974 resultados para Learning Programming Paradigms
Resumo:
Using the integer programming approach introduced by Sethuraman, Teo, and Vohra (2003), we extend the analysis of the preference domains containing an inseparable ordered pair, initiated by Kalai and Ritz (1978). We show that these domains admit not only Arrovian social welfare functions \without ties," but also Arrovian social welfare functions \with ties," since they satisfy the strictly decomposability condition introduced by Busetto, Codognato, and Tonin (2012). Moreover, we go further in the comparison between Kalai and Ritz (1978)'s inseparability and Arrow (1963)'s single-peak restrictions, showing that the former condition is more \respectable," in the sense of Muller and Satterthwaite (1985).
Resumo:
In rats pre-but not post-training ip administration of either flumazenil, a central benzodiazepine (BSD) receptor antagonist, or of n-butyl-B-carboline-carboxylate (BCCB), an inverse agonist, enhanced retention of inhibitory avoidance learning. Flumazenil vlocked the enhancing effect of BCCB, and the inhibitory effect of the BZD agonists clonazepam and diazepam also given pre-training. Post-training administration of these drugs had no effects. The peripheral BZD receptor agonist/chloride channel blocker Ro5-4864 had no effect on the inhibitory avoidance task when given ip prior to training, buth it caused enhancement when given immediately post-training either ip or icv. This effect was blocked by PK11195, a competitive antagonist of Ro5-4864. These results suggest that ther is an endogenous mechanism mediated by BZD agonists, which is sensitive to inverse agonists and that normally down-regulates the formation of memories through a mechanism involving GABA-A receptors and the corresponding chloride channels. The most likely agonists for the endogenous mechanism suggested are the diazepam-like BZDs found in brain whose origin is possibly alimentary. Levels of these BZDs in the cortex were found to sharply decrease after inhibitory acoidance training or mere exposure to the training apparatus.
Resumo:
This study explores how South African Early Childhood Development (ECD) Practitioners and families meet the needs of the increasing number of children from diverse cultural backgrounds in their care. Research participants were identified through ten ECD centres located in two urban communities in the Eastern and Western Cape Provinces of South Africa. The values and attitudes held by Practitioners and families vis-à-vis cultural diversity was investigated, along with the knowledge and strategies they employ to manage cultural diversity in ECD programmes. The intercultural education model provides the necessary tools to address the challenges identified.
Resumo:
The human auditory system is comprised of specialized but interacting anatomic and functional pathways encoding object, spatial, and temporal information. We review how learning-induced plasticity manifests along these pathways and to what extent there are common mechanisms subserving such plasticity. A first series of experiments establishes a temporal hierarchy along which sounds of objects are discriminated along basic to fine-grained categorical boundaries and learned representations. A widespread network of temporal and (pre)frontal brain regions contributes to object discrimination via recursive processing. Learning-induced plasticity typically manifested as repetition suppression within a common set of brain regions. A second series considered how the temporal sequence of sound sources is represented. We show that lateralized responsiveness during the initial encoding phase of pairs of auditory spatial stimuli is critical for their accurate ordered perception. Finally, we consider how spatial representations are formed and modified through training-induced learning. A population-based model of spatial processing is supported wherein temporal and parietal structures interact in the encoding of relative and absolute spatial information over the initial ∼300ms post-stimulus onset. Collectively, these data provide insights into the functional organization of human audition and open directions for new developments in targeted diagnostic and neurorehabilitation strategies.
Resumo:
There are controversial reports about the effect of aging on movement preparation, and it is unclear to which extent cognitive and/or motor related cerebral processes may be affected. This study examines the age effects on electro-cortical oscillatory patterns during various motor programming tasks, in order to assess potential differences according to the mode of action selection. Twenty elderly (EP, 60-84 years) and 20 young (YP, 20-29 years) participants with normal cognition underwent 3 pre-cued response tasks (S1-S2 paradigm). S1 carried either complete information on response side (Full; stimulus-driven motor preparation), no information (None; general motor alertness), or required free response side selection (Free; internally-driven motor preparation). Electroencephalogram (EEG) was recorded using 64 surface electrodes. Alpha (8-12 Hz) desynchronization (ERD)/synchronization (ERS) and motor-related amplitude asymmetries (MRAA) were analyzed during the S1-S2 interval. Reaction times (RTs) to S2 were slower in EP than YP, and in None than in the other 2 tasks. There was an Age x Task interaction due to increased RTs in Free compared to Full in EP only. Central bilateral and midline activation (alpha ERD) was smaller in EP than YP in None. In Full just before S2, readiness to move was reflected by posterior midline inhibition (alpha ERS) in both groups. In Free, such inhibition was present only in YP. Moreover, MRAA showed motor activity lateralization in both groups in Full, but only in YP in Free. The results indicate reduced recruitment of motor regions for motor alertness in the elderly. They further show less efficient cerebral processes subtending free selection of movement in elders, suggesting reduced capacity for internally-driven action with age.
Resumo:
Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.
Resumo:
El proyecto trata de crear un software que dinámicamente nos proporcione exámenes o pruebas dependiendo de nuestro nivel de conocimientos actual. Estos exámenes se cargarán a través de un fichero XML configurable, lo que nos permitirá poner a prueba nuestros conocimientos en el tema que deseemos. El software se desarrollará en Nintendo DS, para aprovechar las prestaciones que nos ofrece de serie: doble pantalla, pantalla táctil, portabilidad.
Resumo:
In this paper we describe an open learning object repository on Statistics based on DSpace which contains true learning objects, that is, exercises, equations, data sets, etc. This repository is part of a large project intended to promote the use of learning object repositories as part of the learning process in virtual learning environments. This involves the creation of a new user interface that provides users with additional services such as resource rating, commenting and so. Both aspects make traditional metadata schemes such as Dublin Core to be inadequate, as there are resources with no title or author, for instance, as those fields are not used by learners to browse and search for learning resources in the repository. Therefore, exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting the visibility of the learning objects in the repository outside the institution. We propose an architecture based on ontologies and the use of extended metadata records for both storing and refactoring such descriptions.
Resumo:
This paper studies optimal monetary policy in a framework that explicitly accounts for policymakers' uncertainty about the channels of transmission of oil prices into the economy. More specfically, I examine the robust response to the real price of oil that US monetary authorities would have been recommended to implement in the period 1970 2009; had they used the approach proposed by Cogley and Sargent (2005b) to incorporate model uncertainty and learning into policy decisions. In this context, I investigate the extent to which regulator' changing beliefs over different models of the economy play a role in the policy selection process. The main conclusion of this work is that, in the specific environment under analysis, one of the underlying models dominates the optimal interest rate response to oil prices. This result persists even when alternative assumptions on the model's priors change the pattern of the relative posterior probabilities, and can thus be attributed to the presence of model uncertainty itself.