Aspectos linguístico-ergonômicos em rótulos: avaliação da linguagem verbo-visual de rótulos de embalagens para alimentos achocolatados

We have been living in a world of packed products. The package and the labels support the companies to communicate with the customers in addition to give protection, storage and convenience in proportion to the products that move in the price list. The labels mainly add up a value which helps the companies differ their products and increase the value of the brands among the final customers. However, the information given in the label are not clear sometimes. It displays a verbal-visual defective language resulted from a poor visibility, legibleness and comprehensibleness of the verbal and visual marks. The aim of this research is to verify, according to the costumers‟ view, the level of the clarity in the informative texts, harmony and ergonomic conformity of the package labels in the chocolate powder of the Claralate brand, considering the linguistic aspects presented on the labels. The criteria to evaluate the chocolate package selected were based on the linguistic field: the organization and the structure of the text derided from the classification of the textual genre; the clarity and the comprehension of the language utilized on those labels. From the ergonomic view, the informative and ergonomic conformity, based on the following requirements: legibility, symbols, characters, reading fields and intermission of the written lines. Therefore, the research done july 2007 and added july 2011 had a structured questionnaire in the interview put to the 118 customers of the chocolate package that go shopping in one of the two supermarkets in Floriano, Piauí São Jorge and/or Super Quaresma. The main results of the investigation show that the linguistic aspects in the informative texts of the labels provide the customers‟ expectancy partially, while the consideration of the informative ergonomic analyzed can contribute to the improvement of the information and consequent visual progress of those, on the labels of chocolate package investigated. As recommendation towards the maker of the product, the outcome of the research indicates: harmonize the proportion of the letters and numbers; enlarge the letters size; make the visual information more comprehensive determined by the reading field; put the expiry date in a better visual place

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries