Plataforma computacional fuzzy para avaliação nos estágios do tomateiro dos efeitos da irrigação e salinidade da água

Pós-graduação em Agronegócio e Desenvolvimento - Tupã

Análise envoltória de dados combinada com a lógica fuzzy em problemas de avaliação de eficiência de máquinas de consumo: um estudo em empresa do segmento farmacêutico

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

Modelagem fuzzy de dados climáticos estimados por modelo matemático - CCATT-BRAMS

Pós-graduação em Engenharia Mecânica - FEG

Análise envoltória de dados combinada com a lógica fuzzy em problemas de avaliação de eficiência de máquinas de consumo: um estudo em empresa do segmento farmacêutico

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

Modelagem fuzzy de dados climáticos estimados por modelo matemático - CCATT-BRAMS

Pós-graduação em Engenharia Mecânica - FEG

Fuzzy linguistic model for bioelectrical impedance vector analysis

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.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

Fuzzy Connectedness Image Segmentation in Graph Cut Formulation: A Linear-Time Algorithm and a Comparative Analysis

A deep theoretical analysis of the graph cut image segmentation framework presented in this paper simultaneously translates into important contributions in several directions. The most important practical contribution of this work is a full theoretical description, and implementation, of a novel powerful segmentation algorithm, GC(max). The output of GC(max) coincides with a version of a segmentation algorithm known as Iterative Relative Fuzzy Connectedness, IRFC. However, GC(max) is considerably faster than the classic IRFC algorithm, which we prove theoretically and show experimentally. Specifically, we prove that, in the worst case scenario, the GC(max) algorithm runs in linear time with respect to the variable M=|C|+|Z|, where |C| is the image scene size and |Z| is the size of the allowable range, Z, of the associated weight/affinity function. For most implementations, Z is identical to the set of allowable image intensity values, and its size can be treated as small with respect to |C|, meaning that O(M)=O(|C|). In such a situation, GC(max) runs in linear time with respect to the image size |C|. We show that the output of GC(max) constitutes a solution of a graph cut energy minimization problem, in which the energy is defined as the a"" (a) norm ayenF (P) ayen(a) of the map F (P) that associates, with every element e from the boundary of an object P, its weight w(e). This formulation brings IRFC algorithms to the realm of the graph cut energy minimizers, with energy functions ayenF (P) ayen (q) for qa[1,a]. Of these, the best known minimization problem is for the energy ayenF (P) ayen(1), which is solved by the classic min-cut/max-flow algorithm, referred to often as the Graph Cut algorithm. We notice that a minimization problem for ayenF (P) ayen (q) , qa[1,a), is identical to that for ayenF (P) ayen(1), when the original weight function w is replaced by w (q) . Thus, any algorithm GC(sum) solving the ayenF (P) ayen(1) minimization problem, solves also one for ayenF (P) ayen (q) with qa[1,a), so just two algorithms, GC(sum) and GC(max), are enough to solve all ayenF (P) ayen (q) -minimization problems. We also show that, for any fixed weight assignment, the solutions of the ayenF (P) ayen (q) -minimization problems converge to a solution of the ayenF (P) ayen(a)-minimization problem (ayenF (P) ayen(a)=lim (q -> a)ayenF (P) ayen (q) is not enough to deduce that). An experimental comparison of the performance of GC(max) and GC(sum) algorithms is included. This concentrates on comparing the actual (as opposed to provable worst scenario) algorithms' running time, as well as the influence of the choice of the seeds on the output.

Speed Neuro-fuzzy Estimator Applied To Sensorless Induction Motor Control

This work proposes the development of an Adaptive Neuro-fuzzy Inference System (ANFIS) estimator applied to speed control in a three-phase induction motor sensorless drive. Usually, ANFIS is used to replace the traditional PI controller in induction motor drives. The evaluation of the estimation capability of the ANFIS in a sensorless drive is one of the contributions of this work. The ANFIS speed estimator is validated in a magnetizing flux oriented control scheme, consisting in one more contribution. As an open-loop estimator, it is applied to moderate performance drives and it is not the proposal of this work to solve the low and zero speed estimation problems. Simulations to evaluate the performance of the estimator considering the vector drive system were done from the Matlab/Simulink(R) software. To determine the benefits of the proposed model, a practical system was implemented using a voltage source inverter (VSI) to drive the motor and the vector control including the ANFIS estimator, which is carried out by the Real Time Toolbox from Matlab/Simulink(R) software and a data acquisition card from National Instruments.

Modeling and measuring the spatial relation "along": Regions, contours and fuzzy sets

The analysis of spatial relations among objects in an image is an important vision problem that involves both shape analysis and structural pattern recognition. In this paper, we propose a new approach to characterize the spatial relation along, an important feature of spatial configurations in space that has been overlooked in the literature up to now. We propose a mathematical definition of the degree to which an object A is along an object B, based on the region between A and B and a degree of elongatedness of this region. In order to better fit the perceptual meaning of the relation, distance information is included as well. In order to cover a more wide range of potential applications, both the crisp and fuzzy cases are considered. In the crisp case, the objects are represented in terms of 2D regions or ID contours, and the definition of the alongness between them is derived from a visibility notion and from the region between the objects. However, the computational complexity of this approach leads us to the proposition of a new model to calculate the between region using the convex hull of the contours. On the fuzzy side, the region-based approach is extended. Experimental results obtained using synthetic shapes and brain structures in medical imaging corroborate the proposed model and the derived measures of alongness, thus showing that they agree with the common sense. (C) 2011 Elsevier Ltd. All rights reserved.

Ecosystem approach and the Fuzzy logic: a dialectical proposal for information on Environmental Health

The ever-growing production and the problematization of Environmental Health have shown the need to apprehend complex realities and deal with uncertainties from the most diversified instruments which may even incorporate local aspects and subjectivities by means of qualitative realities, while broadening the capacity of the information system. This paper presents a view on the reflection upon some challenges and possible convergences between the ecosystemic approach and the Fuzzy logic in the process of dealing with scientific information and decision-making in Environmental Health.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.

Regulación de la proliferación tumoral y la apoptosis en tumores epidermoides de cavidad oral: papel del receptor para el factor de crecimiento insulínico tipo 1 (IGF-1R) y major vault proteína (MVP)

Programa de doctorado: Cáncer: Biología y Clínica

La matematica fuzzy nell'ingegneria dei materiali. Applicazioni alla durevolezza e alla conservazione dei materiali in opera nei siti archeologici

La ricerca presentata è un’ampia esplorazione delle possibili applicazioni di concetti, metodi e procedure della Fuzzy Logic all’Ingegneria dei Materiali. Tale nuovo approccio è giustificato dalla inadeguatezza dei risultati conseguiti con i soli metodi tradizionali riguardo alla reologia ed alla durabilità, all’utilizzo di dati di laboratorio nella progettazione e alla necessità di usare un linguaggio (informatizzabile) che consenta una valutazione congiunta degli aspetti tecnici, culturali, economici, paesaggistici della progettazione. – In particolare, la Fuzzy Logic permette di affrontare in modo razionale l’aleatorietà delle variabili e dei dati che, nel settore specifico dei materiali in opera nel costruito dei Beni Culturali, non possono essere trattati con i metodi statistici ordinari. – La scelta di concentrare l’attenzione su materiali e strutture in opera in siti archeologici discende non solo dall’interesse culturale ed economico connesso ai sempre più numerosi interventi in questo nuovo settore di pertinenza dell’Ingegneria dei Materiali, ma anche dal fatto che, in tali contesti, i termini della rappresentatività dei campionamenti, della complessità delle interazioni tra le variabili (fisiche e non), del tempo e quindi della durabilità sono evidenti ed esasperati. – Nell’ambito di questa ricerca si è anche condotto un ampio lavoro sperimentale di laboratorio per l’acquisizione dei dati utilizzati nelle procedure di modellazione fuzzy (fuzzy modeling). In tali situazioni si è operato secondo protocolli sperimentali standard: acquisizione della composizione mineralogica tramite diffrazione di raggi X (XRD), definizione della tessitura microstrutturale con osservazioni microscopiche (OM, SEM) e porosimetria tramite intrusione forzata di mercurio (MIP), determinazioni fisiche quali la velocità di propagazione degli ultrasuoni e rotoviscosimetria, misure tecnologiche di resistenza meccanica a compressione uniassiale, lavorabilità, ecc. – Nell’elaborazione dei dati e nella modellazione in termini fuzzy, la ricerca è articolata su tre livelli: a. quello dei singoli fenomeni chimico-fisici, di natura complessa, che non hanno trovato, a tutt’oggi, una trattazione soddisfacente e di generale consenso; le applicazioni riguardano la reologia delle dispersioni ad alto tenore di solido in acqua (calci, cementi, malte, calcestruzzi SCC), la correlazione della resistenza a compressione, la gelività dei materiali porosi ed alcuni aspetti della durabilità del calcestruzzo armato; b. quello della modellazione della durabilità dei materiali alla scala del sito archeologico; le applicazioni presentate riguardano i centri di cultura nuragica di Su Monte-Sorradile, GennaMaria-Villanovaforru e Is Paras-Isili; c. quello della scelta strategica costituita dalla selezione del miglior progetto di conservazione considerando gli aspetti connessi all’Ingegneria dei Materiali congiuntamente a quelli culturali, paesaggistici ed economici; le applicazioni hanno riguardato due importanti monumenti (Anfiteatro e Terme a Mare) del sito Romano di Nora-Pula.