31 resultados para Organizational Diagnosis

em Instituto Politécnico do Porto, Portugal


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Dissertação apresentada ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Professor Doutor José de Freitas Santos

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This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

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Antibodies against gliadin are used to detect celiac disease (CD) in patients. An electrochemical immunosensor for the voltammetric detection of human anti-gliadin antibodies (AGA) IgA and AGA IgG in real serum samples is proposed. The transducer surface consists of screen-printed carbon electrodes modified with a carbon nanotube/gold nanoparticle hybrid system, which provides a very useful surface for the amplification of the immunological interactions. The immunosensing strategy is based on the immobilization of gliadin, the antigen for the autoantibodies of interest, onto the nanostructured surface. The antigen–antibody interaction is recorded using alkaline phosphatase labeled anti-human antibodies and a mixture of 3-indoxyl phosphate with silver ions (3-IP/Ag+) was used as the substrate. The analytical signal is based on the anodic redissolution of the enzymatically generated silver by cyclic voltammetry. The electrochemical behavior of this immunosensor was carefully evaluated assessing aspects as sensitivity, non-specific binding and matrix effects, and repeatability and reproducibility. The results were supported with a commercial ELISA test.

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A indústria automóvel é um dos setores mais exigentes do mercado global, por este motivo empresas como a Continental Mabor S.A, líderes de mercado, necessitam estar na linha da frente no que toca a programas de melhoria contínua e de uma gestão orientada para um crescimento rentável e sustentado. Nesta perspetiva, este estudo de dissertação tem como objetivo encontrar uma solução para a gestão de stock e FiFo (First in First out) de pneus em verde na supracitada empresa, situada em Lousado, Vila Nova de Famalicão. Este projeto de dissertação iniciou-se com uma análise e diagnóstico do processo produtivo do pneu, entre a Construção e a Vulcanização. Nesta análise, foi possível identificar vários problemas, sendo o mais crítico associado à logística interna de transporte do pneu “em curso”, de fabrico entre as fases do mesmo, Construção e Vulcanização. Devido a condicionantes estruturais e de organização, a logística interna de transporte entre estes dois sectores enfrenta estrangulamentos nos fluxos, a falta de espaço para acomodar o material em curso, problemas organizacionais de controlo e monitorização do processo produtivo, dificuldades de regulação do fluxo e localização dos carros de transporte dos pneus em verde. Face aos problemas detetados ao longo do estudo, foram analisadas várias soluções para a resolução ou minimização dos mesmos. Entre as soluções propostas salientam-se: o alargamento do sistema de transporte por tapetes rolantes GTC (Green Tire Conveying) a todos os módulos de construção. Esta solução diminui o fluxo de carros para a área da construção, descongestionando a zona próxima do sistema de carregamento automático GTAL (Green Tire Automatic Loading) na vulcanização. A implementação dum sistema Wi-Fi RFID, que permite identificar e localizar artigos em curso utilizando etiquetas inteligentes numa rede wireless, conseguindo melhorar a programação de produção e o respetivo sequenciamento. Sabendo também que a Continental se encontra numa fase de expansão, designada Projeto Route 17/20, as soluções propostas tomaram em consideração essa nova realidade futura. Assim, foram estudados e propostos novos layouts para esse atual processo. Nestes novos layouts, procurou-se uma reorganização dos processos de fabrico, bem como um redimensionamento dos espaços de parqueamento de carros de pneus verdes adequado aos volumes produtivos. De igual forma, adequou-se os espaços físicos à possível implementação de um sistema de FiFo de pneus em verde na planta fabril, quando concluída a expansão. Este trabalho de dissertação apresenta como vantagens diretas da sua implementação: gerar a menor perturbação no atual método de trabalho seguido na empresa; previsivelmente aumentar a eficiência do processo produtivo; potenciar o crescimento tecnológico programado pela empresa; e oferecer uma boa relação custo/benefício no investimento necessário. Como apreciação final, pode-se concluir que este estudo foi finalizado com sucesso, visto que as soluções propostas foram apreciadas positivamente pela Administração da Continental Mabor S.A. e estão correntemente a ser avaliadas pelo grupo.

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Celiac disease (CD) is an autoimmune enteropathy, characterized by an inappropriate T-cell-mediated immune response to the ingestion of certain dietary cereal proteins in genetically susceptible individuals. This disorder presents environmental, genetic, and immunological components. CD presents a prevalence of up to 1% in populations of European ancestry, yet a high percentage of cases remain underdiagnosed. The diagnosis and treatment should be made early since untreated disease causes growth retardation and atypical symptoms, like infertility or neurological disorders. The diagnostic criteria for CD, which requires endoscopy with small bowel biopsy, have been changing over the last few decades, especially due to the advent of serological tests with higher sensitivity and specificity. The use of serological markers can be very useful to rule out clinical suspicious cases and also to help monitor the patients, after adherence to a gluten-free diet. Since the current treatment consists of a life-long glutenfree diet, which leads to significant clinical and histological improvement, the standardization of an assay to assess in an unequivocal way gluten in gluten-free foodstuff is of major importance.

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The first electrochemical immunosensor (EI) for the detection of antibodies against deamidated gliadin peptides (DGP) is described here. A disposable nanohybrid screen-printed carbon electrode modified with DGP was employed as the transducer's sensing surface. Real serumsampleswere successfully assayed and the results were corroborated with an ELISA kit. The presented EI is a promising analytical tool for celiac disease diagnosis.

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The latest medical diagnosis devices enable the performance of e-diagnosis making the access to these services easier, faster and available in remote areas. However this imposes new communications and data interchange challenges. In this paper a new XML based format for storing cardiac signals and related information is presented. The proposed structure encompasses data acquisition devices, patient information, data description, pathological diagnosis and waveform annotation. When compared with similar purpose formats several advantages arise. Besides the full integrated data model it may also be noted the available geographical references for e-diagnosis, the multi stream data description, the ability to handle several simultaneous devices, the possibility of independent waveform annotation and a HL7 compliant structure for common contents. These features represent an enhanced integration with existent systems and an improved flexibility for cardiac data representation.

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This study aims to understand the reality of social service organizations, the level of implementation of the strategic planning as well as the impact of its application on organizational effectiveness. At first, we will group organizations in clusters according to the level of strategic planning implementation and its degree of effectiveness. Secondly, we will analyse all the different groups. Given the growing number of social service organizations and the consequent complexity of their structures, it turns out the need for these organizations adopt formal management techniques. Strategic planning is a valuable strategic management tool and one of its main objectives is to make organizations more effective. Therefore, the research has been conducted in order to determine if strategic planning is implemented in social service organizations and which effects has its application on organizational effectiveness. The survey, applied to 220 social service organizations, allowed us to gather them into different clusters, showing that different levels of strategic planning determine distinct degrees of organizational efficiency. Finally, it should be noted that findings of this research may be essential to decision makers of these organizations, because it was shown that the adoption of strategic planning has a positive influence on organizational effectiveness of social service organizations.

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More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.