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This work proposes some considerations and reflections on the knowledge transfer process that occurs when relationships are established between the firm and the university. More specifically, it addresses the effects of the type of agreement between the parties and the size of the recipient unit on the success of the transfer. To that end, the work begins by defining what is understood by knowledge:...
In the present study, we characterized the phagocytic capacity, cytokine profile along with the FCγ-R and TLR expression in leukocytes from Chagas disease patients (indeterminate-IND and cardiac-CARD) before and one-year after Bz-treatment (IND T and CARD T ). A down-regulation of IL-17, IFN-γ and IL-10 synthesis by neutrophils was observed in CARD T . The Bz-treatment did...
The distinct ability of phagocytes to present antigens, produce cytokines and provide co-stimulatory signals may contribute to the severity of the outcome of Chagas disease. In this paper, we evaluate the phenotypic features of phagocytes along with the cytokine signature of circulating T-cells from Chagas disease patients with indeterminate (IND) and cardiac (CARD) clinical forms of the disease....
This work presents a multi-dimensional similarity modeling strategy and relevance feedback technique for minimizing the semantic gap intrinsic problem of CBIR systems by allowing users to customize their queries according to their requirements and preferences. We propose a composite strategy using a multi-dimensional, vectorial, spatially clustered, and relevance-ordered approach. Given a set of k...
The achievement of image retrieval systems severally depends on the way the data is represented. This paper proposes a new image representation through an intelligent mechanism via neural networks for semantic-gap and dimensionality reduction. The goal of the multilayer neural network is to represent high-level semantic concepts and knowledge through a pre-defined set of images. As a consequence of...
This paper introduces a new matching algorithm to estimate the similarity between two contour saliences by exploiting the relation between a contour and its skeleton. Some experimental results are presented and discussed in order to demonstrate the potentiality of the proposed technique.
This work presents a new image characterization through an intelligent mechanism via neural networks. The goal of a neural network is to represent the high-level semantic concepts and the knowledge through a pre-defined set of images. As a consequence of this low-level into high-level feature transformation there is a semantic gap reduction between the human perception and the automatic feature extraction...
Low-level attributes such as color, shape and texture generally fail in describing the high-level semantic concepts. This work presents, through the formation of a high- level characteristics vector, the representation of the subjective knowledge used by humans for the verification of which aspects are most important for image characterization. Such vector will be formed by using the Artificial Intelligence...
In this work an image retrieval system adaptable to user's interests by the use of relevance feedback via genetic algorithm is presented. The retrieval process is based on local similarity patterns. The goal of the genetic algorithm is to infer weights for regions and features that better translate the user's requirements producing better quality rankings. The genetic algorithm used has as its main...
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