No abstract

Segmentation is a crucial step in Computer Vision in which texture plays an important role. The existence of a large amount of methods from which texture can be computed is, sometimes, a hurdle to overcome when it comes to modeling solutions for texture-based segmentation. Following the excellence of the natural vision system and its generality, this work has adopted a feature selection method based on salience of synaptic connections of a Multilayer Perceptron neural network. Unlike traditional approaches [9,21], this paper introduces an equalization scheme to salience measures which contributed to significantly improve the selection of the most suitable features and, hence, yield better segmentation. The proposed method is compared with exhaustive search according to the Jeffrey-Matusita distance criterion. Segmentation for images of natural scenes has also been provided as a probable application of the method.

Organizational climate impacts on the employee’s well-being, commitment and positive behavior. Most studies to assess climate in healthcare organizations use qualitative and/or statistical methods. Here, we propose a general framework, based on a multiple criteria decision making/aid (MCDM / A) method, which considers different objectives in a single problem. Such framework includes internal and external factors to assess organizational climate and presented adequate results when tested in a particular case. To assess the organizational climate, we use the ELECTRE TRI method, an outranking method that combine the decision-maker (DM) preferences and his value judgments. We conclude that MCDM methods can improve agility, provide a systemic vision on organizational climate assessment and contribute to the decision-making process

Considering the increasing scenario of natural gas consumption, it is necessary that all agents in the chain use methods that structure decision-making and problem-solving processes. This paper proposes a multicriteria decision model to solve a site selection problem for a pressure reducing station. A natural gas distribution company was selected to test the model and the preference modeling was conducted through the flexible interactive tradeoff (FITradeoff) approach, according to the preferences of the decision maker (DM). FITradeoff's decision support system was used to assess the alternatives of the model, through the inference of the criteria scale constants. The results proved the robustness of the model and the DM evidenced consistency in its preferences. Also, the FITradeoff method demonstrated to be intuitive to apply, since a smaller effort is required from the DM and this is because the procedure does not require complete information in the scale constants elicitation process.