larry, Ed.

    1996-01-01

    The abstracts in this series provide two-page discussions of issues related to leadership, administration, professional development, technology, and education in community colleges. Volume 9 for 1996 includes the following 12 abstracts: (1) "Tech-Prep + School-To-Work: Working Together To Foster Educational Reform," (Roderick F. Beaumont); (2)…

  12. Mathematical Abstraction through Scaffolding

    ERIC Educational Resources Information Center

    Ozmantar, Mehmet Fatih; Roper, Tom

    2004-01-01

    This paper examines the role of scaffolding in the process of abstraction. An activity-theoretic approach to abstraction in context is taken. This examination is carried out with reference to verbal protocols of two 17 year-old students working together on a task connected to sketching the graph of |f|x|)|. Examination of the data suggests that…

  13. Enriching regulatory networks by bootstrap learning using optimised GO-based gene similarity and gene links mined from PubMed abstracts

    SciTech Connect

    Taylor, Ronald C.; Sanfilippo, Antonio P.; McDermott, Jason E.; Baddeley, Robert L.; Riensche, Roderick M.; Jensen, Russell S.; Verhagen, Marc; Pustejovsky, James

    2011-02-18

    Transcriptional regulatory networks are being determined using “reverse engineering” methods that infer connections based on correlations in gene state. Corroboration of such networks through independent means such as evidence from the biomedical literature is desirable. Here, we explore a novel approach, a bootstrapping version of our previous Cross-Ontological Analytic method (XOA) that can be used for semi-automated annotation and verification of inferred regulatory connections, as well as for discovery of additional functional relationships between the genes. First, we use our annotation and network expansion method on a biological network learned entirely from the literature. We show how new relevant links between genes can be iteratively derived using a gene similarity measure based on the Gene Ontology that is optimized on the input network at each iteration. Second, we apply our method to annotation, verification, and expansion of a set of regulatory connections found by the Context Likelihood of Relatedness algorithm.

  14. Abstract Datatypes in PVS

    NASA Technical Reports Server (NTRS)

    Owre, Sam; Shankar, Natarajan

    1997-01-01

    PVS (Prototype Verification System) is a general-purpose environment for developing specifications and proofs. This document deals primarily with the abstract datatype mechanism in PVS which generates theories containing axioms and definitions for a class of recursive datatypes. The concepts underlying the abstract datatype mechanism are illustrated using ordered binary trees as an example. Binary trees are described by a PVS abstract datatype that is parametric in its value type. The type of ordered binary trees is then presented as a subtype of binary trees where the ordering relation is also taken as a parameter. We define the operations of inserting an element into, and searching for an element in an ordered binary tree; the bulk of the report is devoted to PVS proofs of some useful properties of these operations. These proofs illustrate various approaches to proving properties of abstract datatype operations. They also describe the built-in capabilities of the PVS proof checker for simplifying abstract datatype expressions.

  15. The Rules of Evidence: Focus on Key Points to Develop the Best Strategy to Evaluate Professional Learning

    ERIC Educational Resources Information Center

    Guskey, Thomas R.

    2012-01-01

    Gathering evidence on the outcomes of any professional learning experience can be a challenging and complicated task. It involves consideration of a wide variety of perceptual and contextual issues, some obvious to education leaders and others not. Those who want to succeed in this process may find the following points helpful: (1) Always begin…

  16. Rules of Engagement: The Joint Influence of Trainer Expressiveness and Trainee Experiential Learning Style on Engagement and Training Transfer

    ERIC Educational Resources Information Center

    Rangel, Bertha; Chung, Wonjoon; Harris, T. Brad; Carpenter, Nichelle C.; Chiaburu, Dan S.; Moore, Jenna L.

    2015-01-01

    We investigated the joint effect of trainer expressiveness and trainee experiential learning style on training transfer intentions. Extending prior research where trainer expressiveness has been established as a positive predictor of transfer, we show that trainer expressiveness is more impactful for trainees with high (vs. low) experiential…

  17. Experience with abstract notation one

    NASA Technical Reports Server (NTRS)

    Harvey, James D.; Weaver, Alfred C.

    1990-01-01

    The development of computer science has produced a vast number of machine architectures, programming languages, and compiler technologies. The cross product of these three characteristics defines the spectrum of previous and present data representation methodologies. With regard to computer networks, the uniqueness of these methodologies presents an obstacle when disparate host environments are to be interconnected. Interoperability within a heterogeneous network relies upon the establishment of data representation commonality. The International Standards Organization (ISO) is currently developing the abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively address this problem. When used within the presentation layer of the open systems interconnection reference model, these two standards provide the data representation commonality required to facilitate interoperability. The details of a compiler that was built to automate the use of ASN.1 and BER are described. From this experience, insights into both standards are given and potential problems relating to this development effort are discussed.

  18. Abstracts of SIG Sessions.

    ERIC Educational Resources Information Center

    Proceedings of the ASIS Annual Meeting, 1997

    1997-01-01

    Presents abstracts of SIG Sessions. Highlights include digital collections; information retrieval methods; public interest/fair use; classification and indexing; electronic publication; funding; globalization; information technology projects; interface design; networking in developing countries; metadata; multilingual databases; networked…

  19. Automatic Abstraction in Planning

    NASA Technical Reports Server (NTRS)

    Christensen, J.

    1991-01-01

    Traditionally, abstraction in planning has been accomplished by either state abstraction or operator abstraction, neither of which has been fully automatic. We present a new method, predicate relaxation, for automatically performing state abstraction. PABLO, a nonlinear hierarchical planner, implements predicate relaxation. Theoretical, as well as empirical results are presented which demonstrate the potential advantages of using predicate relaxation in planning. We also present a new definition of hierarchical operators that allows us to guarantee a limited form of completeness. This new definition is shown to be, in some ways, more flexible than previous definitions of hierarchical operators. Finally, a Classical Truth Criterion is presented that is proven to be sound and complete for a planning formalism that is general enough to include most classical planning formalisms that are based on the STRIPS assumption.

  20. 1971 Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Journal of Engineering Education, 1971

    1971-01-01

    Included are 112 abstracts listed under headings such as: acoustics, continuing engineering studies, educational research and methods, engineering design, libraries, liberal studies, and materials. Other areas include agricultural, electrical, mechanical, mineral, and ocean engineering. (TS)

  1. 2016 ACPA MEETING ABSTRACTS.

    PubMed

    2016-07-01

    The peer-reviewed abstracts presented at the 73rd Annual Meeting of the ACPA are published as submitted by the authors. For financial conflict of interest disclosure, please visit http://meeting.acpa-cpf.org/disclosures.html. PMID:27447885

  2. Abstracts of contributed papers

    SciTech Connect

    Not Available

    1994-08-01

    This volume contains 571 abstracts of contributed papers to be presented during the Twelfth US National Congress of Applied Mechanics. Abstracts are arranged in the order in which they fall in the program -- the main sessions are listed chronologically in the Table of Contents. The Author Index is in alphabetical order and lists each paper number (matching the schedule in the Final Program) with its corresponding page number in the book.

  3. TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries.

    PubMed

    Chang, Yung-Chun; Dai, Hong-Jie; Wu, Johnny Chi-Yang; Chen, Jian-Ming; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

    2013-12-01

    Patient discharge summaries provide detailed medical information about individuals who have been hospitalized. To make a precise and legitimate assessment of the abundant data, a proper time layout of the sequence of relevant events should be compiled and used to drive a patient-specific timeline, which could further assist medical personnel in making clinical decisions. The process of identifying the chronological order of entities is called temporal relation extraction. In this paper, we propose a hybrid method to identify appropriate temporal links between a pair of entities. The method combines two approaches: one is rule-based and the other is based on the maximum entropy model. We develop an integration algorithm to fuse the results of the two approaches. All rules and the integration algorithm are formally stated so that one can easily reproduce the system and results. To optimize the system's configuration, we used the 2012 i2b2 challenge TLINK track dataset and applied threefold cross validation to the training set. Then, we evaluated its performance on the training and test datasets. The experiment results show that the proposed TEMPTING (TEMPoral relaTion extractING) system (ranked seventh) achieved an F-score of 0.563, which was at least 30% better than that of the baseline system, which randomly selects TLINK candidates from all pairs and assigns the TLINK types. The TEMPTING system using the hybrid method also outperformed the stage-based TEMPTING system. Its F-scores were 3.51% and 0.97% better than those of the stage-based system on the training set and test set, respectively. PMID:24060600

  4. Raising the Level of Abstraction in Online Education: The Context

    ERIC Educational Resources Information Center

    Natale, Samuel M.; Libertella, Anthony F.; Sora, Sebastian A.; Ulin, John

    2007-01-01

    A commonly accepted definition of online learning is that students have access to learning experiences in: time, place, pace, learning style, content, assessment, and pathways (Chen, 2003). Although this is true, there is a considerable concern about the level of abstraction involved in online education. Critics of flexible learning call it just…

  5. Metacognition and abstract reasoning.

    PubMed

    Markovits, Henry; Thompson, Valerie A; Brisson, Janie

    2015-05-01

    The nature of people's meta-representations of deductive reasoning is critical to understanding how people control their own reasoning processes. We conducted two studies to examine whether people have a metacognitive representation of abstract validity and whether familiarity alone acts as a separate metacognitive cue. In Study 1, participants were asked to make a series of (1) abstract conditional inferences, (2) concrete conditional inferences with premises having many potential alternative antecedents and thus specifically conducive to the production of responses consistent with conditional logic, or (3) concrete problems with premises having relatively few potential alternative antecedents. Participants gave confidence ratings after each inference. Results show that confidence ratings were positively correlated with logical performance on abstract problems and concrete problems with many potential alternatives, but not with concrete problems with content less conducive to normative responses. Confidence ratings were higher with few alternatives than for abstract content. Study 2 used a generation of contrary-to-fact alternatives task to improve levels of abstract logical performance. The resulting increase in logical performance was mirrored by increases in mean confidence ratings. Results provide evidence for a metacognitive representation based on logical validity, and show that familiarity acts as a separate metacognitive cue. PMID:25416026

  6. Thyra Abstract Interface Package

    2005-09-01

    Thrya primarily defines a set of abstract C++ class interfaces needed for the development of abstract numerical atgorithms (ANAs) such as iterative linear solvers, transient solvers all the way up to optimization. At the foundation of these interfaces are abstract C++ classes for vectors, vector spaces, linear operators and multi-vectors. Also included in the Thyra package is C++ code for creating concrete vector, vector space, linear operator, and multi-vector subclasses as well as other utilitiesmore » to aid in the development of ANAs. Currently, very general and efficient concrete subclass implementations exist for serial and SPMD in-core vectors and multi-vectors. Code also currently exists for testing objects and providing composite objects such as product vectors.« less

  7. Abstracting and indexing guide

    USGS Publications Warehouse

    U.S. Department of the Interior; Office of Water Resources Research

    1974-01-01

    These instructions have been prepared for those who abstract and index scientific and technical documents for the Water Resources Scientific Information Center (WRSIC). With the recent publication growth in all fields, information centers have undertaken the task of keeping the various scientific communities aware of current and past developments. An abstract with carefully selected index terms offers the user of WRSIC services a more rapid means for deciding whether a document is pertinent to his needs and professional interests, thus saving him the time necessary to scan the complete work. These means also provide WRSIC with a document representation or surrogate which is more easily stored and manipulated to produce various services. Authors are asked to accept the responsibility for preparing abstracts of their own papers to facilitate quick evaluation, announcement, and dissemination to the scientific community.

  8. Association Rules

    NASA Astrophysics Data System (ADS)

    Höppner, Frank

    Association rules are rules of the kind "70% of the customers who buy vine and cheese also buy grapes". While the traditional field of application is market basket analysis, association rule mining has been applied to various fields since then, which has led to a number of important modifications and extensions. We discuss the most frequently applied approach that is central to many extensions, the Apriori algorithm, and briefly review some applications to other data types, well-known problems of rule evaluation via support and confidence, and extensions of or alternatives to the standard framework.

  9. Abstraction and art.

    PubMed Central

    Gortais, Bernard

    2003-01-01

    In a given social context, artistic creation comprises a set of processes, which relate to the activity of the artist and the activity of the spectator. Through these processes we see and understand that the world is vaster than it is said to be. Artistic processes are mediated experiences that open up the world. A successful work of art expresses a reality beyond actual reality: it suggests an unknown world using the means and the signs of the known world. Artistic practices incorporate the means of creation developed by science and technology and change forms as they change. Artists and the public follow different processes of abstraction at different levels, in the definition of the means of creation, of representation and of perception of a work of art. This paper examines how the processes of abstraction are used within the framework of the visual arts and abstract painting, which appeared during a period of growing importance for the processes of abstraction in science and technology, at the beginning of the twentieth century. The development of digital platforms and new man-machine interfaces allow multimedia creations. This is performed under the constraint of phases of multidisciplinary conceptualization using generic representation languages, which tend to abolish traditional frontiers between the arts: visual arts, drama, dance and music. PMID:12903659

  10. The SIDdatagrabber (Abstract)

    NASA Astrophysics Data System (ADS)

    Silvis, G.

    2015-12-01

    (Abstract only) The Stanford/SARA SuperSid project offers an opportunity for adding data to the AAVSO SID Monitoring project. You can now build a SID antenna and monitoring setup for about $150. And with the SIDdatagrabber application you can easily re-purpose the data collected for the AAVSO.

  11. Making the Abstract Concrete

    ERIC Educational Resources Information Center

    Potter, Lee Ann

    2005-01-01

    President Ronald Reagan nominated a woman to serve on the United States Supreme Court. He did so through a single-page form letter, completed in part by hand and in part by typewriter, announcing Sandra Day O'Connor as his nominee. While the document serves as evidence of a historic event, it is also a tangible illustration of abstract concepts…

  12. Leadership Abstracts, 2002.

    ERIC Educational Resources Information Center

    Wilson, Cynthia, Ed.; Milliron, Mark David, Ed.

    2002-01-01

    This 2002 volume of Leadership Abstracts contains issue numbers 1-12. Articles include: (1) "Skills Certification and Workforce Development: Partnering with Industry and Ourselves," by Jeffrey A. Cantor; (2) "Starting Again: The Brookhaven Success College," by Alice W. Villadsen; (3) "From Digital Divide to Digital Democracy," by Gerardo E. de los…

  13. Leadership Abstracts, 1993.

    ERIC Educational Resources Information Center

    Doucette, Don, Ed.

    1993-01-01

    This document includes 10 issues of Leadership Abstracts (volume 6, 1993), a newsletter published by the League for Innovation in the Community College (California). The featured articles are: (1) "Reinventing Government" by David T. Osborne; (2) "Community College Workforce Training Programs: Expanding the Mission to Meet Critical Needs" by…

  14. Abstraction through Game Play

    ERIC Educational Resources Information Center

    Avraamidou, Antri; Monaghan, John; Walker, Aisha

    2012-01-01

    This paper examines the computer game play of an 11-year-old boy. In the course of building a virtual house he developed and used, without assistance, an artefact and an accompanying strategy to ensure that his house was symmetric. We argue that the creation and use of this artefact-strategy is a mathematical abstraction. The discussion…

  15. CIRF Abstracts, Volume 12.

    ERIC Educational Resources Information Center

    International Labour Office, Geneva (Switzerland).

    The aim of the CIRF abstracts is to convey information about vocational training ideas, programs, experience, and experiments described in periodicals, books, and other publications and relating to operative personnel, supervisors, and technical and training staff in all sectors of economic activity. Information is also given on major trends in…

  16. Leadership Abstracts, 1999.

    ERIC Educational Resources Information Center

    Leadership Abstracts, 1999

    1999-01-01

    This document contains five Leadership Abstracts publications published February-December 1999. The article, "Teaching the Teachers: Meeting the National Teacher Preparation Challenge," authored by George R. Boggs and Sadie Bragg, examines the community college role and makes recommendations and a call to action for teacher education. "Chaos…

  17. Double Trouble (Abstract)

    NASA Astrophysics Data System (ADS)

    Simonsen, M.

    2015-12-01

    (Abstract only) Variable stars with close companions can be difficult to accurately measure and characterize. The companions can create misidentifications, which in turn can affect the perceived magnitudes, amplitudes, periods, and colors of the variable stars. We will show examples of these Double Trouble stars and the impact their close companions have had on our understanding of some of these variable stars.

  18. Send Me No Abstract.

    ERIC Educational Resources Information Center

    Levy, Steven

    1985-01-01

    Discusses Magazine Index's practice of assigning letter grades (sometimes inaccurate) to book, restaurant, and movie reviews, thus allowing patrons to get the point of the review from the index rather than the article itself, and argues that this situation is indicative of the larger problem of reliability of abstracts. (MBR)

  19. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Engineering Education, 1976

    1976-01-01

    Presents the abstracts of 158 papers presented at the American Society for Engineering Education's annual conference at Knoxville, Tennessee, June 14-17, 1976. Included are engineering topics covering education, aerospace, agriculture, biomedicine, chemistry, computers, electricity, acoustics, environment, mechanics, and women. (SL)

  20. Water reuse. [Lead abstract

    SciTech Connect

    Middlebrooks, E.J.

    1982-01-01

    Separate abstracts were prepared for the 31 chapters of this book which deals with all aspects of wastewater reuse. Design data, case histories, performance data, monitoring information, health information, social implications, legal and organizational structures, and background information needed to analyze the desirability of water reuse are presented. (KRM)

  1. Reasoning abstractly about resources

    NASA Technical Reports Server (NTRS)

    Clement, B.; Barrett, A.

    2001-01-01

    r describes a way to schedule high level activities before distributing them across multiple rovers in order to coordinate the resultant use of shared resources regardless of how each rover decides how to perform its activities. We present an algorithm for summarizing the metric resource requirements of an abstract activity based n the resource usages of its potential refinements.

  2. Abstracts of SIG Sessions.

    ERIC Educational Resources Information Center

    Proceedings of the ASIS Annual Meeting, 1995

    1995-01-01

    Presents abstracts of 15 special interest group (SIG) sessions. Topics include navigation and information utilization in the Internet, natural language processing, automatic indexing, image indexing, classification, users' models of database searching, online public access catalogs, education for information professions, information services,…

  3. Annual Conference Abstracts

    ERIC Educational Resources Information Center

    Journal of Engineering Education, 1972

    1972-01-01

    Includes abstracts of papers presented at the 80th Annual Conference of the American Society for Engineering Education. The broad areas include aerospace, affiliate and associate member council, agricultural engineering, biomedical engineering, continuing engineering studies, chemical engineering, civil engineering, computers, cooperative…

  4. Computers in Abstract Algebra

    ERIC Educational Resources Information Center

    Nwabueze, Kenneth K.

    2004-01-01

    The current emphasis on flexible modes of mathematics delivery involving new information and communication technology (ICT) at the university level is perhaps a reaction to the recent change in the objectives of education. Abstract algebra seems to be one area of mathematics virtually crying out for computer instructional support because of the…

  5. Abstract Film and Beyond.

    ERIC Educational Resources Information Center

    Le Grice, Malcolm

    A theoretical and historical account of the main preoccupations of makers of abstract films is presented in this book. The book's scope includes discussion of nonrepresentational forms as well as examination of experiments in the manipulation of time in films. The ten chapters discuss the following topics: art and cinematography, the first…

  6. State-of-the-art in design rules for drug delivery platforms: lessons learned from FDA-approved nanomedicines.

    PubMed

    Dawidczyk, Charlene M; Kim, Chloe; Park, Jea Ho; Russell, Luisa M; Lee, Kwan Hyi; Pomper, Martin G; Searson, Peter C

    2014-08-10

    The ability to efficiently deliver a drug to a tumor site is dependent on a wide range of physiologically imposed design constraints. Nanotechnology provides the possibility of creating delivery vehicles where these design constraints can be decoupled, allowing new approaches for reducing the unwanted side effects of systemic delivery, increasing targeting efficiency and efficacy. Here we review the design strategies of the two FDA-approved antibody-drug conjugates (Brentuximab vedotin and Trastuzumab emtansine) and the four FDA-approved nanoparticle-based drug delivery platforms (Doxil, DaunoXome, Marqibo, and Abraxane) in the context of the challenges associated with systemic targeted delivery of a drug to a solid tumor. The lessons learned from these nanomedicines provide an important insight into the key challenges associated with the development of new platforms for systemic delivery of anti-cancer drugs. PMID:24874289

  7. The Acquisition of Abstract Words by Young Infants

    ERIC Educational Resources Information Center

    Bergelson, Elika; Swingley, Daniel

    2013-01-01

    Young infants' learning of words for abstract concepts like "all gone" and "eat," in contrast to their learning of more concrete words like "apple" and "shoe," may follow a relatively protracted developmental course. We examined whether infants know such abstract words. Parents named one of two events shown in side-by-side videos while their…

  8. Innovation Abstracts: Volume XI, Numbers 1-30.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1989-01-01

    This series of one- to two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) cooperative planning for institutional excellence; (2) rewarding scholarship among community college faculty; (3) in-class debates as a learning strategy; (4)…

  9. Historical development of abstracting.

    PubMed

    Skolnik, H

    1979-11-01

    The abstract, under a multitude of names, such as hypothesis, marginalia, abridgement, extract, digest, précis, resumé, and summary, has a long history, one which is concomitant with advancing scholarship. The progression of this history from the Sumerian civilization ca. 3600 B.C., through the Egyptian and Greek civilizations, the Hellenistic period, the Dark Ages, Middle Ages, Renaissance, and into the modern period is reviewed. PMID:399482

  10. Generalized Abstract Symbolic Summaries

    NASA Technical Reports Server (NTRS)

    Person, Suzette; Dwyer, Matthew B.

    2009-01-01

    Current techniques for validating and verifying program changes often consider the entire program, even for small changes, leading to enormous V&V costs over a program s lifetime. This is due, in large part, to the use of syntactic program techniques which are necessarily imprecise. Building on recent advances in symbolic execution of heap manipulating programs, in this paper, we develop techniques for performing abstract semantic differencing of program behaviors that offer the potential for improved precision.

  11. Development of Abstract Grammatical Categorization in Infants

    ERIC Educational Resources Information Center

    Cyr, Marilyn; Shi, Rushen

    2013-01-01

    This study examined abstract syntactic categorization in infants, using the case of grammatical gender. Ninety-six French-learning 14-, 17-, 20-, and 30-month-olds completed the study. In a preferential looking procedure infants were tested on their generalized knowledge of grammatical gender involving pseudonouns and gender-marking determiners.…

  12. Abstracts of Research Papers 1977 AAHPER Convention.

    ERIC Educational Resources Information Center

    Sage, George H., Ed.

    This volume of abstracts describes papers written on the following topics: (1) Strength Physiology; (2) Learning Disabilities (motor); (3) Physiology - General; (4) Work Capacity; (5) Measurement and Recreation; (6) Biomechanics; (7) Professional Preparation (physical education); (8) Muscle Performance; (9) Sociology of Sport; (10) History of…

  13. Using Group Explorer in Teaching Abstract Algebra

    ERIC Educational Resources Information Center

    Schubert, Claus; Gfeller, Mary; Donohue, Christopher

    2013-01-01

    This study explores the use of Group Explorer in an undergraduate mathematics course in abstract algebra. The visual nature of Group Explorer in representing concepts in group theory is an attractive incentive to use this software in the classroom. However, little is known about students' perceptions on this technology in learning concepts in…

  14. Cool Cats: Feline Fun with Abstract Art.

    ERIC Educational Resources Information Center

    Lambert, Phyllis Gilchrist

    2002-01-01

    Presents a lesson that teaches students about abstract art in a fun way. Explains that students draw cats, learn about the work of Pablo Picasso, and, in the style of Picasso, combine the parts of the cats (tail, legs, head, body) together in unconventional ways. (CMK)

  15. Greenbook Abstract & Catalog--4.

    ERIC Educational Resources Information Center

    Coole, Walter A.; And Others

    This catalog is the fourth in a series extending and updating teaching materials previously disseminated through the ERIC system, including the "Greenbook System" of training materials for higher education professionals (ED 103 083-084 and 148 438), Open Classroom Documentation, a procedural manual for an autoinstructional learning laboratory at…

  16. EBS Radionuclide Transport Abstraction

    SciTech Connect

    J. Prouty

    2006-07-14

    The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment (TSPA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers advective transport and diffusive transport

  17. Using Group Explorer in teaching abstract algebra

    NASA Astrophysics Data System (ADS)

    Schubert, Claus; Gfeller, Mary; Donohue, Christopher

    2013-04-01

    This study explores the use of Group Explorer in an undergraduate mathematics course in abstract algebra. The visual nature of Group Explorer in representing concepts in group theory is an attractive incentive to use this software in the classroom. However, little is known about students' perceptions on this technology in learning concepts in abstract algebra. A total of 26 participants in an undergraduate course studying group theory were surveyed regarding their experiences using Group Explorer. Findings indicate that all participants believed that the software was beneficial to their learning and described their attitudes regarding the software in terms of using the technology and its helpfulness in learning concepts. A multiple regression analysis reveals that representational fluency of concepts with the software correlated significantly with participants' understanding of group concepts yet, participants' attitudes about Group Explorer and technology in general were not significant factors.

  18. Binary translation using peephole translation rules

    DOEpatents

    Bansal, Sorav; Aiken, Alex

    2010-05-04

    An efficient binary translator uses peephole translation rules to directly translate executable code from one instruction set to another. In a preferred embodiment, the translation rules are generated using superoptimization techniques that enable the translator to automatically learn translation rules for translating code from the source to target instruction set architecture.

  19. EBS Radionuclide Transport Abstraction

    SciTech Connect

    J.D. Schreiber

    2005-08-25

    The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in ''Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration'' (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment for the license application (TSPA-LA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA-LA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers

  20. IEEE conference record -- Abstracts

    SciTech Connect

    Not Available

    1994-01-01

    This conference covers the following areas: computational plasma physics; vacuum electronic; basic phenomena in fully ionized plasmas; plasma, electron, and ion sources; environmental/energy issues in plasma science; space plasmas; plasma processing; ball lightning/spherical plasma configurations; plasma processing; fast wave devices; magnetic fusion; basic phenomena in partially ionized plasma; dense plasma focus; plasma diagnostics; basic phenomena in weakly ionized gases; fast opening switches; MHD; fast z-pinches and x-ray lasers; intense ion and electron beams; laser-produced plasmas; microwave plasma interactions; EM and ETH launchers; solid state plasmas and switches; intense beam microwaves; and plasmas for lighting. Separate abstracts were prepared for 416 papers in this conference.

  1. Teaching for Abstraction: A Model

    ERIC Educational Resources Information Center

    White, Paul; Mitchelmore, Michael C.

    2010-01-01

    This article outlines a theoretical model for teaching elementary mathematical concepts that we have developed over the past 10 years. We begin with general ideas about the abstraction process and differentiate between "abstract-general" and "abstract-apart" concepts. A 4-phase model of teaching, called Teaching for Abstraction, is then proposed…

  2. Learning to Learn about Uncertain Feedback

    ERIC Educational Resources Information Center

    Faraut, Mailys C. M.; Procyk, Emmanuel; Wilson, Charles R. E.

    2016-01-01

    Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to…

  3. Linking Research to Policy, Practice, and Education: Lessons Learned, Tasks Ahead. Program Abstracts. Annual Scientific Meeting of the Gerontological Society of America (53rd, Washington, DC, November 17-21, 2000).

    ERIC Educational Resources Information Center

    Gerontologist, 2000

    2000-01-01

    This publication contains abstracts from the 53rd annual meeting of the Gerontological Society of America. The abstracts are arranged numerically by the session number in which they appear. Several abstracts are listed under each of the 388 sessions. Although the sessions are not limited to one topic, the dominant theme is education concerning all…

  4. Automated Supernova Discovery (Abstract)

    NASA Astrophysics Data System (ADS)

    Post, R. S.

    2015-12-01

    (Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.

  5. Stellar Presentations (Abstract)

    NASA Astrophysics Data System (ADS)

    Young, D.

    2015-12-01

    (Abstract only) The AAVSO is in the process of expanding its education, outreach and speakers bureau program. powerpoint presentations prepared for specific target audiences such as AAVSO members, educators, students, the general public, and Science Olympiad teams, coaches, event supervisors, and state directors will be available online for members to use. The presentations range from specific and general content relating to stellar evolution and variable stars to specific activities for a workshop environment. A presentation—even with a general topic—that works for high school students will not work for educators, Science Olympiad teams, or the general public. Each audience is unique and requires a different approach. The current environment necessitates presentations that are captivating for a younger generation that is embedded in a highly visual and sound-bite world of social media, twitter and U-Tube, and mobile devices. For educators, presentations and workshops for themselves and their students must support the Next Generation Science Standards (NGSS), the Common Core Content Standards, and the Science Technology, Engineering and Mathematics (STEM) initiative. Current best practices for developing relevant and engaging powerpoint presentations to deliver information to a variety of targeted audiences will be presented along with several examples.

  6. Adaptation and Extension of the Framework of Reducing Abstraction in the Case of Differential Equations

    ERIC Educational Resources Information Center

    Raychaudhuri, Debasree

    2014-01-01

    Although there is no consensus in regard to a unique meaning for abstraction, there is a recognition of the existence of several theories of abstraction, and that the ability to abstract is imperative to learning and doing meaningful mathematics. The theory of "reducing abstraction" maps the abstract nature of mathematics to the nature…

  7. Abstraction of Drift Seepage

    SciTech Connect

    J.T. Birkholzer

    2004-11-01

    This model report documents the abstraction of drift seepage, conducted to provide seepage-relevant parameters and their probability distributions for use in Total System Performance Assessment for License Application (TSPA-LA). Drift seepage refers to the flow of liquid water into waste emplacement drifts. Water that seeps into drifts may contact waste packages and potentially mobilize radionuclides, and may result in advective transport of radionuclides through breached waste packages [''Risk Information to Support Prioritization of Performance Assessment Models'' (BSC 2003 [DIRS 168796], Section 3.3.2)]. The unsaturated rock layers overlying and hosting the repository form a natural barrier that reduces the amount of water entering emplacement drifts by natural subsurface processes. For example, drift seepage is limited by the capillary barrier forming at the drift crown, which decreases or even eliminates water flow from the unsaturated fractured rock into the drift. During the first few hundred years after waste emplacement, when above-boiling rock temperatures will develop as a result of heat generated by the decay of the radioactive waste, vaporization of percolation water is an additional factor limiting seepage. Estimating the effectiveness of these natural barrier capabilities and predicting the amount of seepage into drifts is an important aspect of assessing the performance of the repository. The TSPA-LA therefore includes a seepage component that calculates the amount of seepage into drifts [''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504], Section 6.3.3.1)]. The TSPA-LA calculation is performed with a probabilistic approach that accounts for the spatial and temporal variability and inherent uncertainty of seepage-relevant properties and processes. Results are used for subsequent TSPA-LA components that may handle, for example, waste package corrosion or radionuclide transport.

  8. Attracting Girls into Physics (abstract)

    NASA Astrophysics Data System (ADS)

    Gadalla, Afaf

    2009-04-01

    A recent international study of women in physics showed that enrollment in physics and science is declining for both males and females and that women are severely underrepresented in careers requiring a strong physics background. The gender gap begins early in the pipeline, from the first grade. Girls are treated differently than boys at home and in society in ways that often hinder their chances for success. They have fewer freedoms, are discouraged from accessing resources or being adventurous, have far less exposure to problem solving, and are not encouraged to choose their lives. In order to motivate more girl students to study physics in the Assiut governorate of Egypt, the Assiut Alliance for the Women and Assiut Education District collaborated in renovating the education of physics in middle and secondary school classrooms. A program that helps in increasing the number of girls in science and physics has been designed in which informal groupings are organized at middle and secondary schools to involve girls in the training and experiences needed to attract and encourage girls to learn physics. During implementation of the program at some schools, girls, because they had not been trained in problem-solving as boys, appeared not to be as facile in abstracting the ideas of physics, and that was the primary reason for girls dropping out of science and physics. This could be overcome by holding a topical physics and technology summer school under the supervision of the Assiut Alliance for the Women.

  9. Abstracts of Review Articles and Educational Materials in Physiology

    ERIC Educational Resources Information Center

    Physiology Teacher, 1977

    1977-01-01

    Contained are 99 abstracts of review articles, texts, books, manuals, learning programs, and audiovisual material used in teaching physiology. Specific fields include cell physiology, circulation, comparative physiology, development and aging, endocrinology and metabolism, environmental and exercise physiology, gastrointestinal physiology, muscle…

  10. Advance Organizers: Concret Versus Abstract.

    ERIC Educational Resources Information Center

    Corkill, Alice J.; And Others

    1988-01-01

    Two experiments examined the relative effects of concrete and abstract advance organizers on students' memory for subsequent prose. Results of the experiments are discussed in terms of the memorability, familiarity, and visualizability of concrete and abstract verbal materials. (JD)

  11. Accepted scientific research works (abstracts).

    PubMed

    2014-01-01

    These are the 39 accepted abstracts for IAYT's Symposium on Yoga Research (SYR) September 24-24, 2014 at the Kripalu Center for Yoga & Health and published in the Final Program Guide and Abstracts. PMID:25645134

  12. Rules to acquire by.

    PubMed

    Nolop, Bruce

    2007-09-01

    When Bruce Nolop was an investment banker, he saw only the glamorous side of acquisitions. Since becoming executive vice president and chief financial officer of Pitney Bowes, however, he's learned how hard it is to pull them off. In this article, he shares the lessons his organization has learned throughout its successful six-year acquisition campaign, which comprised more than 70 deals: Stick to adjacent spaces, take a portfolio approach, have a business sponsor, know how to judge an acquisition, and don't shop when you're hungry. Pitney Bowes's management and board of directors now use these five basic rules to chart the company's growth course. For example, when evaluating a potential acquisition, Pitney Bowes distinguishes between "platform" and "bolt-on" acquisitions to set expectations and guide integration efforts; the company applies different criteria, depending on the type. According to Nolop, any company can improve its acquisition track record if it is able to learn from experience, and he suspects that Pitney Bowes's rules apply just as well to other organizations. Buying a company should be treated like any other business process, he maintains. It should be approached deliberately and reviewed and improved constantly. That means mapping a complex chain of actions; paying attention to what can go right or wrong at different stages; and using standard, constantly honed, approaches and tools. PMID:17886488

  13. Leadership Abstracts, Volume 11, Numbers 1-10, 1998.

    ERIC Educational Resources Information Center

    Milliron, Mark D. Ed.

    1998-01-01

    The abstracts in this series provide brief discussions of issues related to leadership, administration, professional development, technology, and education in community colleges. Volume 11 for 1998 contains the following 10 abstracts: (1) "What If They Learn Differently: Applying Multiple Intelligences Theory in the Community College" (Rene…

  14. Innovation Abstracts, Volume X, Numbers 1-30. 1988.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1988-01-01

    This series of one- to two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) staff development; (2) integrating computers into the curriculum; (3) a strategy for selecting and hiring good teachers; (4) faculty involvement in support services…

  15. Rules for Optical Metrology

    NASA Technical Reports Server (NTRS)

    Stahl, H. Philip

    2014-01-01

    Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task. GUIDING PRINCIPLES 1. Fully Understand the Task 2. Develop an Error Budget 3. Continuous Metrology Coverage 4. Know where you are 5. 'Test like you fly' 6. Independent Cross-Checks 7. Understand All Anomalies. These rules have been applied with great success to the in-process optical testing and final specification compliance testing of the JWST mirrors.

  16. Rules for Optical Testing

    NASA Technical Reports Server (NTRS)

    Stahl, H. Philip

    2014-01-01

    Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task: Fully Understand the Task, Develop an Error Budget, Continuous Metrology Coverage, Know where you are, Test like you fly, Independent Cross-Checks, Understand All Anomalies. These rules have been applied with great success to the inprocess optical testing and final specification compliance testing of the JWST mirrors.

  17. Rules for Optical Metrology

    NASA Technical Reports Server (NTRS)

    Stahl, H. Philip

    2014-01-01

    Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task. GUIDING PRINCIPLES 1.Fully Understand the Task 2.Develop an Error Budget 3.Continuous Metrology Coverage 4.Know where you are 5. 'Test like you fly' 6.Independent Cross-Checks 7.Understand All Anomalies. These rules have been applied with great success to the in-process optical testing and final specification compliance testing of the JWST mirrors.

  18. Mechanical Engineering Department technical abstracts

    SciTech Connect

    Denney, R.M.

    1982-07-01

    The Mechanical Engineering Department publishes listings of technical abstracts twice a year to inform readers of the broad range of technical activities in the Department, and to promote an exchange of ideas. Details of the work covered by an abstract may be obtained by contacting the author(s). Overall information about current activities of each of the Department's seven divisions precedes the technical abstracts.

  19. Recursive Abstractions for Parameterized Systems

    NASA Astrophysics Data System (ADS)

    Jaffar, Joxan; Santosa, Andrew E.

    We consider a language of recursively defined formulas about arrays of variables, suitable for specifying safety properties of parameterized systems. We then present an abstract interpretation framework which translates a paramerized system as a symbolic transition system which propagates such formulas as abstractions of underlying concrete states. The main contribution is a proof method for implications between the formulas, which then provides for an implementation of this abstract interpreter.

  20. An Integrated Planning Representation Using Macros, Abstractions, and Cases

    NASA Technical Reports Server (NTRS)

    Baltes, Jacky; MacDonald, Bruce

    1992-01-01

    Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.

  1. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification §...

  2. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification §...

  3. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification §...

  4. 37 CFR 1.72 - Title and abstract.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Title and abstract. 1.72 Section 1.72 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Specification §...

  5. Abstracts

    NASA Astrophysics Data System (ADS)

    2012-09-01

    Measuring cosmological parameters with GRBs: status and perspectives New interpretation of the Amati relation The SED Machine - a dedicated transient spectrograph PTF10iue - evidence for an internal engine in a unique Type Ic SN Direct evidence for the collapsar model of long gamma-ray bursts On pair instability supernovae and gamma-ray bursts Pan-STARRS1 observations of ultraluminous SNe The influence of rotation on the critical neutrino luminosity in core-collapse supernovae General relativistic magnetospheres of slowly rotating and oscillating neutron stars Host galaxies of short GRBs GRB 100418A: a bridge between GRB-associated hypernovae and SNe Two super-luminous SNe at z ~ 1.5 from the SNLS Prospects for very-high-energy gamma-ray bursts with the Cherenkov Telescope Array The dynamics and radiation of relativistic flows from massive stars The search for light echoes from the supernova explosion of 1181 AD The proto-magnetar model for gamma-ray bursts Stellar black holes at the dawn of the universe MAXI J0158-744: the discovery of a supersoft X-ray transient Wide-band spectra of magnetar burst emission Dust formation and evolution in envelope-stripped core-collapse supernovae The host galaxies of dark gamma-ray bursts Keck observations of 150 GRB host galaxies Search for properties of GRBs at large redshift The early emission from SNe Spectral properties of SN shock breakout MAXI observation of GRBs and short X-ray transients A three-dimensional view of SN 1987A using light echo spectroscopy X-ray study of the southern extension of the SNR Puppis A All-sky survey of short X-ray transients by MAXI GSC Development of the CALET gamma-ray burst monitor (CGBM)

  6. Vague Language in Conference Abstracts

    ERIC Educational Resources Information Center

    Cutting, Joan

    2012-01-01

    This study examined abstracts for a British Association for Applied Linguistics conference and a Sociolinguistics Symposium, to define the genre of conference abstracts in terms of vague language, specifically universal general nouns (e.g. people) and research general nouns (e.g. results), and to discover if the language used reflected the level…

  7. Leadership Abstracts; Volume 4, 1991.

    ERIC Educational Resources Information Center

    Doucette, Don, Ed.

    1991-01-01

    "Leadership Abstracts" is published bimonthly and distributed to the chief executive officer of every two-year college in the United States and Canada. This document consists of the 15 one-page abstracts published in 1991. Addressing a variety of topics of interest to the community college administrators, this volume includes: (1) "Delivering the…

  8. Food Science and Technology Abstracts.

    ERIC Educational Resources Information Center

    Cohen, Elinor; Federman, Joan

    1979-01-01

    Introduces the reader to the Food Science and Technology Abstracts, a data file that covers worldwide literature on human food commodities and aspects of food processing. Topics include scope, subject index, thesaurus, searching online, and abstracts; tables provide a comparison of ORBIT and DIALOG versions of the file. (JD)

  9. Student Success with Abstract Art

    ERIC Educational Resources Information Center

    Hamidou, Kristine

    2009-01-01

    An abstract art project can be challenging or not, depending on the objectives the teacher sets up. In this article, the author describes an abstract papier-mache project that is a success for all students, and is a versatile project easily manipulated to suit the classroom of any art teacher.

  10. Multistrategy learning: A case study

    SciTech Connect

    Domingos, P.

    1996-12-31

    Two of the most popular approaches to induction are instance-based learning (IBL) and rule generation. Their strengths and weaknesses are largely complementary. IBL methods are able to identify small details in the instance space, but have trouble with attributes that are relevant in some parts of the space but not others. Conversely, rule induction methods may overlook small exception regions, but are able to select different attributes in different parts of the instance space. The two methods have been unified in the RISE algorithm. RISE views instances as maximally specific rules, forms more general rules by gradually clustering instances of the same class, and classifies a test example by letting the nearest rule win. This approach potentially combines the advantages of rule induction and IBL, and has indeed been observed to be more accurate than each on a large number of bench-mark datasets. However, it is important to determine if this performance is indeed due to the hypothesized advantages, and to define the situations in which RISE`s bias will and will not be preferable to those of the individual approaches. This abstract reports experiments to this end in artificial domains.

  11. Technical abstracts: Mechanical engineering, 1990

    SciTech Connect

    Broesius, J.Y.

    1991-03-01

    This document is a compilation of the published, unclassified abstracts produced by mechanical engineers at Lawrence Livermore National Laboratory (LLNL) during the calendar year 1990. Many abstracts summarize work completed and published in report form. These are UCRL-JC series documents, which include the full text of articles to be published in journals and of papers to be presented at meetings, and UCID reports, which are informal documents. Not all UCIDs contain abstracts: short summaries were generated when abstracts were not included. Technical Abstracts also provides descriptions of those documents assigned to the UCRL-MI (miscellaneous) category. These are generally viewgraphs or photographs presented at meetings. An author index is provided at the back of this volume for cross referencing.

  12. Metaphor: Bridging embodiment to abstraction.

    PubMed

    Jamrozik, Anja; McQuire, Marguerite; Cardillo, Eileen R; Chatterjee, Anjan

    2016-08-01

    Embodied cognition accounts posit that concepts are grounded in our sensory and motor systems. An important challenge for these accounts is explaining how abstract concepts, which do not directly call upon sensory or motor information, can be informed by experience. We propose that metaphor is one important vehicle guiding the development and use of abstract concepts. Metaphors allow us to draw on concrete, familiar domains to acquire and reason about abstract concepts. Additionally, repeated metaphoric use drawing on particular aspects of concrete experience can result in the development of new abstract representations. These abstractions, which are derived from embodied experience but lack much of the sensorimotor information associated with it, can then be flexibly applied to understand new situations. PMID:27294425

  13. How Long Does It Take to Learn a Second Language?: Applying the "10,000-Hour Rule" as a Model for Fluency

    ERIC Educational Resources Information Center

    Eaton, Sarah Elaine

    2011-01-01

    This study applies the model of expertise developed by Ericsson et al (2007) to second and foreign language learning. Ericsson et al posits that in order to achieve expertise (as they define it) requires 10,000 or longer of "intense training". Applying this model to language learning, equating an expert level of competence with fluency, various…

  14. Usage-Based vs. Rule-Based Learning: The Acquisition of Word Order in "Wh"-Questions in English and Norwegian

    ERIC Educational Resources Information Center

    Westergaard, Marit

    2009-01-01

    This paper discusses different approaches to language acquisition in relation to children's acquisition of word order in "wh"-questions in English and Norwegian. While generative models assert that children set major word order parameters and thus acquire a rule of subject-auxiliary inversion or generalized verb second (V2) at an early stage, some…

  15. NASA Patent Abstracts bibliography: A continuing bibliography. Section 1: Abstracts (supplement 21) Abstracts

    NASA Technical Reports Server (NTRS)

    1982-01-01

    Abstracts are cited for 87 patents and applications introduced into the NASA scientific and technical information system during the period of January 1982 through June 1982. Each entry consists of a citation, an abstract, and in mose cases, a key illustration selected from the patent or patent application.

  16. Teaching Abstract Concepts by Metaphor.

    ERIC Educational Resources Information Center

    Sutherland, Judith A.

    2001-01-01

    Defines metaphor and its uses; explains the construction and application of metaphors in nursing education. Describes the transformation of the abstract psychiatric concept of therapeutic milieu into a visual metaphor. (SK)

  17. Deficiencies in structured medical abstracts.

    PubMed

    Froom, P; Froom, J

    1993-07-01

    This study was carried out to determine if the content of structured abstracts conforms with recommendations of the Ad Hoc Working Group for the critical appraisal of the medical literature as adopted by the Annals of Internal Medicine. The study design was a survey. All articles published in Annals of Internal Medicine in 1991, excluding editorials, case-reports, literature reviews, decision analysis, studies in medical education, descriptive studies of clinical and basic phenomena, and papers lacking a structured abstract, were studied. Of a total of 150 articles, 20 were excluded. The abstract and text of each article were assessed for the presence of the following items; patient selection criteria, statements concerning extrapolation of findings, need for further study, and whether or not the information should be used now. Number of refusers, drop outs and reason(s) for drop outs were assessed for intervention and prospective cohort studies only. Deficiencies of assessed items were noted in both abstracts and texts. For abstracts, patient selection criteria, numbers of refusers, number of drop outs and reason(s) for drop outs were reported in 44.6% (58/130), 3.1% (4/130), 16.9% (14/83) and 2.4% (2/83) respectively. These items were reported more frequently in the texts 87.7% (114/130), 9.2% (12/130), 60.2% (50/83) and 37.3% (31/83) respectively (p < 0.05). Statements concerning extrapolation of findings, need for further study and use of information now were also more frequent in texts than abstracts (p < 0.0001). A large number of structured abstracts published in the Annals of Internal Medicine in 1991, lack information recommended by the Ad Hoc Working Group. Our findings should not be extrapolated to other journals requiring structured abstracts. PMID:8326342

  18. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

    PubMed Central

    Burbank, Kendra S.

    2015-01-01

    The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

  19. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

    PubMed

    Burbank, Kendra S

    2015-12-01

    The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

  20. Transfer of the Nonmatch-to-Goal rule in Monkeys across Cognitive Domains

    PubMed Central

    Falcone, Rossella; Bevacqua, Sara; Cerasti, Erika; Brunamonti, Emiliano; Cervelloni, Milena; Genovesio, Aldo

    2013-01-01

    To solve novel problems, it is advantageous to abstract relevant information from past experience to transfer on related problems. To study whether macaque monkeys were able to transfer an abstract rule across cognitive domains, we trained two monkeys on a nonmatch-to-goal (NMTG) task. In the object version of the task (O-NMTG), the monkeys were required to choose between two object-like stimuli, which differed either only in shape or in shape and color. For each choice, they were required to switch from their previously chosen object-goal to a different one. After they reached a performance level of over 90% correct on the O-NMTG task, the monkeys were tested for rule transfer on a spatial version of the task (S-NMTG). To receive a reward, the monkeys had to switch from their previously chosen location to a different one. In both the O-NMTG and S-NMTG tasks, there were four potential choices, presented in pairs from trial-to-trial. We found that both monkeys transferred successfully the NMTG rule within the first testing session, showing effective transfer of the learned rule between two cognitive domains. PMID:24391894

  1. Abstract concepts: data from a Grey parrot.

    PubMed

    Pepperberg, Irene M

    2013-02-01

    Do humans and nonhumans share the ability to form abstract concepts? Until the 1960s, many researchers questioned whether avian subjects could form categorical constructs, much less more abstract formulations, including concepts such as same-different or exact understanding of number. Although ethologists argued that nonhumans, including birds, had to have some understanding of divisions such as prey versus predator, mate versus nonmate, food versus nonfood, or basic relational concepts such as more versus less, simply in order to survive, no claims were made that these abilities reflected cognitive processes, and little formal data from psychology laboratories could initially support such claims. Researchers like Anthony Wright, however, succeeded in obtaining such data and inspired many others to pursue these topics, with the eventual result that several avian species are now considered "feathered primates" in terms of cognitive processes. Here I review research on numerical concepts in the Gray parrot (Psittacus erithacus), demonstrating that at least one subject, Alex, understood number symbols as abstract representations of real-world collections, in ways comparing favorably to those of apes and young human children. He not only understood such concepts, but also appeared to learn them in ways more similar to humans than to apes. PMID:23089384

  2. Abstract context representations in primate amygdala and prefrontal cortex

    PubMed Central

    Saez, A.; Rigotti, M.; Ostojic, S.; Fusi, S.; Salzman, C. D.

    2015-01-01

    Summary Neurons in prefrontal cortex (PFC) encode rules, goals and other abstract information thought to underlie cognitive, emotional, and behavioral flexibility. Here we show that the amygdala, a brain area traditionally thought to mediate emotions, also encodes abstract information that could underlie this flexibility. Monkeys performed a task in which stimulus-reinforcement contingencies varied between two sets of associations, each defining a context. Reinforcement prediction required identifying a stimulus and knowing the current context. Behavioral evidence indicated that monkeys utilized this information to perform inference and adjust their behavior. Neural representations in both amygdala and PFC reflected the linked sets of associations implicitly defining each context, a process requiring a level of abstraction characteristic of cognitive operations. Surprisingly, when errors were made, the context signal weakened substantially in the amygdala. These data emphasize the importance of maintaining abstract cognitive information in the amygdala to support flexible behavior. PMID:26291167

  3. Abstract Context Representations in Primate Amygdala and Prefrontal Cortex.

    PubMed

    Saez, A; Rigotti, M; Ostojic, S; Fusi, S; Salzman, C D

    2015-08-19

    Neurons in prefrontal cortex (PFC) encode rules, goals, and other abstract information thought to underlie cognitive, emotional, and behavioral flexibility. Here we show that the amygdala, a brain area traditionally thought to mediate emotions, also encodes abstract information that could underlie this flexibility. Monkeys performed a task in which stimulus-reinforcement contingencies varied between two sets of associations, each defining a context. Reinforcement prediction required identifying a stimulus and knowing the current context. Behavioral evidence indicated that monkeys utilized this information to perform inference and adjust their behavior. Neural representations in both amygdala and PFC reflected the linked sets of associations implicitly defining each context, a process requiring a level of abstraction characteristic of cognitive operations. Surprisingly, when errors were made, the context signal weakened substantially in the amygdala. These data emphasize the importance of maintaining abstract cognitive information in the amygdala to support flexible behavior. PMID:26291167

  4. Modelling Metamorphism by Abstract Interpretation

    NASA Astrophysics Data System (ADS)

    Dalla Preda, Mila; Giacobazzi, Roberto; Debray, Saumya; Coogan, Kevin; Townsend, Gregg M.

    Metamorphic malware apply semantics-preserving transformations to their own code in order to foil detection systems based on signature matching. In this paper we consider the problem of automatically extract metamorphic signatures from these malware. We introduce a semantics for self-modifying code, later called phase semantics, and prove its correctness by showing that it is an abstract interpretation of the standard trace semantics. Phase semantics precisely models the metamorphic code behavior by providing a set of traces of programs which correspond to the possible evolutions of the metamorphic code during execution. We show that metamorphic signatures can be automatically extracted by abstract interpretation of the phase semantics, and that regular metamorphism can be modelled as finite state automata abstraction of the phase semantics.

  5. Mechanical Engineering Department technical abstracts

    SciTech Connect

    Not Available

    1984-07-01

    The Mechanical Engineering Department publishes abstracts twice a year to inform readers of the broad range of technical activities in the Department, and to promote an exchange of ideas. Details of the work covered by an abstract may be obtained by contacting the author(s). General information about the current role and activities of each of the Department's seven divisions precedes the technical abstracts. Further information about a division's work may be obtained from the division leader, whose name is given at the end of each divisional summary. The Department's seven divisions are as follows: Nuclear Test Engineering Division, Nuclear Explosives Engineering Division, Weapons Engineering Division, Energy Systems Engineering Division, Engineering Sciences Division, Magnetic Fusion Engineering Division and Materials Fabrication Division.

  6. Meeting Abstracts - Annual Meeting 2016.

    PubMed

    2016-04-01

    The AMCP Abstracts program provides a forum through which authors can share their insights and outcomes of advanced managed care practice through publication in AMCP's Journal of Managed Care & Specialty Pharmacy (JMCP). Most of the reviewed and unreviewed abstracts are presented as posters so that interested AMCP meeting attendees can review findings and query authors. The Student/Resident/ Fellow poster presentation (unreviewed) is Wednesday, April 20, 2016, and the Professional poster presentation (reviewed) is Thursday, April 21. The Professional posters will also be displayed on Friday, April 22. The reviewed abstracts are published in the JMCP Meeting Abstracts supplement. The AMCP Managed Care & Specialty Pharmacy Annual Meeting 2016 in San Francisco, California, is expected to attract more than 3,500 managed care pharmacists and other health care professionals who manage and evaluate drug therapies, develop and manage networks, and work with medical managers and information specialists to improve the care of all individuals enrolled in managed care programs. Abstracts were submitted in the following categories: Research Report: describe completed original research on managed care pharmacy services or health care interventions. Examples include (but are not limited to) observational studies using administrative claims, reports of the impact of unique benefit design strategies, and analyses of the effects of innovative administrative or clinical programs. Economic Model: describe models that predict the effect of various benefit design or clinical decisions on a population. For example, an economic model could be used to predict the budget impact of a new pharmaceutical product on a health care system. Solving Problems in Managed Care: describe the specific steps taken to introduce a needed change, develop and implement a new system or program, plan and organize an administrative function, or solve other types of problems in managed care settings. These

  7. Abstract communication for coordinated planning

    NASA Technical Reports Server (NTRS)

    Clement, Bradley J.; Durfee, Edmund H.

    2003-01-01

    work offers evidence that distributed planning agents can greatly reduce communication costs by reasoning at abstract levels. While it is intuitive that improved search can reduce communication in such cases, there are other decisions about how to communicate plan information that greatly affect communication costs. This paper identifies cases independent of search where communicating at multiple levels of abstraction can exponentially decrease costs and where it can exponentially add costs. We conclude with a process for determining appropriate levels of communication based on characteristics of the domain.

  8. Bridging History of the Concept of Function with Learning of Mathematics: Students' Meta-Discursive Rules, Concept Formation and Historical Awareness

    ERIC Educational Resources Information Center

    Kjeldsen, Tinne Hoff; Petersen, Pernille Hviid

    2014-01-01

    In this paper we present a matrix-organised implementation of an experimental course in the history of the concept of a function. The course was implemented in a Danish high school. One of the aims was to bridge history of mathematics with the teaching and learning of mathematics. The course was designed using the theoretical frameworks of a…

  9. Learning the Rules of the Game: The Nature of Game and Classroom Supports When Using a Concept-Integrated Digital Physics Game in the Middle School Science Classroom

    ERIC Educational Resources Information Center

    Stewart, Phillip Michael, Jr.

    2013-01-01

    Games in science education is emerging as a popular topic of scholarly inquiry. The National Research Council recently published a report detailing a research agenda for games and science education entitled "Learning Science Through Computer Games and Simulations" (2011). The report recommends moving beyond typical proof-of-concept…

  10. Handedness Shapes Children's Abstract Concepts

    ERIC Educational Resources Information Center

    Casasanto, Daniel; Henetz, Tania

    2012-01-01

    Can children's handedness influence how they represent abstract concepts like "kindness" and "intelligence"? Here we show that from an early age, right-handers associate rightward space more strongly with positive ideas and leftward space with negative ideas, but the opposite is true for left-handers. In one experiment, children indicated where on…

  11. Abstract Journal Concept Being Examined

    ERIC Educational Resources Information Center

    Somerville, Brendan F.

    1972-01-01

    In order to control the information explosion, some European chemical groups are studying the idea of abandoning full publication in printed form of all primary journals and, in their place, substituting a new form of abstract journal combined with a microfilm record of full scientific papers. (Author/CP)

  12. Metaphoric Images from Abstract Concepts.

    ERIC Educational Resources Information Center

    Vizmuller-Zocco, Jana

    1992-01-01

    Discusses children's use of metaphors to create meaning, using as an example the pragmatic and "scientific" ways in which preschool children explain thunder and lightning to themselves. Argues that children are being shortchanged by modern scientific notions of abstractness and that they should be encouraged to create their own explanations of…

  13. ERGONOMICS ABSTRACTS 48347-48982.

    ERIC Educational Resources Information Center

    Ministry of Technology, London (England). Warren Spring Lab.

    IN THIS COLLECTION OF ERGONOMICS ABSTRACTS AND ANNOTATIONS THE FOLLOWING AREAS OF CONCERN ARE REPRESENTED--GENERAL REFERENCES, METHODS, FACILITIES, AND EQUIPMENT RELATING TO ERGONOMICS, SYSTEMS OF MAN AND MACHINES, VISUAL, AUDITORY, AND OTHER SENSORY INPUTS AND PROCESSES (INCLUDING SPEECH AND INTELLIGIBILITY), INPUT CHANNELS, BODY MEASUREMENTS,…

  14. Does "Social Work Abstracts" Work?

    ERIC Educational Resources Information Center

    Holden, Gary; Barker, Kathleen; Covert-Vail, Lucinda; Rosenberg, Gary; Cohen, Stephanie A.

    2008-01-01

    Objective: The current study seeks to provide estimates of the adequacy of journal coverage in the Social Work Abstracts (SWA) database. Method: A total of 23 journals listed in the Journal Citation Reports social work category during the 1997 to 2005 period were selected for study. Issue-level coverage estimates were obtained for SWA and…

  15. Manpower Management Studies: Selected Abstracts.

    ERIC Educational Resources Information Center

    Ryerson, William R., Comp.

    This bibliography contains 58 selected abstracts of research reports dating back to 1964 on the general subject of manpower management. It was prepared from a search of the National Technical Information Service data base of more than 300,000 documents submitted by agencies of the Federal Government and also by private organizations or individuals…

  16. The Theatre Audience: An Abstraction.

    ERIC Educational Resources Information Center

    Campbell, Paul Newell

    1981-01-01

    Argues that theater is aimed at and presented to an ideal or abstract audience. Discusses the implications of performing for an actual audience, adaptation to various audiences, and the concept of the audience as an evaluative device. (See CS 705 536.) (JMF)

  17. Chemical Abstracts' Document Delivery Service.

    ERIC Educational Resources Information Center

    Rollins, Stephen

    1984-01-01

    The Document Delivery Service offered by Chemical Abstracts is described in terms of the DIALORDER option on the Dialog information retrieval system, mail requests, and requests transmitted through OCLC's Interlibrary Loan system. Transmission costs, success rates, delivery rates, and other considerations in utilizing the service are included.…

  18. Brain Research: Implications for the Education of Exceptional Children. Abstract XV: Research & Resources on Special Education.

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Handicapped and Gifted Children, Reston, VA.

    The one-page abstract summarizes "Brain Research: Implications for the Education of Exceptional Children," an ERIC Computer Search Reprint containing bibliographic information and abstracts of 115 documents. Citations are described in five sections: learning disabilities, autism, other learning handicaps, assessment techniques, and instructional…

  19. Learning the Rules of the Game: The Nature of Game and Classroom Supports When Using a Concept-Integrated Digital Physics Game in the Middle School Science Classroom

    NASA Astrophysics Data System (ADS)

    Stewart, Phillip Michael, Jr.

    Games in science education is emerging as a popular topic of scholarly inquiry. The National Research Council recently published a report detailing a research agenda for games and science education entitled Learning Science Through Computer Games and Simulations (2011). The report recommends moving beyond typical proof-of-concept studies into more exploratory and theoretically-based work to determine how best to integrate games into K-12 classrooms for learning , as well as how scaffolds from within the game and from outside the game (from peers and teachers) support the learning of applicable science. This study uses a mixed-methods, quasi-experimental design with an 8th grade class at an independent school in southern Connecticut to answer the following questions: 1. What is the nature of the supports for science content learning provided by the game, the peer, and the teacher, when the game is used in a classroom setting? 2. How do the learning gains in the peer support condition compare to the solo play condition, both qualitatively and quantitatively? The concept-integrated physics game SURGE (Scaffolding Understanding through Redesigning Games for Education) was selected for this study, as it was developed with an ear towards specific learning theories and prior work on student understandings of impulse, force, and vectors. Stimulated recall interviews and video observations served as the primary sources and major patterns emerged through the triangulation of data sources and qualitative analysis in the software QSR NVivo 9. The first pattern which emerged indicated that scaffolding from within the game and outside the game requires a pause in game action to be effective, unless that scaffolding is directly useful to the player in the moment of action. The second major pattern indicated that both amount and type of prior gaming experience has somewhat complex effects on both the uses of supports and learning outcomes. In general, a high correlation was found

  20. FeynRules - Feynman rules made easy

    NASA Astrophysics Data System (ADS)

    Christensen, Neil D.; Duhr, Claude

    2009-09-01

    In this paper we present FeynRules, a new Mathematica package that facilitates the implementation of new particle physics models. After the user implements the basic model information ( e.g., particle content, parameters and Lagrangian), FeynRules derives the Feynman rules and stores them in a generic form suitable for translation to any Feynman diagram calculation program. The model can then be translated to the format specific to a particular Feynman diagram calculator via FeynRules translation interfaces. Such interfaces have been written for CalcHEP/CompHEP, FeynArts/FormCalc, MadGraph/MadEvent and Sherpa, making it possible to write a new model once and have it work in all of these programs. In this paper, we describe how to implement a new model, generate the Feynman rules, use a generic translation interface, and write a new translation interface. We also discuss the details of the FeynRules code.

  1. An Abstract Plan Preparation Language

    NASA Technical Reports Server (NTRS)

    Butler, Ricky W.; Munoz, Cesar A.

    2006-01-01

    This paper presents a new planning language that is more abstract than most existing planning languages such as the Planning Domain Definition Language (PDDL) or the New Domain Description Language (NDDL). The goal of this language is to simplify the formal analysis and specification of planning problems that are intended for safety-critical applications such as power management or automated rendezvous in future manned spacecraft. The new language has been named the Abstract Plan Preparation Language (APPL). A translator from APPL to NDDL has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats Project (SAVH) sponsored by the Explorations Technology Development Program, which is seeking to mature autonomy technology for application to the new Crew Exploration Vehicle (CEV) that will replace the Space Shuttle.

  2. Cryogenic foam insulation: Abstracted publications

    NASA Technical Reports Server (NTRS)

    Williamson, F. R.

    1977-01-01

    A group of documents were chosen and abstracted which contain information on the properties of foam materials and on the use of foams as thermal insulation at cryogenic temperatures. The properties include thermal properties, mechanical properties, and compatibility properties with oxygen and other cryogenic fluids. Uses of foams include applications as thermal insulation for spacecraft propellant tanks, and for liquefied natural gas storage tanks and pipelines.

  3. Mental Ability and Mismatch Negativity: Pre-Attentive Discrimination of Abstract Feature Conjunctions in Auditory Sequences

    ERIC Educational Resources Information Center

    Houlihan, Michael; Stelmack, Robert M.

    2012-01-01

    The relation between mental ability and the ability to detect violations of an abstract, third-order conjunction rule was examined using event-related potential measures, specifically mismatch negativity (MMN). The primary objective was to determine whether the extraction of invariant relations based on abstract conjunctions between two…

  4. Concrete and abstract Voronoi diagrams

    SciTech Connect

    Klein, R. )

    1989-01-01

    The Voronoi diagram of a set of sites is a partition of the plane into regions, one to each site, such that the region of each site contains all points of the plane that are closer to this site than to the other ones. Such partitions are of great importance to computer science and many other fields. The challenge is to compute Voronoi diagrams quickly. The problem is that their structure depends on the notion of distance and the sort of site. In this book the author proposes a unifying approach by introducing abstract Voronoi diagrams. These are based on the concept of bisecting curves which are required to have some simple properties that are actually possessed by most bisectors of concrete Voronoi diagrams. Abstract Voronoi diagrams can be computed efficiently and there exists a worst-case efficient algorithm of divide-and-conquer type that applies to all abstract Voronoi diagrams satisfying a certain constraint. The author shows that this constraint is fulfilled by the concrete diagrams based no large classes of metrics in the plane.

  5. Innovation Abstracts, Vol. IX, No. 1-28.

    ERIC Educational Resources Information Center

    Roueche, Suanne D., Ed.

    1987-01-01

    This series of one- and two-page abstracts highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the articles include the use of Hollywood films as a tool for teaching history; displaced homemaker programs; the relationship between teaching and scholarship; helping students write for the…

  6. Representations of Abstract Grammatical Feature Agreement in Young Children

    ERIC Educational Resources Information Center

    Melançon, Andréane; Shi, Rushen

    2015-01-01

    A fundamental question in language acquisition research is whether young children have abstract grammatical representations. We tested this question experimentally. French-learning 30-month-olds were first taught novel word-object pairs in the context of a gender-marked determiner (e.g., un[subscript MASC]ravole "a ravole"). Test trials…

  7. Non-Traditional Methods of Teaching Abstract Algebra

    ERIC Educational Resources Information Center

    Capaldi, Mindy

    2014-01-01

    This article reports on techniques of teaching abstract algebra which were developed to achieve multiple student objectives: reasoning and communication skills, deep content knowledge, student engagement, independence, and pride. The approach developed included a complementary combination of inquiry-based learning, individual (not group) homework…

  8. Development: Ages & Stages--How Abstract Thinking Develops

    ERIC Educational Resources Information Center

    Poole, Carla; Miller, Susan A.; Church, Ellen Booth

    2005-01-01

    Babies are active participants in their learning and need to explore a variety of objects. Nurturing relationships support these explorations. Objects are more clearly remembered and understood. Thus, one activity this article suggests doing with a 12-month-old to encourage abstract thinking, is talking about how squeezing the bottle of ketchup…

  9. Functional Neuroanatomy of Contextual Acquisition of Concrete and Abstract Words

    ERIC Educational Resources Information Center

    Mestres-Misse, Anna; Munte, Thomas F.; Rodriguez-Fornells, Antoni

    2009-01-01

    The meaning of a novel word can be acquired by extracting it from linguistic context. Here we simulated word learning of new words associated to concrete and abstract concepts in a variant of the human simulation paradigm that provided linguistic context information in order to characterize the brain systems involved. Native speakers of Spanish…

  10. Promoting Early Abstraction to Promote Early Literacy and Numeracy

    ERIC Educational Resources Information Center

    Pasnak, Robert; Kidd, Julie K.; Gadzichowski, Marinka K.; Gallington, Debbie A.; Saracina, Robin P.; Addison, Katherine T.

    2009-01-01

    A learning-set procedure was used to teach the oddity principle, insertions into series, and number conservation to 85 kindergarten children who did not grasp these abstractions. Control groups were given lessons in kindergarten literacy, numeracy, or art in sessions matched in timing and extent. The children who were taught the principles of…

  11. Youth Studies Abstracts. Vol. 4 No. 3.

    ERIC Educational Resources Information Center

    Youth Studies Abstracts, 1985

    1985-01-01

    This volume contains 169 abstracts of documents dealing with youth and educational programs for youth. Included in the volume are 97 abstracts of documents dealing with social and educational developments; 56 abstracts of program reports, reviews, and evaluations; and 16 abstracts of program materials. Abstracts are grouped according to the…

  12. Discrimination theory of rule-governed behavior

    PubMed Central

    Cerutti, Daniel T.

    1989-01-01

    In rule-governed behavior, previously established elementary discriminations are combined in complex instructions and thus result in complex behavior. Discriminative combining and recombining of responses produce behavior with characteristics differing from those of behavior that is established through the effects of its direct consequences. For example, responding in instructed discrimination may be occasioned by discriminative stimuli that are temporally and situationally removed from the circumstances under which the discrimination is instructed. The present account illustrates properties of rule-governed behavior with examples from research in instructional control and imitation learning. Units of instructed behavior, circumstances controlling compliance with instructions, and rule-governed problem solving are considered. PMID:16812579

  13. From Abstract to Concrete Norms in Agent Institutions

    NASA Technical Reports Server (NTRS)

    Grossi, Davide; Dignum, Frank

    2004-01-01

    Norms specifying constraints over institutions are stated in such a form that allows them to regulate a wide range of situations over time without need for modification. To guarantee this stability, the formulation of norms need to abstract from a variety of concrete aspects, which are instead relevant for the actual operationalization of institutions. If agent institutions are to be built, which comply with a set of abstract requirements, how can those requirements be translated in more concrete constraints the impact of which can be described directly in the institution? In this work we make use of logical methods in order to provide a formal characterization of the translation rules that operate the connection between abstract and concrete norms. On the basis of this characterization, a comprehensive formalization of the notion of institution is also provided.

  14. Rule Breaking in the Child Care Centre: Tensions for Children and Teachers

    ERIC Educational Resources Information Center

    Brennan, Margaret

    2016-01-01

    Research suggests that young children transgress conventional rules in every culture and society. In this article, the argument is made that rule teaching and learning provide insight into how children learn to be part of a group. The research question addressed is, "Why do some children transgress the rules if their actions risk jeopardising…

  15. Operating System Abstraction Layer (OSAL)

    NASA Technical Reports Server (NTRS)

    Yanchik, Nicholas J.

    2007-01-01

    This viewgraph presentation reviews the concept of the Operating System Abstraction Layer (OSAL) and its benefits. The OSAL is A small layer of software that allows programs to run on many different operating systems and hardware platforms It runs independent of the underlying OS & hardware and it is self-contained. The benefits of OSAL are that it removes dependencies from any one operating system, promotes portable, reusable flight software. It allows for Core Flight software (FSW) to be built for multiple processors and operating systems. The presentation discusses the functionality, the various OSAL releases, and describes the specifications.

  16. IEEE conference record--Abstracts

    SciTech Connect

    Not Available

    1992-01-01

    The following topics were covered in this meeting: basic plasma phenomena and plasma waves; plasma diagnostics; space plasma diagnostics; magnetic fusion; electron, ion and plasma sources; intense electron and ion beams; intense beam microwaves; fast wave M/W devices; microwave plasma interactions; plasma focus; ultrafast Z-pinches; plasma processing; electrical gas discharges; fast opening switches; magnetohydrodynamics; electromagnetic and electrothermal launchers; x-ray lasers; computational plasma science; solid state plasmas and switches; environmental/energy issues in plasma science; vacuum electronics; plasmas for lighting; gaseous electronics; and ball lightning and other spherical plasmas. Separate abstracts were prepared for 278 papers of this conference.

  17. Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning.

    PubMed

    ten Cate, Carel; Okanoya, Kazuo

    2012-07-19

    The domain of syntax is seen as the core of the language faculty and as the most critical difference between animal vocalizations and language. We review evidence from spontaneously produced vocalizations as well as from perceptual experiments using artificial grammars to analyse animal syntactic abilities, i.e. abilities to produce and perceive patterns following abstract rules. Animal vocalizations consist of vocal units (elements) that are combined in a species-specific way to create higher order strings that in turn can be produced in different patterns. While these patterns differ between species, they have in common that they are no more complex than a probabilistic finite-state grammar. Experiments on the perception of artificial grammars confirm that animals can generalize and categorize vocal strings based on phonetic features. They also demonstrate that animals can learn about the co-occurrence of elements or learn simple 'rules' like attending to reduplications of units. However, these experiments do not provide strong evidence for an ability to detect abstract rules or rules beyond finite-state grammars. Nevertheless, considering the rather limited number of experiments and the difficulty to design experiments that unequivocally demonstrate more complex rule learning, the question of what animals are able to do remains open. PMID:22688634

  18. Neural networks supporting switching, hypothesis testing, and rule application.

    PubMed

    Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S; Seger, Carol A

    2015-10-01

    We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example "choose the blue letter". Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest

  19. Phonological reduplication in sign language: Rules rule

    PubMed Central

    Berent, Iris; Dupuis, Amanda; Brentari, Diane

    2014-01-01

    Productivity—the hallmark of linguistic competence—is typically attributed to algebraic rules that support broad generalizations. Past research on spoken language has documented such generalizations in both adults and infants. But whether algebraic rules form part of the linguistic competence of signers remains unknown. To address this question, here we gauge the generalization afforded by American Sign Language (ASL). As a case study, we examine reduplication (X→XX)—a rule that, inter alia, generates ASL nouns from verbs. If signers encode this rule, then they should freely extend it to novel syllables, including ones with features that are unattested in ASL. And since reduplicated disyllables are preferred in ASL, such a rule should favor novel reduplicated signs. Novel reduplicated signs should thus be preferred to nonreduplicative controls (in rating), and consequently, such stimuli should also be harder to classify as nonsigns (in the lexical decision task). The results of four experiments support this prediction. These findings suggest that the phonological knowledge of signers includes powerful algebraic rules. The convergence between these conclusions and previous evidence for phonological rules in spoken language suggests that the architecture of the phonological mind is partly amodal. PMID:24959158

  20. Improving drivers' knowledge of road rules using digital games.

    PubMed

    Li, Qing; Tay, Richard

    2014-04-01

    Although a proficient knowledge of the road rules is important to safe driving, many drivers do not retain the knowledge acquired after they have obtained their licenses. Hence, more innovative and appealing methods are needed to improve drivers' knowledge of the road rules. This study examines the effect of game based learning on drivers' knowledge acquisition and retention. We find that playing an entertaining game that is designed to impart knowledge of the road rules not only improves players' knowledge but also helps them retain such knowledge. Hence, learning by gaming appears to be a promising learning approach for driver education. PMID:24384385

  1. Abstract Expression Grammar Symbolic Regression

    NASA Astrophysics Data System (ADS)

    Korns, Michael F.

    This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.

  2. Toward Millimagnitude Photometric Calibration (Abstract)

    NASA Astrophysics Data System (ADS)

    Dose, E.

    2014-12-01

    (Abstract only) Asteroid roation, exoplanet transits, and similar measurements will increasingly call for photometric precisions better than about 10 millimagnitudes, often between nights and ideally between distant observers. The present work applies detailed spectral simulations to test popular photometric calibration practices, and to test new extensions of these practices. Using 107 synthetic spectra of stars of diverse colors, detailed atmospheric transmission spectra computed by solar-energy software, realistic spectra of popular astronomy gear, and the option of three sources of noise added at realistic millimagnitude levels, we find that certain adjustments to current calibration practices can help remove small systematic errors, especially for imperfect filters, high airmasses, and possibly passing thin cirrus clouds.

  3. Abstraction Planning in Real Time

    NASA Technical Reports Server (NTRS)

    Washington, Richard

    1994-01-01

    When a planning agent works in a complex, real-world domain, it is unable to plan for and store all possible contingencies and problem situations ahead of time. The agent needs to be able to fall back on an ability to construct plans at run time under time constraints. This thesis presents a method for planning at run time that incrementally builds up plans at multiple levels of abstraction. The plans are continually updated by information from the world, allowing the planner to adjust its plan to a changing world during the planning process. All the information is represented over intervals of time, allowing the planner to reason about durations, deadlines, and delays within its plan. In addition to the method, the thesis presents a formal model of the planning process and uses the model to investigate planning strategies. The method has been implemented, and experiments have been run to validate the overall approach and the theoretical model.

  4. Abstraction Planning in Real Time

    NASA Technical Reports Server (NTRS)

    Washington, R.

    1994-01-01

    When a planning agent works in a complex, real-world domain, it is unable to plan for and store all possible contingencies and problem situations ahead of time. This thesis presents a method for planning a run time that incrementally builds up plans at multiple levels of abstraction. The plans are continually updated by information from the world, allowing the planner to adjust its plan to a changing world during the planning process. All the information is represented over intervals of time, allowing the planner to reason about durations, deadlines, and delays within its plan. In addition to the method, the thesis presents a formal model of the planning process and uses the model to investigate planning strategies.

  5. Modifying Intramural Rules.

    ERIC Educational Resources Information Center

    Rokosz, Francis M.

    1981-01-01

    Standard sports rules can be altered to improve the game for intramural participants. These changes may improve players' attitudes, simplify rules for officials, and add safety features to a game. Specific rule modifications are given for volleyball, football, softball, floor hockey, basketball, and soccer. (JN)

  6. Two Rules for Communication

    ERIC Educational Resources Information Center

    Hamilton, Mark R.

    2005-01-01

    One of the most important and most difficult skills of academic leadership is communication. In this column, the author defines what he considers to be the two most important rules for communication. The first rule, which he terms the "Great American Rule," involves trusting that the person on the other end of the line or the fax or the e-mail is…

  7. A Better Budget Rule

    ERIC Educational Resources Information Center

    Dothan, Michael; Thompson, Fred

    2009-01-01

    Debt limits, interest coverage ratios, one-off balanced budget requirements, pay-as-you-go rules, and tax and expenditure limits are among the most important fiscal rules for constraining intertemporal transfers. There is considerable evidence that the least costly and most effective of such rules are those that focus directly on the rate of…

  8. English Language Arts Skills and Instruction: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," July through December 1981 (Vol. 42 Nos. 1 through 6).

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

    This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 36 titles deal with a variety of topics, including the following: (1) distancing in young children's stories; (2) the effects of verbal and visual elaborations on the learning of abstract concepts; (3) the effects of underlined…

  9. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

    PubMed

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing. PMID:26627568

  10. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    SciTech Connect

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  11. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  12. The acquisition of abstract words by young infants.

    PubMed

    Bergelson, Elika; Swingley, Daniel

    2013-06-01

    Young infants' learning of words for abstract concepts like 'all gone' and 'eat,' in contrast to their learning of more concrete words like 'apple' and 'shoe,' may follow a relatively protracted developmental course. We examined whether infants know such abstract words. Parents named one of two events shown in side-by-side videos while their 6-16-month-old infants (n=98) watched. On average, infants successfully looked at the named video by 10 months, but not earlier, and infants' looking at the named referent increased robustly at around 14 months. Six-month-olds already understand concrete words in this task (Bergelson & Swingley, 2012). A video-corpus analysis of unscripted mother-infant interaction showed that mothers used the tested abstract words less often in the presence of their referent events than they used concrete words in the presence of their referent objects. We suggest that referential uncertainty in abstract words' teaching conditions may explain the later acquisition of abstract than concrete words, and we discuss the possible role of changes in social-cognitive abilities over the 6-14 month period. PMID:23542412

  13. When felids and hominins ruled at Olduvai Gorge: A machine learning analysis of the skeletal profiles of the non-anthropogenic Bed I sites

    NASA Astrophysics Data System (ADS)

    Arriaza, Mari Carmen; Domínguez-Rodrigo, Manuel

    2016-05-01

    In the past twenty years, skeletal part profiles, which are prone to equifinality, have not occupied a prominent role in the interpretation of early Pleistocene sites on Africa. Alternatively, taphonomic studies on bone surface modifications and bone breakage patterns, have provided heuristic interpretations of some of the best preserved archaeological record of this period; namely, the Olduvai Bed I sites. The most recent and comprehensive taphonomic study of these sites (Domínguez-Rodrigo et al., 2007a) showed that FLK Zinj was an anthropogenic assemblage in which hominins acquired carcasses via primary access. That study also showed that the other sites were palimpsests with minimal or no intervention by hominins. The FLK N, FLK NN and DK sequence seemed to be dominated by single-agent (mostly, felid) or multiple-agent (mostly, felid-hyenid) processes. The present study re-analyzes the Bed I sites focusing on skeletal part profiles. Machine learning methods, which incorporate complex algorithms, are powerful predictive and classification methods and have the potential to better extract information from skeletal part representation than past approaches. Here, multiple algorithms (via decision trees, neural networks, random forests and support vector machines) are combined to produce a solid interpretation of bone accumulation agency at the Olduvai Bed I sites. This new approach virtually coincides with previous taphonomic interpretations on a site by site basis and shows that felids were dominant accumulating agents over hyenas during Bed I times. The recent discovery of possibly a modern lion-accumulated assemblage at Olduvai Gorge (Arriaza et al., submitted) provides a very timely analog for this interpretation.

  14. Extended abstracts: Ninth battery and electrochemical contractors' conference

    SciTech Connect

    Not Available

    1989-11-01

    This document contains the extended abstracts for presentations scheduled for the Ninth Battery and Electrochemical Contractors' Conference, highlighting research supporting by the US Department of Energy and the Electric Power Research Institute. It is intended to be a technical overview for engineers and scientists in government, industry, and academia who are interested in learning more about electrochemical energy storage. The abstracts are grouped according to the following technical sessions: Introductory Session; Sodium/Sulfur Battery Development; Planning, Analysis, and Technology Transfer; Fuel Cells; Zinc/Bromine Battery Development; Aqueous Battery Development; Non-Aqueous Batteries; Battery Testing and Evaluation; and Metal/Air Batteries.

  15. Attentional effects on rule extraction and consolidation from speech.

    PubMed

    López-Barroso, Diana; Cucurell, David; Rodríguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2016-07-01

    Incidental learning plays a crucial role in the initial phases of language acquisition. However the knowledge derived from implicit learning, which is based on prediction-based mechanisms, may become explicit. The role that attention plays in the formation of implicit and explicit knowledge of the learned material is unclear. In the present study, we investigated the role that attention plays in the acquisition of non-adjacent rule learning from speech. In addition, we also tested whether the amount of attention during learning changes the representation of the learned material after a 24h delay containing sleep. For that, we developed an experiment run on two consecutive days consisting on the exposure to an artificial language that contained non-adjacent dependencies (rules) between words whereas different conditions were established to manipulate the amount of attention given to the rules (target and non-target conditions). Furthermore, we used both indirect and direct measures of learning that are more sensitive to implicit and explicit knowledge, respectively. Whereas the indirect measures indicated that learning of the rules occurred regardless of attention, more explicit judgments after learning showed differences in the type of learning reached under the two attention conditions. 24 hours later, indirect measures showed no further improvements during additional language exposure and explicit judgments indicated that only the information more robustly learned in the previous day, was consolidated. PMID:27031495

  16. Attentional effects on rule extraction and consolidation from speech

    PubMed Central

    López-Barroso, Diana; Cucurell, David; Rodríguez-Fornells, Antoni; de Diego-Balaguer, Ruth

    2016-01-01

    Incidental learning plays a crucial role in the initial phases of language acquisition. However the knowledge derived from implicit learning, which is based on prediction-based mechanisms, may become explicit. The role that attention plays in the formation of implicit and explicit knowledge of the learned material is unclear. In the present study, we investigated the role that attention plays in the acquisition of non-adjacent rule learning from speech. In addition, we also tested whether the amount of attention during learning changes the representation of the learned material after a 24 h delay containing sleep. For that, we developed an experiment run on two consecutive days consisting on the exposure to an artificial language that contained non-adjacent dependencies (rules) between words whereas different conditions were established to manipulate the amount of attention given to the rules (target and non-target conditions). Furthermore, we used both indirect and direct measures of learning that are more sensitive to implicit and explicit knowledge, respectively. Whereas the indirect measures indicated that learning of the rules occurred regardless of attention, more explicit judgments after learning showed differences in the type of learning reached under the two attention conditions. 24 hours later, indirect measures showed no further improvements during additional language exposure and explicit judgments indicated that only the information more robustly learned in the previous day, was consolidated. PMID:27031495

  17. Early object rule acquisition.

    PubMed

    Pierce, D E

    1991-05-01

    The purpose of this study was to generate a grounded theory of early object rule acquisition. The grounded theory approach and computer coding were used to analyze videotaped samples of an infant's and a toddler's independent object play, which produced the categories descriptive of three primary types of object rules; rules of object properties, rules of object action, and rules of object affect. This occupational science theory offers potential for understanding the role of objects in human occupations, for development of instruments, and for applications in occupational therapy early intervention. PMID:2048625

  18. Learning to learn about uncertain feedback.

    PubMed

    Faraut, Maïlys C M; Procyk, Emmanuel; Wilson, Charles R E

    2016-02-01

    Unexpected outcomes can reflect noise in the environment or a change in the current rules. We should ignore noise but shift strategy after rule changes. How we learn to do this is unclear, but one possibility is that it relies on learning to learn in uncertain environments. We propose that acquisition of latent task structure during learning to learn, even when not necessary, is crucial. We report results consistent with this hypothesis. Macaque monkeys acquired adaptive responses to feedback while learning to learn serial stimulus-response associations with probabilistic feedback. Monkeys learned well, decreasing their errors to criterion, but they also developed an apparently nonadaptive reactivity to unexpected stochastic feedback, even though that unexpected feedback never predicted problem switch. This surprising learning trajectory permitted the same monkeys, naïve to relearning about previously learned stimuli, to transfer to a task of stimulus-response remapping at immediately asymptotic levels. Our results suggest that learning new problems in a stochastic environment promotes the acquisition of performance rules from latent task structure, providing behavioral flexibility. Learning to learn in a probabilistic and volatile environment thus appears to induce latent learning that may be beneficial to flexible cognition. PMID:26787780

  19. An abstract approach to music.

    SciTech Connect

    Kaper, H. G.; Tipei, S.

    1999-04-19

    In this article we have outlined a formal framework for an abstract approach to music and music composition. The model is formulated in terms of objects that have attributes, obey relationships, and are subject to certain well-defined operations. The motivation for this approach uses traditional terms and concepts of music theory, but the approach itself is formal and uses the language of mathematics. The universal object is an audio wave; partials, sounds, and compositions are special objects, which are placed in a hierarchical order based on time scales. The objects have both static and dynamic attributes. When we realize a composition, we assign values to each of its attributes: a (scalar) value to a static attribute, an envelope and a size to a dynamic attribute. A composition is then a trajectory in the space of aural events, and the complex audio wave is its formal representation. Sounds are fibers in the space of aural events, from which the composer weaves the trajectory of a composition. Each sound object in turn is made up of partials, which are the elementary building blocks of any music composition. The partials evolve on the fastest time scale in the hierarchy of partials, sounds, and compositions. The ideas outlined in this article are being implemented in a digital instrument for additive sound synthesis and in software for music composition. A demonstration of some preliminary results has been submitted by the authors for presentation at the conference.

  20. Ozone Conference II: Abstract Proceedings

    SciTech Connect

    1999-11-01

    Ozone Conference II: Pre- and Post-Harvest Applications Two Years After Gras, was held September 27-28, 1999 in Tulare, California. This conference, sponsored by EPRI's Agricultural Technology Alliance and Southern California Edison's AgTAC facility, was coordinated and organized by the on-site ATA-AgTAC Regional Center. Approximately 175 people attended the day-and-a-half conference at AgTAC. During the Conference twenty-two presentations were given on ozone food processing and agricultural applications. Included in the presentations were topics on: (1) Ozone fumigation; (2) Ozone generation techniques; (3) System and design applications; (4) Prewater treatment requirements; (5) Poultry water reuse; (6) Soil treatments with ozone gas; and (7) Post-harvest aqueous and gaseous ozone research results. A live videoconference between Tulare and Washington, D.C. was held to discuss the regulators' view from inside the beltway. Attendees participated in two Roundtable Question and Answer sessions and visited fifteen exhibits and demonstrations. The attendees included university and governmental researchers, regulators, consultants and industry experts, technology developers and providers, and corporate and individual end-users. This report is comprised of the Abstracts of each presentation, biographical sketches for each speaker and a registration/attendees list.

  1. 1986 annual information meeting. Abstracts

    SciTech Connect

    Not Available

    1986-01-01

    Abstracts are presented for the following papers: Geohydrological Research at the Y-12 Plant (C.S. Haase); Ecological Impacts of Waste Disposal Operations in Bear Creek Valley Near the Y-12 Plant (J.M. Loar); Finite Element Simulation of Subsurface Contaminant Transport: Logistic Difficulties in Handling Large Field Problems (G.T. Yeh); Dynamic Compaction of a Radioactive Waste Burial Trench (B.P. Spalding); Comparative Evaluation of Potential Sites for a High-Level Radioactive Waste Repository (E.D. Smith); Changing Priorities in Environmental Assessment and Environmental Compliance (R.M. Reed); Ecology, Ecotoxicology, and Ecological Risk Assessment (L.W. Barnthouse); Theory and Practice in Uncertainty Analysis from Ten Years of Practice (R.H. Gardner); Modeling Landscape Effects of Forest Decline (V.H. Dale); Soil Nitrogen and the Global Carbon Cycle (W.M. Post); Maximizing Wood Energy Production in Short-Rotation Plantations: Effect of Initial Spacing and Rotation Length (L.L. Wright); and Ecological Communities and Processes in Woodland Streams Exhibit Both Direct and Indirect Effects of Acidification (J.W. Elwood).

  2. Invented Rule with English Language Learners

    ERIC Educational Resources Information Center

    Boyer, Valerie E.; Martin, Kathryn Y.

    2012-01-01

    The purpose of this study was to utilize an invented rule with English language learners (ELLs) in a clinical setting to determine differences based on language and age of the children. The performance was correlated with teacher reports of strong and weak language learning. Using a within-participants design, ELLs of age three to five were taught…

  3. Another Look at the Rules of Differentiation

    ERIC Educational Resources Information Center

    Cupillari, Antonella

    2004-01-01

    It is an eye opening experience for students to find out that even a great mathematician like Leibniz made mistakes, forgot to check carefully his calculations, and was temporarily misled by user-friendly but incorrect formulas. From Leibniz's mishap with the derivation of the rules of differentiation students can learn the importance of spending…

  4. Changing the Rules to Increase Discourse

    ERIC Educational Resources Information Center

    Brooks, Lisa A.; Dixon, Juli K.

    2013-01-01

    This article describes how one of the authors, second-grade teacher Lisa A. Brooks, challenged the raise-your-hand to-speak rule. Her desire to make this change was a result of experiences gained in a graduate class taught by the second author, Juli K. Dixon. Brooks had learned that it is possible to create a classroom community where students…

  5. A Collaborative Educational Association Rule Mining Tool

    ERIC Educational Resources Information Center

    Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; de Castro, Carlos

    2011-01-01

    This paper describes a collaborative educational data mining tool based on association rule mining for the ongoing improvement of e-learning courses and allowing teachers with similar course profiles to share and score the discovered information. The mining tool is oriented to be used by non-expert instructors in data mining so its internal…

  6. Complex linguistic rules modulate early auditory brain responses.

    PubMed

    Sun, Yue; Giavazzi, Maria; Adda-Decker, Martine; Barbosa, Leonardo S; Kouider, Sid; Bachoud-Lévi, Anne-Catherine; Jacquemot, Charlotte; Peperkamp, Sharon

    2015-10-01

    During speech perception, listeners compensate for phonological rules of their language. For instance, English place assimilation causes green boat to be typically pronounced as greem boat; English listeners, however, perceptually compensate for this rule and retrieve the intended sound (n). Previous research using EEG has focused on rules with clear phonetic underpinnings, showing that perceptual compensation occurs at an early stage of speech perception. We tested whether this early mechanism also accounts for the compensation for more complex rules. We examined compensation for French voicing assimilation, a rule with abstract phonological restrictions on the contexts in which it applies. Our results reveal that perceptual compensation for this rule by French listeners modulates an early ERP component. This is evidence that early stages of speech sound categorization are sensitive to complex phonological rules of the native language. PMID:26186230

  7. Abstraction and reformulation in artificial intelligence.

    PubMed Central

    Holte, Robert C.; Choueiry, Berthe Y.

    2003-01-01

    This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense. PMID:12903653

  8. Annotating user-defined abstractions for optimization

    SciTech Connect

    Quinlan, D; Schordan, M; Vuduc, R; Yi, Q

    2005-12-05

    This paper discusses the features of an annotation language that we believe to be essential for optimizing user-defined abstractions. These features should capture semantics of function, data, and object-oriented abstractions, express abstraction equivalence (e.g., a class represents an array abstraction), and permit extension of traditional compiler optimizations to user-defined abstractions. Our future work will include developing a comprehensive annotation language for describing the semantics of general object-oriented abstractions, as well as automatically verifying and inferring the annotated semantics.

  9. Genetic algorithm for extracting rules in discrete domain

    SciTech Connect

    Neruda, R.

    1995-09-20

    We propose a genetic algorithm that evolves families of rules from a set of examples. Inputs and outputs of the problem are discrete and nominal values which makes it difficult to use alternative learning methods that implicitly regard a metric space. A way how to encode sets of rules is presented together with special variants of genetic operators suitable for this encoding. The solution found by means of this process can be used as a core of a rule-based expert system.

  10. Searching for Atmospheric Signatures of Other Worlds (Abstract)

    NASA Astrophysics Data System (ADS)

    Lopez-Morales, M.

    2016-06-01

    (Abstract only) The field of exoplanets continues to evolve at giant steps. With about 2000 planets already discovered around other stars, the next big challenge is to detect and characterize their atmospheres: What is the chemical composition of the atmospheres of those planets? What is their temperature? Do they have clouds? In this talk I will review what we have learned about exoplanets in the past two decades and the current and future efforts to unveil their atmospheres.

  11. Mass Communication: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," January through June 1980 (Vol. 40 Nos. 7 through 12).

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

    This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 55 titles deal with a variety of topics, including the following: (1) the prime time access rule; (2) media education; (3) magazine and children's advertising; (4) Irish national and Third World cinema; (5) international radio…

  12. Journalism and Journalism Education: Abstracts of Doctoral Dissertations Published in "Dissertation Abstracts International," January through June 1980 (Vol. 40 Nos. 7 through 12).

    ERIC Educational Resources Information Center

    ERIC Clearinghouse on Reading and Communication Skills, Urbana, IL.

    This collection of abstracts is part of a continuing series providing information on recent doctoral dissertations. The 30 titles deal with a variety of topics, including the following: (1) the Nigerian press under military rule; (2) the agrarian myth in eighteenth and nineteenth century United States magazines; (3) editorial opinion on education…

  13. Working memory updating and the development of rule-guided behavior.

    PubMed

    Amso, Dima; Haas, Sara; McShane, Lauren; Badre, David

    2014-10-01

    The transition from middle childhood into adolescence is marked by both increasing independence and also extensive change in the daily requirements of familial demands, social pressures, and academic achievement. To manage this increased complexity, children must develop the ability to use abstract rules that guide the choice of behavior across a range of circumstances. Here, we tested children through adults in a task that requires increasing levels of rule abstraction, while separately manipulating competition among alternatives in working memory. We found that age-related differences in rule-guided behavior can be explained in terms of improvement in rule abstraction, which we suggest involves a working memory updating mechanism. Furthermore, family socioeconomic status (SES) predicted change in rule-guided behavior, such that higher SES predicted better performance with development. We discuss these results within a working memory gating framework for abstract rule-guided behavior. PMID:25044248

  14. Abstract Data Types In The Construction Of Knowledge-Based Quantum Chemistry Software

    NASA Astrophysics Data System (ADS)

    Kilpatrick, P. L.; Scott, N. S.

    Recently, Diercksen and Hall (1) presented the OpenMol Program: a proposal for an open, flexible and intelligent software system for performing quantum chemical computations. Central to their proposal was the observation that there is a close relationship between an abstract data type operation and a production rule in a rule-based expert system. The aim of this paper is to explore the establishment of a sound theoretical foundation for this relationship.

  15. OIL POLLUTION ABSTRACTS. VOLUME 6, NUMBER 1

    EPA Science Inventory

    Oil Pollution Abstracts (formerly entitled Oil Pollution Reports) is a quarterly compilation of abstracts of current oil pollution related literature and research projects. Comprehensive coverage of oil pollution and its prevention and control is provided, with emphasis on the aq...

  16. An algorithm for generating abstract syntax trees

    NASA Technical Reports Server (NTRS)

    Noonan, R. E.

    1985-01-01

    The notion of an abstract syntax is discussed. An algorithm is presented for automatically deriving an abstract syntax directly from a BNF grammar. The implementation of this algorithm and its application to the grammar for Modula are discussed.

  17. Revisiting the syntactic abilities of non-human animals: natural vocalizations and artificial grammar learning

    PubMed Central

    ten Cate, Carel; Okanoya, Kazuo

    2012-01-01

    The domain of syntax is seen as the core of the language faculty and as the most critical difference between animal vocalizations and language. We review evidence from spontaneously produced vocalizations as well as from perceptual experiments using artificial grammars to analyse animal syntactic abilities, i.e. abilities to produce and perceive patterns following abstract rules. Animal vocalizations consist of vocal units (elements) that are combined in a species-specific way to create higher order strings that in turn can be produced in different patterns. While these patterns differ between species, they have in common that they are no more complex than a probabilistic finite-state grammar. Experiments on the perception of artificial grammars confirm that animals can generalize and categorize vocal strings based on phonetic features. They also demonstrate that animals can learn about the co-occurrence of elements or learn simple ‘rules’ like attending to reduplications of units. However, these experiments do not provide strong evidence for an ability to detect abstract rules or rules beyond finite-state grammars. Nevertheless, considering the rather limited number of experiments and the difficulty to design experiments that unequivocally demonstrate more complex rule learning, the question of what animals are able to do remains open. PMID:22688634

  18. Predicting terrorist actions using sequence learning and past events

    NASA Astrophysics Data System (ADS)

    Ruda, Harald; Das, Subrata K.; Zacharias, Greg L.

    2003-09-01

    This paper describes the application of sequence learning to the domain of terrorist group actions. The goal is to make accurate predictions of future events based on learning from past history. The past history of the group is represented as a sequence of events. Well-established sequence learning approaches are used to generate temporal rules from the event sequence. In order to represent all the possible events involving a terrorist group activities, an event taxonomy has been created that organizes the events into a hierarchical structure. The event taxonomy is applied when events are extracted, and the hierarchical form of the taxonomy is especially useful when only scant information is available about an event. The taxonomy can also be used to generate temporal rules at various levels of abstraction. The generated temporal rules are used to generate predictions that can be compared to actual events for evaluation. The approach was tested on events collected for a four-year period from relevant newspaper articles and other open-source literature. Temporal rules were generated based on the first half of the data, and predictions were generated for the second half of the data. Evaluation yielded a high hit rate and a moderate false-alarm rate.

  19. 2013 SYR Accepted Poster Abstracts.

    PubMed

    2013-01-01

    SYR 2013 Accepted Poster abstracts: 1. Benefits of Yoga as a Wellness Practice in a Veterans Affairs (VA) Health Care Setting: If You Build It, Will They Come? 2. Yoga-based Psychotherapy Group With Urban Youth Exposed to Trauma. 3. Embodied Health: The Effects of a Mind�Body Course for Medical Students. 4. Interoceptive Awareness and Vegetable Intake After a Yoga and Stress Management Intervention. 5. Yoga Reduces Performance Anxiety in Adolescent Musicians. 6. Designing and Implementing a Therapeutic Yoga Program for Older Women With Knee Osteoarthritis. 7. Yoga and Life Skills Eating Disorder Prevention Among 5th Grade Females: A Controlled Trial. 8. A Randomized, Controlled Trial Comparing the Impact of Yoga and Physical Education on the Emotional and Behavioral Functioning of Middle School Children. 9. Feasibility of a Multisite, Community based Randomized Study of Yoga and Wellness Education for Women With Breast Cancer Undergoing Chemotherapy. 10. A Delphi Study for the Development of Protocol Guidelines for Yoga Interventions in Mental Health. 11. Impact Investigation of Breathwalk Daily Practice: Canada�India Collaborative Study. 12. Yoga Improves Distress, Fatigue, and Insomnia in Older Veteran Cancer Survivors: Results of a Pilot Study. 13. Assessment of Kundalini Mantra and Meditation as an Adjunctive Treatment With Mental Health Consumers. 14. Kundalini Yoga Therapy Versus Cognitive Behavior Therapy for Generalized Anxiety Disorder and Co-Occurring Mood Disorder. 15. Baseline Differences in Women Versus Men Initiating Yoga Programs to Aid Smoking Cessation: Quitting in Balance Versus QuitStrong. 16. Pranayam Practice: Impact on Focus and Everyday Life of Work and Relationships. 17. Participation in a Tailored Yoga Program is Associated With Improved Physical Health in Persons With Arthritis. 18. Effects of Yoga on Blood Pressure: Systematic Review and Meta-analysis. 19. A Quasi-experimental Trial of a Yoga based Intervention to Reduce Stress and

  20. Pericyclic Reactions: FMO Approach-Abstract of Issue 9904M

    NASA Astrophysics Data System (ADS)

    Lee, Albert W. M.; So, C. T.; Chan, C. L.; Wu, Y. K.

    1999-05-01

    Pericyclic Reactions: FMO Approach is a program for Macintosh computers in which the frontier molecular orbital approaches to electrocyclic and cycloaddition reactions are animated. The bonding or antibonding interactions of the frontier molecular orbital(s) determine whether the reactions are thermally or photochemically allowed or forbidden. Pericyclic reactions that involve a redistribution of bonding and nonbonding electrons in a cyclic, concerted manner are an important class of organic reactions. Since the publications of the Woodward-Hoffmann rules on the conservation of orbital symmetry (1) and the frontier molecular orbital theory (FMO) by Fukui first described in the late 1960s (2), the underlying principles of these processes at the molecular level have become fully understood. Many modern organic chemistry textbooks include pericyclic reactions as a major topic. They are usually covered in detail in a typical introductory organic chemistry course. In the Classroom Between the two fundamental approaches to pericyclic reactions, the FMO approach has gained some popularity at the undergraduate teaching level. It is simpler and can be based on a pictorial approach. A detailed understanding of molecular orbital theories and symmetry is not required. Screen from Pericyclic Reactions: FMO Approach When learning the mechanisms of organic reactions, our students have often expressed a wish that they could see how the electrons "jump" and the orbitals "move" in the microscopic world. Pericyclic Reactions: FMO Approach has partially fulfilled the students' request. With its color 3-D graphics and animation, Pericyclic Reactions: FMO Approach can greatly enhance the teaching and learning of the FMO approach to pericyclic reactions. The stereochemical outcomes of these highly stereospecific reactions can be seen clearly as the reaction process is animated on the computer screen. Based on the