1,761 research outputs found

    Overburdening associations: the dependency of psychopathy- related acquisitional learning deficits on processing load

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    Psychopathic personality traits have been identified as an important individual predictor of associative learning capacity. Prior work has associated psychopathy with deficits when adapting learned associations in response to novel information. However, findings are inconsistent and are hypothesised to vary as a function of the processing load created by different experimental paradigms. We tested this hypothesis by examining the association between psychopathic traits and Stimulus-Response-Outcome contingency learning whilst manipulating contextual processing load. In experiment one and two, participants completed three versions of a configural object discrimination task that required participants to use increasingly multidimensional learning cues. Across both experiments, it was found that elevated levels of psychopathic traits were associated with a lesser capacity to form S-R-O associations in the bidimensional but not tridimensional versions of the learning task. This suggests psychopathy-related learning deficits may vary as a function of processing load inherent to the bidimensional learning environment, rather than the type of learning taking place. This provides some of the first experimental evidence that psychopathic learning deficits are detectable during the acquisition phase of learning

    Enabling Ontology-based data access to streaming sources

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    The availability of streaming data sources is progressively increasing thanks to the development of ubiquitous data capturing tech- nologies such as sensor networks. The heterogeneity of these sources in- troduces the requirement of providing data access in a uni ed and co- herent manner, whilst allowing the user to express their needs at an ontological level. In this paper we describe an ontology-based streaming data access service. Sources link their data content to ontologies through s2o mappings. Users can query the ontology using sparqlStream, an ex- tension of sparql for streaming data. A preliminary implementation of the approach is also presented. With this proposal we expect to set the basis for future e orts in ontology-based streaming data integration

    Pedagogical and Acquisitional Implications of the Intonational Map Provided by Korean Textbook Example Conversations

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    Through the analyzation of a corpus of K-ToBI annotated speech taken from beginning level textbook conversation recordings, this paper aims to determine the global attributes of Slow, Clear Speech (SCS) on Korean prosody production, and to implicate these effects in the pedagogy of beginning-level Korean. In an analysis of the features that make Korean SCS distinct, four common themes emerged. First, there is final lengthening on Accentual Phrases (APs). Second, there are additional pauses and breaks between APs. Third, there is broad use of pitch reset and of focus in small syntactic frames. And fourth, boundary tones are typically flat and disaffected. Intonation plays a key role in the pursuit of L2 Korean intelligibility and is integral to strong acquisition of Korean. However, instructors rarely speak at normal speech rates (SR) with normal articulation, and typically use SCS with their beginning students. Students will recall frequently heard or salient intonational patterns, so instructors must take care to use intonational patterns intentionally. Thus, it is proposed that instructors of beginner students give explicit instruction and direct feedback on intonation and show natural speech examples often from various speakers, among other strategies to mitigate the effects of SCS on student intonational acquisition

    Automatic application object migration in sensor networks

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    Object migration in wireless sensor networks has the potential to reduce energy consumption for a wireless sensor network mesh. Automated migration reduces the need for the programmer to perform manual static analysis to find an efficient layout solution. Instead, the system can self-optimise and adjust to changing conditions. This paper describes an automated, transparent object migration system for wireless sensor networks, implemented on a micro Java virtual machine. The migration system moves objects at runtime around the sensor mesh to reduce communication overheads. The movement of objects is transparent to the application developer. Automated transparent object migration is a core component of Hydra, a distributed operating system for wireless sensor networks that is currently under development. Performance of the system under a complex performance test scenario using a real-world dataset of seismic events is described. The results show that under both simple and complex conditions the migration technique can result in lower data traffic and consequently lower overall energy cost
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