Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed. (C) 2011 Elsevier B.V. All rights reserved.

On the efficiency of evolutionary fuzzy clustering

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

Dynamic Fuzzy Logic Control of GeneticAlgorithm Probabilities

Genetic algorithms are commonly used to solve combinatorial optimizationproblems. The implementation evolves using genetic operators (crossover, mutation,selection, etc.). Anyway, genetic algorithms like some other methods have parameters(population size, probabilities of crossover and mutation) which need to be tune orchosen.In this paper, our project is based on an existing hybrid genetic algorithmworking on the multiprocessor scheduling problem. We propose a hybrid Fuzzy-Genetic Algorithm (FLGA) approach to solve the multiprocessor scheduling problem.The algorithm consists in adding a fuzzy logic controller to control and tunedynamically different parameters (probabilities of crossover and mutation), in anattempt to improve the algorithm performance. For this purpose, we will design afuzzy logic controller based on fuzzy rules to control the probabilities of crossoverand mutation. Compared with the Standard Genetic Algorithm (SGA), the resultsclearly demonstrate that the FLGA method performs significantly better.

A fuzzy logic controller for intestinal levodopa infusion in Parkinson’s disease

The aim of this work is to evaluate the fuzzy system for different types of patients for levodopa infusion in Parkinson Disease based on simulation experiments using the pharmacokinetic-pharmacodynamic model. Fuzzy system is to control patient’s condition by adjusting the value of flow rate, and it must be effective on three types of patients, there are three different types of patients, including sensitive, typical and tolerant patient; the sensitive patients are very sensitive to drug dosage, but the tolerant patients are resistant to drug dose, so it is important for controller to deal with dose increment and decrement to adapt different types of patients, such as sensitive and tolerant patients. Using the fuzzy system, three different types of patients can get useful control for simulating medication treatment, and controller will get good effect for patients, when the initial flow rate of infusion is in the small range of the approximate optimal value for the current patient’ type.

DC Motor Speed Control via Fuzzy / Pole Placement / PI Controller

This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulation results of PID controller provide very good results and the controller is further tuned in order to decrease its overshoot error which is common in PID controllers. Further it is purposed that in industrial environment these controllers are better than others controllers as PID controllers are easy to tuned and cheap. Pole placement controller is the best example of control engineering. An addition of integrator reduced the noise disturbances in pole placement controller and this makes it a good choice for industrial applications. The fuzzy controller is introduce with a DC chopper to make the DC motor speed control smooth and almost no steady state error is observed. Another advantage is achieved in fuzzy controller that the simulations of three different controllers are compared and concluded from the results that Fuzzy controller outperforms to PID controller in terms of steady state error and smooth step response. While Pole placement controller have no comparison in terms of controls because designer can change the step response according to nature of control systems, so this controller provide wide range of control over a system. Poles location change the step response in a sense that if poles are near to origin then step response of motor is fast. Finally a GUI of these three controllers are developed which allow the user to select any controller and change its parameters according to the situation.

A fuzzy rule-based decision support system for Duodopa treatment in Parkinson

A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

Um método para detectar falhas incipientes em máquinas rotativas baseado em análise de vibração e lógica Fuzzy

Este trabalho apresenta um método para detectar falhas no funcionamento de máquinas rotativas baseado em alterações no padrão de vibração do sistema e no diagnóstico da condição de operação, por Lógica Fuzzy. As modificações ocorridas são analisadas e servem como parâmetros para predizer falhas incipientes bem como a evolução destas na condição de operação, possibilitando tarefas de manutenção preditiva. Utiliza-se uma estrutura mecânica denominada de Sistema Rotativo (Figura 1), apropriada para as simulações das falhas. Faz-se a aquisição de dados de vibração da máquina usando-se um acelerômetro em chip biaxial de baixa potência. As saídas são lidas diretamente por um contador microprocessador não requerendo um conversor A/D. Um sistema de desenvolvimento para processamento digital de sinais, baseado no microprocessador TMS320C25, o Psi25, é empregado na aquisição dos sinais de vibração (*.dat), do Sistema Rotativo. Os arquivos *.dat são processados através da ferramenta matemática computacional Matlab 5 e do programa SPTOOL. Estabelece-se o padrão de vibração, denominado assinatura espectral do Sistema Rotativo (Figura 2) Os dados são analisados pelo sistema especialista Fuzzy, devidamente calibrado para o processo em questão. São considerados, como parâmetros para a diferenciação e tomada de decisão no diagnóstico do estado de funcionamento pelo sistema especialista, a freqüência de rotação do eixo-volante e as amplitudes de vibração inerentes a cada situação de avaria. As falhas inseridas neste trabalho são desbalanceamentos no eixovolante (Figura 1), através da inserção de elementos desbalanceadores. A relação de massa entre o volante e o menor elemento desbalanceador é de 1:10000. Tomando-se como alusão o conhecimento de especialistas no que se refere a situações normais de funcionamento e conseqüências danosas, utilizam-se elementos de diferentes massas para inserir falhas e diagnosticar o estado de funcionamento pelo sistema fuzzy, que apresenta o diagnóstico de formas qualitativa: normal; falha incipiente; manutenção e perigo e quantitativa, sendo desta maneira possível a detecção e o acompanhamento da evolução da falha.

Development, technological change and innovation, Schumpeter and neo-Schumpeterians

This review essay is devoted to a discussion of some central aspects of the Schumpeterian and neo-Schumpeterian approaches to the dynamic processes of development, technological change and innovation. This essay is organised in two parts. In the first, Schumpeter's insightful distinction between circular flow and development is discussed. In the second, some central elements of the neo-Schumpeterian interpretation and extension of Schumpeter's views are critically outlined, special emphasis being placed on some recent attempts to formalize several of his insights on the cyclical dynamics of the processes of technological change and innovation. I should stress that due to space constraints I will focus primarily upon macrotheoretic issues, thus paying only secondary attention to the neo-Schumpeterian literature on the microeconomics of technological change and to the burgeoning empirical developments along those lines.

Os keynesianos neo-ricardianos e os pós-keynesianos: comentários a Amadeu e Dutt

O objetivo deste "paper" é tecer alguns comentários à leitura que Amadeo e Dutt apresentam em artigo publicado na Pesquisa e Planejamento Econômico, sobre duas vertentes do keynesianismo: a ner-ricardiana e a pós-keynesiana.

A ética em Smith nos neo-clássicos e suas implicações na ética em negócios

Esta pesquisa procurará discutir as relações entre ética em economia e administração. O enfoque adotado demonstrará que a ética da economia clássica representada pelo pensamento de Adam Smith é completamente diferente daquela encontrada nos pensadores neoclássicos representados por Hayek, Von Mises e Friedman. Decorre daí que apesar do mundo dos negócios adotar algumas perspectivas econômicas de Smith, os critérios de avaliação de desempenho empresarial decorrem da economia neoclássica e de forma subjacente incorpora seus valores éticos. Ao se ignorar este relacionamento entre economia e negócios, a discussão sobre ética nos negócios é conduzida por um caminho que impede qualquer consenso ou aplicação prática.