866 resultados para the Fuzzy Colour Segmentation Algorithm


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Pós-graduação em Ciências Ambientais - Sorocaba

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A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Ciências Ambientais - Sorocaba

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This paper presents the application of fuzzy theory to support the decision of implementing energy efficiency program in sawmills operating in the processing of Pinustaeda and Pinuselliotii. The justification of using a system based on fuzzy theory for analysis of consumption and the specific factors involved, such is the diversity of rates / factors. With the fuzzy theory, we can build a reliable system for verifying actual energy efficiency. The indices and factors characteristic of industrial activity were measured and used as the basis for the fuzzy system. We developed a management system and technology. The system involves the management practices in energy efficiency, maintenance of plant and equipment and the presence of qualified staff. The technological system involves the power factor, load factor, the factor of demand and the specific consumption. The first response provides the possibility of increased energy efficiency and the second level of energy efficiency in the industry studied. With this tool, programs can be developed for energy conservation and energy efficiency in the industrial timber with wide application in this area that is as diverse as production processes. The same systems developed can be used in other industrial activities, provided they are used indices and characteristic features of the sectors involved.

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The fuzzy logic accepts infinite intermediate logical values between false and true. In view of this principle, a system based on fuzzy rules was established to provide the best management of Catasetum fimbriatum. For the input of the developed fuzzy system, temperature and shade variables were used, and for the output, the orchid vitality. The system may help orchid experts and amateurs to manage this species. ?Low? (L), ?Medium? (M) and ?High? (H) were used as linguistic variables. The objective of the study was to develop a system based on fuzzy rules to improve management of the Catasetum fimbriatum species, as its production presents some difficulties, and it offers high added value

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Pós-graduação em Ciência da Computação - IBILCE

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The pharmaceutical industry was consolidated in Brazil in the 1930s, and since then has become increasingly competitive. Therefore the implementation of the Toyota Production System, which aims to lean production, has become common among companies in the segment. The main efficiency indicator currently used is the Overall Equipment Effectiveness (OEE). This paper intends to, using the fuzzy model DEA-BCC, analyze the efficiency of the production lines of a pharmaceutical company in the Paraíba Valley, compare the values obtained by the model with those calculated by the OEE, identify the most sensitive machines to variation in the data input and develop a ranking of effectiveness between the consumer machinery. After the development, it is shown that the accuracy of the relationship between the two methods is approximately 57% and the line considered the most effective by the Toyota Production System is not the same as the one found by this paper

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The pharmaceutical industry was consolidated in Brazil in the 1930s, and since then has become increasingly competitive. Therefore the implementation of the Toyota Production System, which aims to lean production, has become common among companies in the segment. The main efficiency indicator currently used is the Overall Equipment Effectiveness (OEE). This paper intends to, using the fuzzy model DEA-BCC, analyze the efficiency of the production lines of a pharmaceutical company in the Paraíba Valley, compare the values obtained by the model with those calculated by the OEE, identify the most sensitive machines to variation in the data input and develop a ranking of effectiveness between the consumer machinery. After the development, it is shown that the accuracy of the relationship between the two methods is approximately 57% and the line considered the most effective by the Toyota Production System is not the same as the one found by this paper

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Backgrounds Ea aims: The boundaries between the categories of body composition provided by vectorial analysis of bioimpedance are not well defined. In this paper, fuzzy sets theory was used for modeling such uncertainty. Methods: An Italian database with 179 cases 18-70 years was divided randomly into developing (n = 20) and testing samples (n = 159). From the 159 registries of the testing sample, 99 contributed with unequivocal diagnosis. Resistance/height and reactance/height were the input variables in the model. Output variables were the seven categories of body composition of vectorial analysis. For each case the linguistic model estimated the membership degree of each impedance category. To compare such results to the previously established diagnoses Kappa statistics was used. This demanded singling out one among the output set of seven categories of membership degrees. This procedure (defuzzification rule) established that the category with the highest membership degree should be the most likely category for the case. Results: The fuzzy model showed a good fit to the development sample. Excellent agreement was achieved between the defuzzified impedance diagnoses and the clinical diagnoses in the testing sample (Kappa = 0.85, p < 0.001). Conclusions: fuzzy linguistic model was found in good agreement with clinical diagnoses. If the whole model output is considered, information on to which extent each BIVA category is present does better advise clinical practice with an enlarged nosological framework and diverse therapeutic strategies. (C) 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

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Background and Purpose: Oropharyngeal dysphagia is a common manifestation in acute stroke. Aspiration resulting from difficulties in swallowing is a symptom that should be considered due to the frequent occurrence of aspiration pneumonia that could influence the patient's recovery as it causes clinical complications and could even lead to the patient's death. The early clinical evaluation of swallowing disorders can help define approaches and avoid oral feeding, which may be detrimental to the patient. This study aimed to create an algorithm to identify patients at risk of developing dysphagia following acute ischemic stroke in order to be able to decide on the safest way of feeding and minimize the complications of stroke using the National Institutes of Health Stroke Scale (NHISS). Methods: Clinical assessment of swallowing was performed in 50 patients admitted to the emergency unit of the University Hospital, Faculty of Medicine of Ribeirao Preto, Sao Paulo, Brazil, with a diagnosis of ischemic stroke, within 48 h after the beginning of symptoms. Patients, 25 females and 25 males with a mean age of 64.90 years (range 26-91 years), were evaluated consecutively. An anamnesis was taken before the patient's participation in the study in order to exclude a prior history of deglutition difficulties. For the functional assessment of swallowing, three food consistencies were used, i.e. pasty, liquid and solid. After clinical evaluation, we concluded whether there was dysphagia. For statistical analysis we used the Fisher exact test, verifying the association between the variables. To assess whether the NIHSS score characterizes a risk factor for dysphagia, a receiver operational characteristics curve was constructed to obtain characteristics for sensitivity and specificity. Results: Dysphagia was present in 32% of the patients. The clinical evaluation is a reliable method of detection of swallowing difficulties. However, the predictors of risk for the swallowing function must be balanced, and the level of consciousness and the presence of preexisting comorbidities should be considered. Gender, age and cerebral hemisphere involved were not significantly associated with the presence of dysphagia. NIHSS, Glasgow Coma Scale, and speech and language changes had a statistically significant predictive value for the presence of dysphagia. Conclusions: The NIHSS is highly sensitive (88%) and specific (85%) in detecting dysphagia; a score of 12 may be considered as the cutoff value. The creation of an algorithm to detect dysphagia in acute ischemic stroke appears to be useful in selecting the optimal feeding route while awaiting a specialized evaluation. Copyright (C) 2012 S. Karger AG, Basel

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The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.