147 resultados para Distributed object
Resumo:
Ten mothers were observed prospectively, interacting with their infants aged 0 ; 10 in two contexts (picture description and noun description). Maternal communicative behaviours were coded for volubility, gestural production and labelling style. Verbal labelling events were categorized into three exclusive categories: label only; label plus deictic gesture; label plus iconic gesture. We evaluated the predictive relations between maternal communicative style and children's subsequent acquisition of ten target nouns. Strong relations were observed between maternal communicative style and children's acquisition of the target nouns. Further, even controlling for maternal volubility and maternal labelling, maternal use of iconic gestures predicted the timing of acquisition of nouns in comprehension. These results support the proposition that maternal gestural input facilitates linguistic development, and suggest that such facilitation may be a function of gesture type.
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Recently, two approaches have been introduced that distribute the molecular fragment mining problem. The first approach applies a master/worker topology, the second approach, a completely distributed peer-to-peer system, solves the scalability problem due to the bottleneck at the master node. However, in many real world scenarios the participating computing nodes cannot communicate directly due to administrative policies such as security restrictions. Thus, potential computing power is not accessible to accelerate the mining run. To solve this shortcoming, this work introduces a hierarchical topology of computing resources, which distributes the management over several levels and adapts to the natural structure of those multi-domain architectures. The most important aspect is the load balancing scheme, which has been designed and optimized for the hierarchical structure. The approach allows dynamic aggregation of heterogenous computing resources and is applied to wide area network scenarios.
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This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distributed across the whole network. We adopt the Situation Calculus to define a network model and the Reactive Golog language to implement the logical reasoner. An active network management architecture is used by the reasoner to inject and execute operational tasks in the network. The integrated system collects the advantages coming from logical reasoning and network programmability, and provides a powerful system capable of performing high-level management tasks in order to deal with network fault.
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In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.
Resumo:
A common method for testing preference for objects is to determine which of a pair of objects is approached first in a paired-choice paradigm. In comparison, many studies of preference for environmental enrichment (EE) devices have used paradigms in which total time spent with each of a pair of objects is used to determine preference. While each of these paradigms gives a specific measure of the preference for one object in comparison to another, neither method allows comparisons between multiple objects simultaneously. Since it is possible that several EE objects would be placed in a cage together to improve animal welfare, it is important to determine measures for rats' preferences in conditions that mimic this potential home cage environment. While it would be predicted that each type of measure would produce similar rankings of objects, this has never been tested empirically. In this study, we compared two paradigms: EE objects were either presented in pairs (paired-choice comparison) or four objects were presented simultaneously (simultaneous presentation comparison). We used frequency of first interaction and time spent with each object to rank the objects in the paired-choice experiment, and time spent with each object to rank the objects in the simultaneous presentation experiment. We also considered the behaviours elicited by the objects to determine if these might be contributing to object preference. We demonstrated that object ranking based on time spent with objects from the paired-choice experiment predicted object ranking in the simultaneous presentation experiment. Additionally, we confirmed that behaviours elicited were an important determinant of time spent with an object. This provides convergent evidence that both paired choice and simultaneous comparisons provide valid measures of preference for EE objects in rats. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
Previous functional imaging studies have shown that facilitated processing of a visual object on repeated, relative to initial, presentation (i.e., repetition priming) is associated with reductions in neural activity in multiple regions, including fusiforin/lateral occipital cortex. Moreover, activity reductions have been found, at diminished levels, when a different exemplar of an object is presented on repetition. In one previous study, the magnitude of diminished priming across exemplars was greater in the right relative to the left fusiform, suggesting greater exemplar specificity in the right. Another previous study, however, observed fusiform lateralization modulated by object viewpoint, but not object exemplar. The present fMRI study sought to determine whether the result of differential fusiform responses for perceptually different exemplars could be replicated. Furthermore, the role of the left fusiform cortex in object recognition was investigated via the inclusion of a lexical/semantic manipulation. Right fusiform cortex showed a significantly greater effect of exemplar change than left fusiform, replicating the previous result of exemplar-specific fusiform lateralization. Right fusiform and lateral occipital cortex were not differentially engaged by the lexical/semantic manipulation, suggesting that their role in visual object recognition is predominantly in the. C visual discrimination of specific objects. Activation in left fusiform cortex, but not left lateral occipital cortex, was modulated by both exemplar change and lexical/semantic manipulation, with further analysis suggesting a posterior-to-anterior progression between regions involved in processing visuoperceptual and lexical/semantic information about objects. The results are consistent with the view that the right fusiform plays a greater role in processing specific visual form information about objects, whereas the left fusiform is also involved in lexical/semantic processing. (C) 2003 Elsevier Science (USA). All rights reserved.
Resumo:
Distributed computing paradigms for sharing resources such as Clouds, Grids, Peer-to-Peer systems, or voluntary computing are becoming increasingly popular. While there are some success stories such as PlanetLab, OneLab, BOINC, BitTorrent, and SETI@home, a widespread use of these technologies for business applications has not yet been achieved. In a business environment, mechanisms are needed to provide incentives to potential users for participating in such networks. These mechanisms may range from simple non-monetary access rights, monetary payments to specific policies for sharing. Although a few models for a framework have been discussed (in the general area of a "Grid Economy"), none of these models has yet been realised in practice. This book attempts to fill this gap by discussing the reasons for such limited take-up and exploring incentive mechanisms for resource sharing in distributed systems. The purpose of this book is to identify research challenges in successfully using and deploying resource sharing strategies in open-source and commercial distributed systems.
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This paper addresses the requirements for a Work/flow Management System that is intended to automate the production and distribution chain for cross-media content which is by nature multi-partner and multi-site. It advocates the requirements for an ontology-based object lifecycle tracking within work/flow integration by identifying various types of interfaces, object life cycles and the work-flow interaction environments within the AXMEDIS Framework.
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There has been a clear lack of common data exchange semantics for inter-organisational workflow management systems where the research has mainly focused on technical issues rather than language constructs. This paper presents the neutral data exchanges semantics required for the workflow integration within the AXAEDIS framework and presents the mechanism for object discovery from the object repository where little or no knowledge about the object is available. The paper also presents workflow independent integration architecture with the AXAEDIS Framework.