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.

Concentration inequalities and laws of large numbers under epistemic and regular irrelevance

This paper presents concentration inequalities and laws of large numbers under weak assumptions of irrelevance that are expressed using lower and upper expectations. The results build upon De Cooman and Miranda`s recent inequalities and laws of large numbers. The proofs indicate connections between the theory of martingales and concepts of epistemic and regular irrelevance. (C) 2010 Elsevier Inc. 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.

Beyond Numbers THE IMPACT OF GENDER QUOTAS IN LATIN AMERICA

This article considers the impact of electoral quotas for women. Most studies have either focused on whether particular policies increase the numbers of women elected or assessed the extent to which a greater number of women in the legislature produces more gender-sensitive legislation. However, little attention has been paid to the cultural changes that can result from adopting gender quotas. This article argues that, although increasing the number of women in legislatures may improve the attention to gender issues, broader processes are involved. Latin American women`s activism and alliances have been critical in ensuring the expansion of women`s rights and increasing the number of women elected. Quotas, and the debate surrounding their adoption, have provided an incentive for women`s collective action and fostered the politicization of gender issues. An analysis of the impact of quotas, therefore, must recognize these broader impacts.

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.

A fuzzy Reed-Frost model for epidemic spreading

In this paper, we present a fuzzy approach to the Reed-Frost model for epidemic spreading taking into account uncertainties in the diagnostic of the infection. The heterogeneities in the infected group is based on the clinical signals of the individuals (symptoms, laboratorial exams, medical findings, etc.), which are incorporated into the dynamic of the epidemic. The infectivity level is time-varying and the classification of the individuals is performed through fuzzy relations. Simulations considering a real problem with data of the viral epidemic in a children daycare are performed and the results are compared with a stochastic Reed-Frost generalization.

Lower numbers of circulating natural killer T (NK T) cells in individuals with human T lymphotropic virus type 1 (HTLV-1) associated neurological disease

Human T lymphotropic virus type 1 (HTLV-1) infects 10-20 million people worldwide. The majority of infected individuals are asymptomatic; however, approximately 3% develop the debilitating neurological disease HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). There is also currently no cure, vaccine or effective therapy for HTLV-1 infection, and the mechanisms for progression to HAM/TSP remain unclear. NK T cells are an immunoregulatory T cell subset whose frequencies and effector functions are associated critically with immunity against infectious diseases. We hypothesized that NK T cells are associated with HAM/TSP progression. We measured NK T cell frequencies and absolute numbers in individuals with HAM/TSP infection from two cohorts on two continents: Sao Paulo, Brazil and San Francisco, CA, USA, and found significantly lower levels when compared with healthy subjects and/or asymptomatic carriers. Also, the circulating NK T cell compartment in HAM/TSP subjects is comprised of significantly more CD4(+) and fewer CD8(+) cells than healthy controls. These findings suggest that lower numbers of circulating NK T cells and enrichment of the CD4(+) NK T subset are associated with HTLV-1 disease progression.

Equal Numbers of Neuronal and Nonneuronal Cells Make the Human Brain an Isometrically Scaled-Up Primate Brain

The human brain is often considered to be the most cognitively capable among mammalian brains and to be much larger than expected for a mammal of our body size. Although the number of neurons is generally assumed to be a determinant of computational power, and despite the widespread quotes that the human brain contains 100 billion neurons and ten times more glial cells, the absolute number of neurons and glial cells in the human brain remains unknown. Here we determine these numbers by using the isotropic fractionator and compare them with the expected values for a human-sized primate. We find that the adult male human brain contains on average 86.1 +/- 8.1 billion NeuN-positive cells (""neurons"") and 84.6 +/- 9.8 billion NeuN-negative (""nonneuronal"") cells. With only 19% of all neurons located in the cerebral cortex, greater cortical size (representing 82% of total brain mass) in humans compared with other primates does not reflect an increased relative number of cortical neurons. The ratios between glial cells and neurons in the human brain structures are similar to those found in other primates, and their numbers of cells match those expected for a primate of human proportions. These findings challenge the common view that humans stand out from other primates in their brain composition and indicate that, with regard to numbers of neuronal and nonneuronal cells, the human brain is an isometrically scaled-up primate brain. J. Comp. Neurol. 513:532-541, 2009. (c) 2009 Wiley-Liss, Inc.

High numbers of human skin cancers express MMP2 and several integrin genes

Background: Basal cell carcinomas (BCC), squamous cell carcinomas (SCC) and cutaneous malignant melanoma (MM) are solid skin cancers derived from different cell types, with different ability to metastasize. Several subtypes of integrins and matrix metalloproteinases (MMP) have been related to malignization and metastasis processes. This work aimed at a quantitative evaluation of skin cancers expressing eight integrins and MMP2 genes. Methods: Expression of integrins and MMP2 genes was evaluated on fresh tumor biopsies from BCC, SCC and MM, and respective controls, by the reverse transcriptase polychain reaction (RT-PCR) technique. Results: More than 90% tumors expressed alpha 6a, beta 1, beta 3 and beta 6 (non-melanoma), and alpha 5a, alpha 6a and MMP2 (MM). Up to 100% controls also expressed beta 1 and beta 3. The results were significant for alpha 6a in BCC (p = 0.026), alpha 6b in SCC (p = 0.035), alpha 2a in BCC (p = 0.003), beta 5 and beta 6 in BCC (p = 0.005). MMP2 was expressed in 100% MM (p = 0.0004). Conclusion: Integrin subunits alpha 2a and alpha 6a would be interesting targets for BCC anti-tumor therapy, as well as alpha 6b in case of SCC. The elevated number of BCC expressing alpha 2 and alpha 6, and of MM expressing alpha v and MMP2, corroborate literature data.

The numbers of sample design for evaluation of the soil fertility

The determination of the amount of sample units that will compose the sample express the optimization of the workforce, and reduce errors inherent in the report of recommendation and evaluation of soil fertility. This study aimed to determine in three systems use and soil management, the numbers of units samples design, needed to form the composed sample, for evaluation of soil fertility. It was concluded that the number of sample units needed to compose the composed sample to determination the attributes of organic matter, pH, P, K, Ca, Mg, Al and H+Al and base saturation of soil vary by use and soil management and error acceptable to the mean estimate. For the same depth of collected, increasing the number of sample units, reduced the percentage error in estimating the average, allowing the recommendation of 14, 14 and 11 sample in management with native vegetation, pasture cultivation and corn, respectively, for a error 20% on the mean estimate.

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.