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Modelers face multiple challenges in their work. In this paper, we focus on two of them. First, multiple modeling methods and tools are currently available. Modelers are sometimes limited by their tools or paradigms. Second, when multiple models are proposed for the same case, a decision maker needs criteria to decide which model to choose for his/her objective.
Traditional affective lexicons are mainly based on discrete classes, such as positive, happiness, sadness, which may limit its expressive power compared to the dimensional representation in which affective meanings are expressed through continuous numerical values on multiple dimensions, such as valence-arousal. Traditional methods for acquiring dimensional lexicons are mainly based on time-consuming...
Deep Convolutional Neural Networks(DCNNs) have recently shown great performance in many high-level vision tasks, such as image classification, object detection and more recently outdoor semantic segmentation. However, the convolutional layer only process the local regions in the image, ignoring the global context information. To overcome this poor localization property of Convolutional Neural Networks(CNNs),...
Both modularity and loose-coupling properties inherent to the self-adaptive systems offer the opportunity for ad-hoc service compositions, dynamic change and adaptation. To provide such a dynamic and self-adapting behavior, developers emphasize special self-management policies. ASSL (Autonomic System Specification Language) is a formal tool where such policies might be formally specified, validated...
Toponym Disambiguation (TD) in Geographic Information Retrieval (GIR) systems is a crucial technique, which makes a direct impact on the quality of subsequent assignment of geographic focus to a document and that of establishment of spatial index as well as the effectiveness of the entire retrieval model as a whole. We explore the mechanism for human beings' dealing with the problem of TD. Human's...
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