47 resultados para MAPE
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II European Conference on Curriculum Studies. "Curriculum studies: Policies, perspectives and practices”. Porto, FPCEUP, October 16th - 17th.
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Resumen tomado de la publicación
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Paciente de 60 años de edad y sexo femenino con esclerodermia y miopía alta bilateral que consulta por estrabismo y ptosis palpebral. El estrabismo consiste en esotropía progresiva con hipotropía de ojo derecho (OD) asociado a miopía alta axial con gran tamaño del globo ocular medido por ecometría ultrasónica que conjuntamente con imágenes de Resonancia Magnética Nuclear (RMN) llevan al diagnóstico de Síndrome MAPE (Miopic Acquired Progressive Esotropia). La hipotropía se diagnostica como heavy eye (ojo pesado). El tratamiento del estrabismo mediante cirugía de retroceso de recto medio derecho con técnica de suturas ajustables corrigió la esotropía mientras que la normalización del trayecto del recto lateral descendido no mejoró la hipotropía en esta paciente. Ésta se compensó parcialmente con el plegamiento ajustable del recto superior. Persiste la ptosis palpebral causada por la esclerodermia.
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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia
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Este artigo relata o desenvolvimento de um modelo de ensino virtual em curso na Universidade dos Açores. Depois de ter sido adotado na lecionação de disciplinas da área da Teoria e Desenvolvimento Curricular em regime de e-learning e b-learning, o modelo foi, no ano académico de 2014/15, estendido à lecionação de outras disciplinas. Além de descrever o modelo e explicar a sua evolução, o artigo destaca a sua adoção no contexto particular de uma disciplina cuja componente online foi lecionada em circunstâncias especialmente desafiadoras. Neste sentido, explica o processo de avaliação da experiência, discute os seus resultados e sugere pistas de melhoria. Essa avaliação enquadra-se num processo de investigação do design curricular – a metodologia que tem sido usada para estudar o desenvolvimento do modelo.
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ECER 2015 "Education and Transition - Contributions from Educational Research", Corvinus University of Budapest from 7 to 11 September 2015.
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Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.
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O principal objectivo deste trabalho assenta em desenvolver modelos de previsão de preços de commodities para assim comparar a capacidade preditiva da simulação de Monte Carlo com a das redes neuronais. A simulação de Monte Carlo é principalmente utilizada para avaliar as opções, já as redes neuronais são utilizadas para fazer previsões, classificações, clustering ou aproximação de funções. Os diversos modelos desenvolvidos foram aplicados na previsão do preço futuro do milho, petróleo, ouro e cobre. Sendo que os horizontes temporais testados neste trabalho foram 1 dia, 5 dias, 20 dias e 60 dias. Através da análise do erro absoluto médio percentual (MAPE) concluiu-se que no geral o modelo individual que apresentou um melhor desempenho preditivo foram as redes neuronais. Contudo, nas previsões a 1 e a 5 dias os resultados obtidos foram semelhantes para ambos os modelos. Para se tentar melhorar os resultados obtidos pelos modelos individuais foram aplicadas algumas técnicas de combinação de modelos. A combinação de modelos demonstrou no geral capacidade para melhorar os resultados dos modelos individuais, porém apenas para o horizonte a 60 dias é que os resultados melhoraram significativamente.
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Dissertação de mestrado em Engenharia de Sistemas
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Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação
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Objective: Health status measures usually have an asymmetric distribution and present a highpercentage of respondents with the best possible score (ceiling effect), specially when they areassessed in the overall population. Different methods to model this type of variables have beenproposed that take into account the ceiling effect: the tobit models, the Censored Least AbsoluteDeviations (CLAD) models or the two-part models, among others. The objective of this workwas to describe the tobit model, and compare it with the Ordinary Least Squares (OLS) model,that ignores the ceiling effect.Methods: Two different data sets have been used in order to compare both models: a) real datacomming from the European Study of Mental Disorders (ESEMeD), in order to model theEQ5D index, one of the measures of utilities most commonly used for the evaluation of healthstatus; and b) data obtained from simulation. Cross-validation was used to compare thepredicted values of the tobit model and the OLS models. The following estimators werecompared: the percentage of absolute error (R1), the percentage of squared error (R2), the MeanSquared Error (MSE) and the Mean Absolute Prediction Error (MAPE). Different datasets werecreated for different values of the error variance and different percentages of individuals withceiling effect. The estimations of the coefficients, the percentage of explained variance and theplots of residuals versus predicted values obtained under each model were compared.Results: With regard to the results of the ESEMeD study, the predicted values obtained with theOLS model and those obtained with the tobit models were very similar. The regressioncoefficients of the linear model were consistently smaller than those from the tobit model. In thesimulation study, we observed that when the error variance was small (s=1), the tobit modelpresented unbiased estimations of the coefficients and accurate predicted values, specially whenthe percentage of individuals wiht the highest possible score was small. However, when theerrror variance was greater (s=10 or s=20), the percentage of explained variance for the tobitmodel and the predicted values were more similar to those obtained with an OLS model.Conclusions: The proportion of variability accounted for the models and the percentage ofindividuals with the highest possible score have an important effect in the performance of thetobit model in comparison with the linear model.
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RESUMOO objetivo foi avaliar o potencial produtivo de cultivares de morangueiro em região representativa do Alto Jequitinhonha. O experimento foi conduzido na fazenda Mape Frutas Ltda., localizada no município de Datas-MG, em delineamento em blocos ao acaso, com oito cultivares de morangueiro em quatro repetições, para verificar a produção de mudas e de frutos. A contagem da produção de estolões e de mudas foi realizada aos 180 dias após o plantio. A avaliação das variáveis relacionadas à produção de frutos foi feita duas vezes por semana, no período de maio a outubro de 2012. Das cultivares de dias curtos (Festival, Campinas, Toyonoka, Dover, Oso Grande e Camarosa) e dias neutros (Diamante e Aromas), apenas Toyonoka foi a que apresentou menor desempenho para as variáveis. A significativa superioridade das cultivares Camarosa e Festival, para praticamente todas as variáveis avaliadas, permite recomendá-las para regiões com características edafoclimáticas semelhantes às da região onde o experimento foi conduzido. Dentre as cultivares avaliadas, as mais precoces tenderam a apresentar maior desempenho para variáveis relacionadas à produção de frutos.
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The main objective of this research was to study the feasibility of incorporating organosolv semi-chemical triticale fibers as the reinforcing element in recycled high density polyethylene (HDPE). In the first step, triticale fibers were characterized in terms of chemical composition and compared with other biomass species (wheat, rye, softwood, and hardwood). Then, organosolv semi-chemical triticale fibers were prepared by the ethanolamine process. These fibers were characterized in terms of its yield, kappa number, fiber length/diameter ratio, fines, and viscosity; the obtained results were compared with those of eucalypt kraft pulp. In the second step, the prepared fibers were examined as a reinforcing element for recycled HDPE composites. Coupled and non-coupled HDPE composites were prepared and tested for tensile properties. Results showed that with the addition of the coupling agent maleated polyethylene (MAPE), the tensile properties of composites were significantly improved, as compared to non-coupled samples and the plain matrix. Furthermore, the influence of MAPE on the interfacial shear strength (IFSS) was studied. The contributions of both fibers and matrix to the composite strength were also studied. This was possible by the use of a numerical iterative method based on the Bowyer-Bader and Kelly-Tyson equations
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Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.