Fatores de sucesso no desenvolvimento de novos produtos em pequenas empresas: um estudo de caso em um fabricante de equipamentos para gás natural veicular

This study presents itself as a contribution to the solidification of the Natural Gas industry, within the scope of the development of new products. The goal of this paper is to analyze the factors that lead to the success of new products through the evaluation of the activities done during the process of development of these products in the Natural Gas sector. To achieve this goal a case study was done in a small company of this segment. At first, as a basis for the study, a bibliographical research was done with books, theses, dissertations, monographies, publications in national and international periodicals, congress annals and publications in the internet related to the subject. Afterwards, a case study was done, aiming at the acquisition of further knowledge about the real process of development of products in a small company of the Natural Gas sector, allowing for the performance of the evaluation. The case study was done at Gas Project and Systems do Brasil, a company that works with the development of electronic equipment to the conversion of car engines to natural gas, through direct observations and interviews with the person responsible for the development and management of products. Through the evaluation of the process it was observed that the activities related to it are done in an informal way and some activities are considered unnecessary for their success. The results also suggest an emphasis in the technological activities, something that was not observed in the activities related to the market. The instruments used in this evaluation prove to be efficient to evaluate the process of development of new products in other companies, including those of different areas. Taking into account the relevance of the studied theme to the strengthening of the Natural Gas industry, it is necessary to do further complementary studies

Multi-resolução com fóvea móvel para redução e abstração de dados em tempo real

We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

Segmentação Fuzzy de Texturas e Vídeos

The segmentation of an image aims to subdivide it into constituent regions or objects that have some relevant semantic content. This subdivision can also be applied to videos. However, in these cases, the objects appear in various frames that compose the videos. The task of segmenting an image becomes more complex when they are composed of objects that are defined by textural features, where the color information alone is not a good descriptor of the image. Fuzzy Segmentation is a region-growing segmentation algorithm that uses affinity functions in order to assign to each element in an image a grade of membership for each object (between 0 and 1). This work presents a modification of the Fuzzy Segmentation algorithm, for the purpose of improving the temporal and spatial complexity. The algorithm was adapted to segmenting color videos, treating them as 3D volume. In order to perform segmentation in videos, conventional color model or a hybrid model obtained by a method for choosing the best channels were used. The Fuzzy Segmentation algorithm was also applied to texture segmentation by using adaptive affinity functions defined for each object texture. Two types of affinity functions were used, one defined using the normal (or Gaussian) probability distribution and the other using the Skew Divergence. This latter, a Kullback-Leibler Divergence variation, is a measure of the difference between two probability distributions. Finally, the algorithm was tested in somes videos and also in texture mosaic images composed by images of the Brodatz album