Dweller perception using fuzzy logic for slum upgrading

A large number of initiatives in cities in Brazil - including slum clearance and upgrading - have been undertaken over the years in an effort to ameliorate the problems arising from informal occupation; unfortunately, however, little is known about the related performance outcomes. Careful appraisal of the results of such initiatives is thus called for, covering evaluations of dwellers` perceptions of the upgraded environments. Among the available evaluation methods, post-occupancy evaluation (POE) is commonly employed, although it fails adequately to reflect prevailing subjective concepts of quality. The present paper contains the partial findings of a research exercise aimed at developing an original method, using fuzzy logic, for urban environmental quality evaluation in informally occupied areas on the basis of combining quantitative indicators and dweller perception. It combines POE with fuzzy logic in order to develop tools that can better model the uncertain information that emerges from that kind of study. This paper aims to introduce an uncertainty measure used in order to identify the strengths and weaknesses of slum upgrading projects. The results show that it is possible to quantify certainty degrees in the findings and to define if additional information is needed.

Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.

Fuzzy computational control for real Chua circuit

We preserit a computational procedure to control art experimental chaotic system by applying the occasional proportional feedback (OPF) method. The method implementation uses the fuzzy theory to relate the variable correction to the necessary adjustment in the control parameter. As an application We control the chaotic attractors of the Chua circuit. We present file developed circuits and algorithms to implement this control in real time. To simplify the used procedure, we use it low resolution analog to digital converter compensated for a lowpass filter that facilitates similar applications to control other systems. (C) 2007 Elsevier Ltd. All rights reserved.

HYBRID AND INCREMENTAL FUZZY LEARNING FOR HUMAN SKIN DETECTION

In this paper, a framework for detection of human skin in digital images is proposed. This framework is composed of a training phase and a detection phase. A skin class model is learned during the training phase by processing several training images in a hybrid and incremental fuzzy learning scheme. This scheme combines unsupervised-and supervised-learning: unsupervised, by fuzzy clustering, to obtain clusters of color groups from training images; and supervised to select groups that represent skin color. At the end of the training phase, aggregation operators are used to provide combinations of selected groups into a skin model. In the detection phase, the learned skin model is used to detect human skin in an efficient way. Experimental results show robust and accurate human skin detection performed by the proposed framework.

Expert system for the assessment of power transformer insulation condition based on type-2 fuzzy logic systems

An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

Fuzzy risk index for power transformer failures due to external short-circuits

A novel methodology to assess the risk of power transformer failures caused by external faults, such as short-circuit, taking the paper insulation condition into account, is presented. The risk index is obtained by contrasting the insulation paper condition with the probability that the transformer withstands the short-circuit current flowing along the winding during an external fault. In order to assess the risk, this probability and the value of the degree of polymerization of the insulating paper are regarded as inputs of a type-2 fuzzy logic system (T2-FLS), which computes the fuzzy risk level. A Monte Carlo simulation has been used to find the survival function of the currents flowing through the transformer winding during a single-phase or a three-phase short-circuit. The Roy Billinton Test System and a real power system have been used to test the results. (C) 2008 Elsevier B.V. All rights reserved.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

A calibration approach based on Takagi-Sugeno fuzzy inference system for digital electronic compasses

Recently, the development of industrial processes brought on the outbreak of technologically complex systems. This development generated the necessity of research relative to the mathematical techniques that have the capacity to deal with project complexities and validation. Fuzzy models have been receiving particular attention in the area of nonlinear systems identification and analysis due to it is capacity to approximate nonlinear behavior and deal with uncertainty. A fuzzy rule-based model suitable for the approximation of many systems and functions is the Takagi-Sugeno (TS) fuzzy model. IS fuzzy models are nonlinear systems described by a set of if then rules which gives local linear representations of an underlying system. Such models can approximate a wide class of nonlinear systems. In this paper a performance analysis of a system based on IS fuzzy inference system for the calibration of electronic compass devices is considered. The contribution of the evaluated IS fuzzy inference system is to reduce the error obtained in data acquisition from a digital electronic compass. For the reliable operation of the TS fuzzy inference system, adequate error measurements must be taken. The error noise must be filtered before the application of the IS fuzzy inference system. The proposed method demonstrated an effectiveness of 57% at reducing the total error based on considered tests. (C) 2011 Elsevier Ltd. All rights reserved.

Could Cyclophosphamide exert a protective role avoiding esophagic neuron loss in Calomys callosus infected with Trypanosoma cruzi?

The protective role of Cyclophosphamide was studied in this work. Young male Calomys callosus were infected with Trypanosoma cruzi and allowed to age. Cyclophosphamide therapy was administered to animals during acute and late chronic phases of infection. Esophageal neurons were counted, displaying enhanced neuronal loss for the young and treated infected groups. For aged and cyclophosphamide treated animals, a protection was observed through a reduced loss of neurons as compared to the young and infected groups. Enhanced nitric oxide concentrations were observed for young animals as compared to aged counterparts. Splenocyte proliferation was reduced during the acute phase in comparison with those found in the chronic phase. Morphometry of neuronal body displayed a significant reduction concerning the area, perimeter, diameter and volume for aged animals as compared to young groups. These results indicate that the protective effects of cyclophosphamide together with process of neuroplasty of peripheral nervous system could lead to a protection against neuronal loss.

Effects of alcohol exposure during early life on neuron numbers in the rat hippocampus. I. Hilus neurons and granule cells

We previously showed that 16-day-old rats exposed to a relatively high dose of ethanol at 10-15 postnatal days of age have fewer neurons in the hilus region of the hippocampus compared with controls. Dentate gyrus granule cell numbers, however, showed no statistically significant changes attributable to the ethanol treatment. It is possible that some of the changes in brain morphology, brought about as a result of the exposure to ethanol during early life, may not be manifested until later in life. This question has been further addressed in an extension to our previous study. Wistar rats were exposed to a relatively high daily dose of ethanol on postnatal days 10-15 by placement in a chamber containing ethanol vapour, for 3 h/day. The blood ethanol concentration was found to be similar to430 mg/dl at the end of the period of exposure. Groups of ethanol-treated (ET), separation control (SC), and mother-reared control (MRC) rats were anaesthetised and killed either at 16 or 30 days of age by perfusion with phosphate-buffered 2.5% glutaraldehyde. The Cavalieri principle and the physical disector methods were used to estimate, respectively, the regional volumes and neuron cell numerical densities in the hilus and granule cell regions of the dentate gyrus. The total numbers of neurons in the hilus region and granule cell layer were computed from these estimates. It was found that 16-day-old animals had 398,000-441,000 granule cells, irrespective of group. The numbers of granule cells increased such that by 30 days of age, rats had 487,000-525,500 granule cells. However, there were no significant differences between ethanol-treated rats and their age-matched controls in granule cell numbers. In contrast, ethanol-treated rats had slightly but significantly fewer neurons in the hilus region than did control animals at 16 days of age, but not at 30 days of age. Therefore, it appears that a short period of ethanol exposure during early life can have effects on neuron numbers of some hippocampal neurons, but not others. The effects on hilar neuron numbers, observed as a result of such short periods of ethanol treatment, appeared to be transitory. (C) 2003 Wiley-Liss, Inc.

A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

Substrate-bound carbohydrates stimulate signal transduction and neurite outgrowth in an olfactory neuron cell line

SUBPOPULATIONS of olfactory receptor neurons, which are dispersed throughout the olfactory neuroepithelium, express specific cell surface carbohydrates and project to discrete regions of the olfactory bulb. Cell surface carbohydrates such as N-acetyl-lactosamine have been postulated to mediate sorting and selective fasciculation of discrete axon subpopulations during development of the olfactory pathway. Substrate-bound N-acetyl-lactosamine promotes neurite outgrowth by both clonal olfactory receptor neuron cell lines and olfactory receptor neurons in vitro, indicating that cell surface carbohydrates may be ligands for receptor-mediated stimulation of axon growth in vivo. In the present study, the role of transmembrane signaling in N-acetyl-lactosamine-stimulated neurite outgrowth was examined in the clonal olfactory neuron cell line 4.4.2. Substrate-bound N-acetyl-lactosamine stimulated neurite outgrowth which was specifically inhibited by antagonists to N- and L-type calcium channels and to tyrosine kinase phosphorylation. These results indicate that N-acetyl-lactosamine can evoke transmembrane receptor-mediated responses capable of influencing neurite outgrowth.

Model for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic

Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.