Real-time process plant fault diagnosis

Operators can become confused while diagnosing faults in process plant while in operation. This may prevent remedial actions being taken before hazardous consequences can occur. The work in this thesis proposes a method to aid plant operators in systematically finding the causes of any fault in the process plant. A computer aided fault diagnosis package has been developed for use on the widely available IBM PC compatible microcomputer. The program displays a coloured diagram of a fault tree on the VDU of the microcomputer, so that the operator can see the link between the fault and its causes. The consequences of the fault and the causes of the fault are also shown to provide a warning of what may happen if the fault is not remedied. The cause and effect data needed by the package are obtained from a hazard and operability (HAZOP) study on the process plant. The result of the HAZOP study is recorded as cause and symptom equations which are translated into a data structure and stored in the computer as a file for the package to access. Probability values are assigned to the events that constitute the basic causes of any deviation. From these probability values, the a priori probabilities of occurrence of other events are evaluated. A top-down recursive algorithm, called TDRA, for evaluating the probability of every event in a fault tree has been developed. From the a priori probabilities, the conditional probabilities of the causes of the fault are then evaluated using Bayes' conditional probability theorem. The posteriori probability values could then be used by the operators to check in an orderly manner the cause of the fault. The package has been tested using the results of a HAZOP study on a pilot distillation plant. The results from the test show how easy it is to trace the chain of events that leads to the primary cause of a fault. This method could be applied in a real process environment.

Deriving a fixpoint computation algorithm for top-down abstract interpretation of logic programs

Bruynooghe described a framework for the top-down abstract interpretation of logic programs. In this framework, abstract interpretation is carried out by constructing an abstract and-or tree in a top-down fashion for a given query and program. Such an abstract interpreter requires fixpoint computation for programs which contain recursive predicates. This paper presents in detail a fixpoint algorithm that has been developed for this purpose and the motivation behind it. We start off by describing a simple-minded algorithm. After pointing out its shortcomings, we present a series of refinements to this algorithm, until we reach the final version. The aim is to give an intuitive grasp and provide justification for the relative complexity of the final algorithm. We also present an informal proof of correctness of the algorithm and some results obtained from an implementation.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Estudo da correlação entre coordenação motora e habilidades motoras de pessoas com sindrome de down

Universidade Estadual de Campinas . Faculdade de Educação Física

Alterações do equilíbrio em indivíduos com ou sem síndrome de Down em repouso e durante a execução de uma tarefa

O equilíbrio é fundamental para o desempenho de Actividades de Vida Diária e de Vida Diária Instrumentais que permitem aos indivíduos com Síndrome de Down manter a sua autonomia. O objectivo principal deste estudo foi verificar as características do estado de equilíbrio em indivíduos com e sem Síndrome de Down, em repouso e durante a execução de uma tarefa, de modo a compreender as implicações da alteração do estado de equilíbrio no desempenho de actividades. Neste estudo, foram seleccionadas duas amostras, de forma probabilística por conveniência, com indivíduos de ambos os sexos. A amostra do grupo experimental foi constituída por oito indivíduos com diagnóstico de Síndrome de Down, com idades compreendidas entre os 17 e os 39 anos de idade. A amostra do grupo de controlo foi constituída por doze indivíduos sem patologia, com idades compreendidas entre os 21 e os 37 anos. O equilíbrio foi avaliado com recurso a uma Plataforma de Forças (Bertec Corporation FP4060-10) para medir a deslocação do centro de pressão (CP) dos indivíduos. A avaliação do equilíbrio decorreu em dois momentos, na posição de pé: em repouso e no desempenho da tarefa segurar um saco de compras. Os resultados diferem entre os dois grupos em repouso e durante a execução da tarefa (segurar no saco). Os valores das variáveis área e distância de deslocação do CP e oscilações corporais, antero-posterior e médio-lateralmente apresentam resultados significativos, o que sugere diferenças do estado de equilíbrio entre as amostras.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Comparação entre o pencil beam convolution algorithm e o analytical anisotropic algorithm em tumores de mama

Mestrado em Radioterapia

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Cytomegalovirus infection in children with Down syndrome in a day-care center in Brazil

This study evaluates the transmission of CMV infection in 120 children aged 1 to 15 years with Down syndrome who attended a day-care center for handicapped children in São Paulo, Brazil. A blood sample was obtained from each children at the beginning of the study for detection of IgG and IgM cytomegalovirus (CMV) antibodies by an immunofluorescence assay. Samples of saliva and urine were obtained every 3 months from the children with CMV antibodies to detect shedding of the virus by culture in human foreskin fibroblasts, by detection of pp65 CMV-antigen and by a nested PCR assay. The prevalence of anti CMV-IgG antibodies was 76.6% (92/120), and IgM anti-CMV antibodies were detected in 13% (12/92) of the seropositive children. During the first viral evaluation, CMV was detected in the urine and/or saliva in 39/90 (43.3%) of the seropositive children. In the second and third evaluations, CMV was detected in 41/89 (46%) and in 35/89 (39.3%) children, respectively. Detection of CMV was shown both in urine and saliva in 28/39 (71.8%), 19/41(46.3%) and 20/35 (57.1%) of the children excreting the virus, respectively. Additionally, in 33/49 (67.4%) of the excreters CMV could be demonstrated in urine or saliva in at least two out of the three virological evaluations carried out sequentially in a six month period. Of the 28 initially seronegative children, 26 were re-examined for anti-CMV IgG antibodies about 18 months after the negative sample; seroconversion was found in 10/26 (38.5%). Taking all 536 samples of urine or saliva examined by virus culture and pp65 antigen detection during the study into account, 159 (29.6%) were positive by virus culture and 59 (11%) gave a positive result with the pp65 assay. These data demonstrate the high prevalence of CMV shedding and the high risk of CMV infection in children with Down syndrome attending a day-care center for mentally handicapped patients. The virus culture was more sensitive than the pp65 CMV antigen assay for CMV detection in both urine and saliva samples.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

Quality Of Attachment, Perinatal Risk, And Mother-Infant Interaction In A High-Risk Premature Sample

Thirty-three families, each with a premature infant born less than 33 gestational weeks, were observed in a longitudinal exploratory study. Infants were recruited in a neonatal intensive care unit, and follow-up visits took place at 4 months and 12 months of corrected age. The severity of the perinatal problems was evaluated using the Perinatal Risk Inventory (PERI; A.P. Scheiner & M.E. Sexton, 1991). At 4 months, mother infant play interaction was observed and coded according to the CARE-index (P.M. Crittenden, 2003); at 12 months, the Strange Situation Procedure (SSP; M.D.S. Ainsworth, M.C. Blehar, E. Waters. & S. Wall, 1978) was administered. Results indicate a strong correlation between the severity of perinatal problems and the quality of attachment at 12 months. Based on the PERI, infants with high medical risks more frequently tended to be insecurely attached. There also was a significant correlation between insecure attachment and dyadic play interaction at 4 months (i.e., maternal controlling behavior and infant compulsive compliance). Moreover, specific dyadic interactive patterns could be identified as protective or as risk factors regarding the quality of attachment. Considering that attachment may have long-term influence on child development, these results underline the need for particular attention to risk factors regarding attachment among premature infants.