997 resultados para Inteligência artificial - Filosofia
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Mestrado em Controlo de Gestão e dos Negócios
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Dissertação apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo de Gestão de Empresas. Orientada por Prof. Dra. Maria Rosário Moreira e Prof. Dr. Paulo Sousa
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Dissertação de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil, perfil de Edificações
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia da Manutenção
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Trabalho Final de mestrado para obtenção do grau de Mestre em Engenharia Mecânica perfil Manutenção e Produção
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Revista da Faculdade de Ciências Sociais e Humanas, N.14(2001)
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Decision making in any environmental domain is a complex and demanding activity, justifying the development of dedicated decision support systems. Every decision is confronted with a large variety and amount of constraints to satisfy as well as contradictory interests that must be sensibly accommodated. The first stage of a project evaluation is its submission to the relevant group of public (and private) agencies. The individual role of each agency is to verify, within its domain of competence, the fulfilment of the set of applicable regulations. The scope of the involved agencies is wide and ranges from evaluation abilities on the technical or economical domains to evaluation competences on the environmental or social areas. The second project evaluation stage involves the gathering of the recommendations of the individual agencies and their justified merge to produce the final conclusion. The incorporation and accommodation of the consulted agencies opinions is of extreme importance: opinions may not only differ, but can be interdependent, complementary, irreconcilable or, simply, independent. The definition of adequate methodologies to sensibly merge, whenever possible, the existing perspectives while preserving the overall legality of the system, will lead to the making of sound justified decisions. The proposed Environmental Decision Support System models the project evaluation activity and aims to assist developers in the selection of adequate locations for their projects, guaranteeing their compliance with the applicable regulations.
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The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.
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Dissertação de Doutoramento em Filosofia
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Relatório apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Ensino da Filosofia no Secundário
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This paper presents several forecasting methodologies based on the application of Artificial Neural Networks (ANN) and Support Vector Machines (SVM), directed to the prediction of the solar radiance intensity. The methodologies differ from each other by using different information in the training of the methods, i.e, different environmental complementary fields such as the wind speed, temperature, and humidity. Additionally, different ways of considering the data series information have been considered. Sensitivity testing has been performed on all methodologies in order to achieve the best parameterizations for the proposed approaches. Results show that the SVM approach using the exponential Radial Basis Function (eRBF) is capable of achieving the best forecasting results, and in half execution time of the ANN based approaches.
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RESUMO - Introdução: A Inteligência Emocional (IE) é considerada um factor preditivo de sucesso, mais significativo do que outros tipos de inteligência e o seu estudo tem recebido cada vez maior relevância com o objectivo de aumentar os níveis de desempenho em gestão (Goleman, 2009). O desenvolvimento da IE no âmbito da formação em gestão apresenta resultados contraditórios sendo necessário confirmar o potencial de desenvolvimento da IE em programas de formação específicos. Objectivos: Confirmar a importância da IE para a gestão da saúde e perceber o seu potencial de desenvolvimento em programas de formação específicos; analisar o módulo opcional de Emoção, Liderança e Coaching na Gestão em Saúde; e construir uma proposta de modelo que avalie se a participação nessa Unidade Curricular permite aumentar os níveis de IE. Metodologia: Realizou-se uma revisão da literatura, que permitiu ter acesso aos conceitos e teorias e, posteriormente, o estudo de caso do módulo opcional que permitiu compará-lo com outras teorias existentes. Finalmente, construiu-se uma proposta de modelo de avaliação da IE, com um desenho quasi-experimental. Conclusões: A IE é um factor essencial para o sucesso, principalmente na Gestão da Saúde, pelas características do mercado e das organizações. Os instrumentos de avaliação da IE com recurso à medição de competências são os que apresentam menos limitações. O peso do módulo opcional no Curso de Mestrado em Gestão da Saúde, é pouco significativo (3,33% dos ECTS) e apenas 36,6% dos alunos o frequentaram. A estrutura do módulo está alinhada com as directrizes de outras teorias, mas a sua curta duração poderá constituir uma limitação. Sugere-se a criação de apoio tutorial individualizado e prolongado. O modelo de avaliação proposto representa a primeira tentativa de avaliação do desenvolvimento da IE na formação em Gestão da Saúde em Portugal e a sua aplicação permitiria a o aprimoramento do potencial de desenvolvimento das competências dos gestores. ---------------------------------- ABSTRACT - Introduction: Emotional Intelligence (EI) is the most predictive factor of success when compared with other types of intelligence. Since it is believed to increase performance levels, EI study has been given more relevance (Goleman, 2009). EI development studies show contradictory results, becoming necessary to prove the benefits of the development programs. Purposes: This study aimed to confirm the importance of the EI in health care management; to perceive the EI development potential of specific programs; to analyze the optional curricular unit of Emotion, Coaching and Leadership in Health Management; and to build a model that proposes to evaluate the student’s EI development. Methods: After the Literature Revision, the Case Study of the Curricular Unit allowed to compare it with other existing theories. The Model of EI evaluation consists on a quasi-experimental study. Conclusions: EI is an essential factor for success, mainly in Health Care Management, because of its market and organizations characteristics. The ability instruments of EI evaluation are those which show the least limitations. The Curricular Unit represents only 3,33% of the ECTS provided by this Health Management Master. Only 36.6% of master’s students chose to participate in this curricular unit. The structure of the curricular unit is lined up with the guide-lines of other theories. However, being a 6 weeks program, it could represent a limitation. It is suggested to create an individual and longitudinal tutorial support. The EI evaluation model proposed represents the first attempt to evaluate de EI development in Health Management programs in Portugal. Its application could increase the manager’s development efficacy.
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A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.
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Trypanosoma cruzi parasitemia observed in immunocompromised patients (transplant or positive HIV) occurred more frequently by the artificial xenodiagnosis method (10/38) compared with hemoculture (2/38), given the same quantity of blood. Other ways of diagnosis, like mice inoculation (5/38), QBC and buffy coat (2/38), were evaluated also. This result showed the importance of the artificial xenodiagnosis. The other techniques increased only one more patient positive.