846 resultados para Predicting


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Este trabalho foi realizado com o objetivo de desenvolver um modelo computacional para simular a secagem de frutos café em um secador intermitente de fluxos contracorrente, empregando a linguagem de simulação EXTEND™ e o Modelo de Thompson (THOMPSON; PEART; FOSTER, 1968). Para validação do modelo desenvolvido foram utilizados dados experimentais obtidos por Silva (1991), em que foram empregados três níveis de temperatura do ar de secagem de 60, 80 e 100 °C. O modelo desenvolvido foi validado, sendo constatados desvios absolutos de 1,8% b.u e 1,1 kg e erros relativos de 11% e 1,6% na previsão dos parâmetros teor de água final e consumo de lenha, respectivamente. O modelo validado foi empregado na condução de experimentos tipo comparação de cenários. O primeiro experimento refere a alterações do ciclo operacional em que foram alterados os tempos de movimentação e de parada do fluxo da massa de grãos. E o segundo refere à alteração da configuração do secador quanto às alturas das câmaras de secagem e descanso. O ciclo operacional com os tempos de movimentação de um minuto e de parada de dezesseis minutos, para a temperatura do ar de secagem de 100 °C, proporcionou o melhor desempenho, sendo constatado tempo secagem de 12,3 h, consumo de lenha de 109,5 kg, consumo específico de energia de 7660 kJ.kg-1 de água evaporada, e capacidade de secagem de 87,86 kg.h-1. Quanto à configuração do secador, o melhor desempenho ocorreu para altura da câmara de secagem de 2,3 m usando a temperatura do ar de secagem de 100 °C, em que foram simulados tempo de secagem de 12,0 h, consumo de lenha de 106,5 kg, consumo específico de energia, de 7433 kJ.kg-1 de água evaporada, e capacidade de secagem de 90 kg.h-1. Desse modo, na condução da secagem de frutos de café em um secador intermitente de fluxos contracorrentes é recomendado o ciclo operacional com tempos de movimentação de um minuto e o de parada de dezesseis minutos, e não empregar a câmara de descanso. Essa conclusão está fundamentada em índices de desempenho do secador. Ressalta-se que não foram simulados os impactos nos parâmetros de qualidade.

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Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall by using an intrathoracic convex prosthesis in the substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT scan. This article presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prostheses for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomical variations, the soft-tissue thicknesses external to the ribs show that both symmetric and asymmetric patients always have asymmetric variations, by comparing the patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient’s rib positions and dimensions. The average differences between the skin and costal line curvature lengths were 84 ± 4 mm and 96 ± 11 mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable of predicting and simulating a virtual shape and size of the bar for asymmetric and symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error introduced by the manually bent bar, which only uses a template that copies the chest wall curvature.

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Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall by using an intrathoracic convex prosthesis in the substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT scan. This article presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prostheses for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomical variations, the soft-tissue thicknesses external to the ribs show that both symmetric and asymmetric patients always have asymmetric variations, by comparing the patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient’s rib positions and dimensions. The average differences between the skin and costal line curvature lengths were 84 ± 4 mm and 96 ± 11 mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable of predicting and simulating a virtual shape and size of the bar for asymmetric and symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error introduced by the manually bent bar, which only uses a template that copies the chest wall curvature.

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Pectus excavatum is the most common deformity of the thorax. A minimally invasive surgical correction is commonly carried out to remodel the anterior chest wall by using an intrathoracic convex prosthesis in the substernal position. The process of prosthesis modeling and bending still remains an area of improvement. The authors developed a new system, i3DExcavatum, which can automatically model and bend the bar preoperatively based on a thoracic CT scan. This article presents a comparison between automatic and manual bending. The i3DExcavatum was used to personalize prostheses for 41 patients who underwent pectus excavatum surgical correction between 2007 and 2012. Regarding the anatomical variations, the soft-tissue thicknesses external to the ribs show that both symmetric and asymmetric patients always have asymmetric variations, by comparing the patients’ sides. It highlighted that the prosthesis bar should be modeled according to each patient’s rib positions and dimensions. The average differences between the skin and costal line curvature lengths were 84 ± 4 mm and 96 ± 11 mm, for male and female patients, respectively. On the other hand, the i3DExcavatum ensured a smooth curvature of the surgical prosthesis and was capable of predicting and simulating a virtual shape and size of the bar for asymmetric and symmetric patients. In conclusion, the i3DExcavatum allows preoperative personalization according to the thoracic morphology of each patient. It reduces surgery time and minimizes the margin error introduced by the manually bent bar, which only uses a template that copies the chest wall curvature.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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Nanotechnology is the manipulation of matter on na almost atomic scale to produce new structures, materials, and devices. As potential occupational exposure to nanomaterials (NMs) becomes more prevalente, it is importante that the principles of medical surveillance and risk management be considered for workers in the nanotechnology industry.However, much information about health risk is beyond our current knowledge. Thus, NMs presente new challenges to understanding, predicting, andmanageing potential health risks. First, we briefly describe some general features of NMs and list the most importante types of NMs. This review discusses the toxicological potential of NMs by comparing possible injury mechanism and know, or potentially adverse, health effects. We review the limited research to date for occupational exposure to these particles and how a worker might be exposed to NMs. The principles of medical surveillance are reviewed to further the discussion of occupational health surveillance are reviewed to further the discussion of occupational health surveillance for workers exposed to NMs. We outlinehow occupational health professionals could contribute to a better knowledge of health effects by the utilization of a health surveillance program and by minimizing exposure. Finally, we discuss the early steps towards regulation and the difficulties facing regulators in controlling potentially harmful exposures in the absence of suficiente scientific evidence.

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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

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The purpose of this study is to investigate the contribution of psychological variables and scales suggested by Economic Psychology in predicting individuals’ default. Therefore, a sample of 555 individuals completed a self-completion questionnaire, which was composed of psychological variables and scales. By adopting the methodology of the logistic regression, the following psychological and behavioral characteristics were found associated with the group of individuals in default: a) negative dimensions related to money (suffering, inequality and conflict); b) high scores on the self-efficacy scale, probably indicating a greater degree of optimism and over-confidence; c) buyers classified as compulsive; d) individuals who consider it necessary to give gifts to children and friends on special dates, even though many people consider this a luxury; e) problems of self-control identified by individuals who drink an average of more than four glasses of alcoholic beverage a day.

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This study demonstrates and applies a social network methodology for studying the dynamics of hierarchies in organizations. Social network (blockmodel) analysis of verbal networks in four hospitals contrasted hierarchical and structurally equivalent partitions of the sociomatrices of frequent ties and perceptions of organizational culture. It was found that the verbal networks in these organizations follow a center periphery pattern rather than a hierarchical logic and that perceptions of culture vary more by verbal network than by formal hierarchy. The perceptions of culture of central groups in one organization are much like those of peripheral groups in another. In all four hospitals, structurally equivalent social networks are more important in predicting subcultures than are hierarchical groupings and hierarchy has a limited impact on the development of verbal networks. These findings suggest the value of an amoeba rather than a pyramid metaphor in interpreting the cultures and relational structures of organizations.

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RESUMO: A morte de um filho às mãos da sua mãe ou de uma mãe às mãos do seu filho, é uma realidade rara que provoca uma reacção colectiva de choque e repulsa. Por seu turno, a comunidade cientifica procura explicações, classificações e formas de prever e evitar novas tragédias. No presente estudo foram objecto de análise cinco casos de filicídio e seis casos de matricídio, tendo-se procedido à avaliação de características de personalidade e enquadramento social e familiar, através da realização de uma entrevista e a aplicação de dois testes de personalidade, um teste de inteligência geral e um teste de impulsividade. Com excepção de 4 casos de matricidas, os restantes sujeitos não apresentaram problemas mentais graves nem marcada perturbação anti-social de personalidade, sendo os factores determinantes mais comuns de natureza social e familiar, que, associados às respectivas características de personalidade e nível de inteligência, conduziram os sujeitos ao acto, levando a concluir pela necessidade do reforço das políticas sociais e de saúde mental, bem como, da necessidade de um maior conhecimento do sujeito que pratica o crime por parte de quem tem a responsabilidade de o julgar e de quem tem o encargo de o reabilitar. ABSTRACT: The death of a child at the hands of its mother or of a mother at the hands of her child is a rare reality that causes a collective reaction of shock and disgust. In turn, the scientific community seeks explanations, classifications and ways of predicting and preventing further tragedies. The current study examined five cases of filicide and six cases of matricide, and personality characteristics and social and family frameworks were assessed, through the application of an interview, two personality tests, a general intelligence test and an impulsivity test. With the exception of 4 cases of matricide, the remaining subjects did not show any serious mental problems or severe anti-social personality disturbance, the most common factors being of social and family nature. These factors, combined with their personality characteristics and intelligence level, led the subjects to the act, thus showing the need to strengthen social and mental health policies, as well as the need for a greater knowledge on the subject who commits the offence, from the part of those who are responsible for judging him and of those who are in charge of rehabilitating him.

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RESUMO: A presente investigação erige como objective inicial predizer as potencialidades/qualidades avaliativas da Grelha de Observação (Louro, 2005), realçando os diferentes comportamentos, a nível verbal e não-verbal, presentes em tribunal, relativamente aos arguidos, vítimas, testemunhas e juízes, num conjunto 34 julgamentos presenciados, no tribunal da Boa-Hora, 4ª Vara Criminal. Nesta medida, foram preenchidas 249 grelhas em contexto judicial, 190 do sexo feminino e 59 do sexo masculino, das quais, 43 grelhas referiam-se a arguidos dispostos 34 julgamentos, devido ao facto de haver julgamentos com mais do que um arguido; 14 a vítimas, dado a maior parte dos julgamentos a vítima fazer-se representar pelo Ministério Público; 108 a testemunhas e 73 grelhas aplicadas a 4 juízes presidentes de cada colectivo. Verificaram-se diferenças estatisticamente significativas no que toca aos comportamentos verbal e não verbal apresentados pelas personagens judiciais. Os resultados foram apoiados e discutidos com base na literatura revista. ABSTRACT: The present investigation aims at predicting the evaluative potential/quality of the Grelha de Observação (Louro, 2005), highlighting the different behaviors (verbal and non-verbal) displayed in a court of law, regarding the arguidos, victims, witnesses and judges, in a set of 34 observed trials at the court of Boa-Hora, “4rd” Vara Criminal. Therefore, 249 grills were filled in judicial contxt, 190 females and 59 males, from which, 43 grills were arguidos from the 34 trials (in some trials, there were more than one arguido); 14 regarding victims, since most trials she is represented by the public prosecution service; 108 witnesses and 73 grills were applied to 4 judges presidents from each collective jury. Statistically significant differences were found for the comparison between judicial characters for verbal and non-verbal behavior. The results were supported and discussed from the revised literature.

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Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

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O trabalho que a seguir se apresenta tem como objectivo descrever a criação de um modelo que sirva de suporte a um sistema de apoio à decisão sobre o risco inerente à execução de projectos na área das Tecnologias de Informação (TI) recorrendo a técnicas de mineração de dados. Durante o ciclo de vida de um projecto, existem inúmeros factores que contribuem para o seu sucesso ou insucesso. A responsabilidade de monitorizar, antever e mitigar esses factores recai sobre o Gestor de Projecto. A gestão de projectos é uma tarefa difícil e dispendiosa, consome muitos recursos, depende de numerosas variáveis e, muitas vezes, até da própria experiência do Gestor de Projecto. Ao ser confrontado com as previsões de duração e de esforço para a execução de uma determinada tarefa, o Gestor de Projecto, exceptuando a sua percepção e intuição pessoal, não tem um modo objectivo de medir a plausibilidade dos valores que lhe são apresentados pelo eventual executor da tarefa. As referidas previsões são fundamentais para a organização, pois sobre elas são tomadas as decisões de planeamento global estratégico corporativo, de execução, de adiamento, de cancelamento, de adjudicação, de renegociação de âmbito, de adjudicação externa, entre outros. Esta propensão para o desvio, quando detectada numa fase inicial, pode ajudar a gerir melhor o risco associado à Gestão de Projectos. O sucesso de cada projecto terminado foi qualificado tendo em conta a ponderação de três factores: o desvio ao orçamentado, o desvio ao planeado e o desvio ao especificado. Analisando os projectos decorridos, e correlacionando alguns dos seus atributos com o seu grau de sucesso o modelo classifica, qualitativamente, um novo projecto quanto ao seu risco. Neste contexto o risco representa o grau de afastamento do projecto ao sucesso. Recorrendo a algoritmos de mineração de dados, tais como, árvores de classificação e redes neuronais, descreve-se o desenvolvimento de um modelo que suporta um sistema de apoio à decisão baseado na classificação de novos projectos. Os modelos são o resultado de um extensivo conjunto de testes de validação onde se procuram e refinam os indicadores que melhor caracterizam os atributos de um projecto e que mais influenciam o risco. Como suporte tecnológico para o desenvolvimento e teste foi utilizada a ferramenta Weka 3. Uma boa utilização do modelo proposto possibilitará a criação de planos de contingência mais detalhados e uma gestão mais próxima para projectos que apresentem uma maior propensão para o risco. Assim, o resultado final pretende constituir mais uma ferramenta à disposição do Gestor de Projecto.

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Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular. Área de especialização: Intervenção Cardiovascular.

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OBJECTIVE: To identify potential prognostic factors for neonatal mortality among newborns referred to intensive care units. METHODS: A live-birth cohort study was carried out in Goiânia, Central Brazil, from November 1999 to October 2000. Linked birth and infant death certificates were used to ascertain the cohort of live born infants. An additional active surveillance system of neonatal-based mortality was implemented. Exposure variables were collected from birth and death certificates. The outcome was survivors (n=713) and deaths (n=162) in all intensive care units in the study period. Cox's proportional hazards model was applied and a Receiver Operating Characteristic curve was used to compare the performance of statistically significant variables in the multivariable model. Adjusted mortality rates by birth weight and 5-min Apgar score were calculated for each intensive care unit. RESULTS: Low birth weight and 5-min Apgar score remained independently associated to death. Birth weight equal to 2,500g had 0.71 accuracy (95% CI: 0.65-0.77) for predicting neonatal death (sensitivity =72.2%). A wide variation in the mortality rates was found among intensive care units (9.5-48.1%) and two of them remained with significant high mortality rates even after adjusting for birth weight and 5-min Apgar score. CONCLUSIONS: This study corroborates birth weight as a sensitive screening variable in surveillance programs for neonatal death and also to target intensive care units with high mortality rates for implementing preventive actions and interventions during the delivery period.