A pegada de carbono como um dos indicadores de sustentabilidade para medição da responsabilidade socioambiental empresarial: um estudo de caso na unidade sede da Petrobras em Natal-RN

As a contemporary tendency, it is been evidenced that the environmental changes theme, already admitted as a concernment to international economical and political reality, is also gaining repercussion on industrial and business sector. Firms are implementing actions on trial to minimize their own greenhouse gases (GHG) emissions impacts. However, the great majority of those actions of Corporative Social-Environmental Responsibility (CSR) are referred only to direct emissions of the main production systems. Direct emissions are those derived of an isolate process, without considering the upstream and downstream processes emissions, which respond for the majority of emissions originated because of respective firm‟s production system existence. Because the greenhouse effect occurs globally and the GHG emissions contribute to the environmental changes independently of their origin, it must be taken into account the whole productive life cycle of products and systems, since the energy invested on resources extraction and necessary materials to the final disposal. To do so, it must be investigated all relevant steps of a product/production system life cycle, tracking all activities which emit greenhouse gases, directly or indirectly. This amount of emissions consists in the firm‟s Carbon Footprint. This research purpose is to defend the Carbon Footprint relevance and its adoption viability to be used as an Environmental Indicator on measurement/assessment of CSR. It has been realized a study case on Petrobras‟s seat unity at Natal-Brazil, assessing part of its Carbon Footprint. It has been used the software GEMIS 4.6 to do the emissions quantifying. The items measured were the direct emissions of the own unity vehicles and indirect emissions of offset paper (A4), energy and disposable plastic cups consumed. To 2009, these emissions were 3.811,94 tCO2eq. We may conclude that Carbon Footprint quantification is indispensable to the knowledge of real emissions caused by a productive process existence, must serving as basis to CSR decisions about the environmental changes reversion challenge

Método Fuzzy para auxílio ao diagnóstico de câncer de mama em ambiente inteligente de telediagnóstico colaborativo para apoio à tomada de decisão

Breast cancer, despite being one of the leading causes of death among women worldwide is a disease that can be cured if diagnosed early. One of the main techniques used in the detection of breast cancer is the Fine Needle Aspirate FNA (aspiration puncture by thin needle) which, depending on the clinical case, requires the analysis of several medical specialists for the diagnosis development. However, such diagnosis and second opinions have been hampered by geographical dispersion of physicians and/or the difficulty in reconciling time to undertake work together. Within this reality, this PhD thesis uses computational intelligence in medical decision-making support for remote diagnosis. For that purpose, it presents a fuzzy method to assist the diagnosis of breast cancer, able to process and sort data extracted from breast tissue obtained by FNA. This method is integrated into a virtual environment for collaborative remote diagnosis, whose model was developed providing for the incorporation of prerequisite Modules for Pre Diagnosis to support medical decision. On the fuzzy Method Development, the process of knowledge acquisition was carried out by extraction and analysis of numerical data in gold standard data base and by interviews and discussions with medical experts. The method has been tested and validated with real cases and, according to the sensitivity and specificity achieved (correct diagnosis of tumors, malignant and benign respectively), the results obtained were satisfactory, considering the opinions of doctors and the quality standards for diagnosis of breast cancer and comparing them with other studies involving breast cancer diagnosis by FNA.