Probabilistic neural network to predict cracks in taphole mud used in blast furnaces

One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

Impedance e-tongue instrument for rapid liquid assessment

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Caracterização das fases de desenvolvimento de células gigantes induzidas por Meloidogyne exigua em raiz de seringueira (Hevea brasiliensis Muell. Arg.)

The developmental phases of giant cells induced by root-knot nematodes (Meloidogyne exigua) in rubber plant (Hevea brasiliensis) root were studied in relation to its number and size evaluated in eight sample dates. The results were subject to cluster analysis and principal component analysis. Sample dates were clearly distinct regarding giant cell development. As a result, the nematode infestation cycle was characterized by the following sequential phases: initial, equilibrium, choice and final.

Relationship between Constrictotermes cyphergaster and Inquiline Termites in the Cerrado (Isoptera: Termitidae)

Constrictotermes cyphergaster builds arboreal nests in Cerrado sensu stricto of Brazil; inquiline termites and termitophiles frequently inhabit their nests. Measurements of the nests and the support trees (nest width and diameter; tree trunk circumference and inclination), colony size of C. cyphergaster and of Inquilinitermes and number of termitophiles were studied at the Parque Estadual da Serra de Caldas Novas. These variables were subjected to a Principal Component Analysis, producing four principal components. The first principal component refers to a multidimensional axis of nest size, encompassing variables related to nest and colony size, such as abundance per caste of C. cyphergaster and I. microcerus, number of termitophile species and the measurements of the nest. The number of soldiers and workers of C. cyphergaster and soldiers of Inquilinitermes increased proportionally to the axis of nest size, while the number of Inquilinitermes workers increased more quickly then the increase in the nest size. Both Inquilinitermes occurred mainly in larger nests. Almost half of the nests (47,5%) were inhabited by I. microcerus and 10% by I. fur.

Nanostructured films of perylene derivatives: High performance materials for taste sensor applications

Four perylene derivatives (PTCD) have been used as transducing materials in taste sensors fabricated with nanostructured Langmuir-Blodgett (LB) films deposited onto interdigitated gold electrodes. The Langmuir monolayers of PTCDs display considerable collapse pressures, with areas per molecule indicative of an edge-on or head-on arrangement for the molecules at the air/water interface. The sensing units for the electronic tongue were produced from 5-layer LB films of the four PTCDs, whose electrical response was characterized with impedance spectroscopy. The distinct responses of the PTCDs, attributed to differences in their molecular structures, allowed one to obtain a finger printing system that was able to distinguish tastes (salty, sweet, bitter and sour) at 1 μM concentrations, which, in some cases, are three orders of magnitude below the human threshold. Using Principal Component Analysis (PCA) data analysis, the electronic tongue also detected trace amounts of a pesticide and could distinguish among samples of ultrapure, distilled and tap water, and two brands of mineral water. © 2004 by American Scientific Publishers. All rights reserved.

Studies on the interaction between humic substances and conducting polymers for sensor application

The interaction between humic substances and poly(o-ethoxyaniline) (POEA), a conducting polymer, was investigated for both solution and self-assembled films. The results have shown that the humic substances induce a doping of POEA by protonation, as indicated by UV-Vis and Raman spectroscopies. The atomic force microscopy (AFM) studies on the self-assembled films have shown that the average roughness of the polymer film has increased after exposing it to humic substances (fulvic and humic acids), consistent with the interaction between POEA and humic substances. However, this change in morphology is reversible by washing the films with water in agreement with the electrical data allowing using this system in sensor applications. Here, the sensor formed by an array of different sensing units was able to detect and distinguish humic substances in aqueous solution, as shown by multivariate analysis (principal component analysis). The motivation to detect humic substance comes due to its importance in terms of quality control of water or soil. ©2005 Sociedade Brasileira de Química.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Nest defense behavior against the attack of ants in colonies of pre-emergent Mischocyttarus cerberus (hymenoptera, vespidae)

The study was carried out at the UNESP Rio Claro campus (SP), where biotests consisting of simulated ant attacks were performed in colonies of Mischocyttarus cerberus. The behaviors of the wasps were recorded with a camcorder, for further analysis. This analysis was done using the Mann-Whitney U test and the Principal Component Analysis. In the pre-emergence development stage, colonies with a single foundress defend the nest only after the first larvae appear. When there are only eggs in the nest, the wasp abandons the nest. Before leaving, the wasp rubs its gaster against the nest, releasing the ant repellent secretion. When the nest contains larvae or larvae and pupae, the foundress defends the colony, vibrating its wings, pumping her abdomen and biting the ant.

Uso de indicadores hidrológicos para classificação de trechos de estradas florestais quanto ao escoamento superficial

Forest roads are frequently pointed as source of environmental problems related to erosion and they also influence harvest cost due to maintenance operations. Roads not well designed are sources of hydrological problems on catchments and the current attention to sustainability of forest exploration projects point out to the need of diagnostics tools for guiding the redesign of the road system. At this study, runoff hydrological indicators for forest road segments were assessed in order to identify critical points of erosion and water concentration on soils. A road network of a forest production area was divided into 252 road segments that were used as observations of four variables: mean terrain slope, main segment slope, LS factor and topographic index. The data analysis was based on descriptive statistics for outliers' identification, principal component analysis and for variability study between variables and between observations, and cluster analysis for similar segments groups' identification. The results allowed classifying roads segments into five mains road types: road on the ridge, on the valley, on the slopes, on the slopes but in a contour line and on the steepest slope. The indicators were able to highlight the most critical segments that differ of others and are potential sources of erosion and water accumulation problems on forest roads. The principal component analysis showed two main variability sources related to terrain topographic characteristics and also road design, showing that indicators represent well those elements. The methodology seems to be appropriated for identification of critical road segments that need to be redesigned and also for road network planning at new forest exploration projects.

Genetic divergence in sesame based on morphological and agronomic traits

The evaluation of diversity in germplasm collections is important for both plant breeders and germplasm curators to optimize the use of the variability available. Diversity can be estimated by different genetic markers. The purpose of this study was to estimate the genetic divergence of 30 morphological and agronomic traits in 108 sesame genotypes by multivariate analysis. The Cole-Rodgers index was used to establish the dissimilarity matrices. The principal component analysis identified the traits that contributed most to the divergence and the genotypes were clustered by Tocher's optimization. Despite the narrow genetic basis, the markers were efficient to characterize the genotypes and identify the most similar groups or duplicate and divergent genotypes. Greatest variation was found for the traits number of capsules per plant and grain yield.

The influence of seasonalness on the structural characteristics of aquatic humic substances extracted from Negro River (Amazon state) waters: Interactions with Hg(II)

In this work, humic substances were extracted from water samples collected monthly from the Negro River basin in the Amazon state (Brazil) to study their properties in the Amazonian environment and interactions with the mercury ion considering the influence of seasonalness in this formation. The C/H, C/N and C/O atomic ratio parameters, functional groups, concentration of semiquinone-type free radicals, pH, pluviometric and fluviometric indices, and mercury concentrations were interpreted using hierarchical cluster analysis (HCA) and principal component analysis (PCA). The statistical analyses showed that when the pluviometric index was greater and the fluviometric index was smaller, the degree of humification of aquatic substances was greater. The following decreasing order of the degree of humification of the AHS collected monthly was established: Nov/02 to Feb/03 > Mar/02 to May/02 > Jun/02 to Oct/02. The greatest concentrations of mercury were detected in more humidified samples. These results suggest that due to inter and/or intra-molecular rearrangements, the degree of humification of aquatic humic substances is related to its affinity for Hg(II) ions. ©2007 Sociedade Brasileira de Química.

Variação sazonal de alguns parâmetros físicos e químicos em três rios pertencentes a uma bacia de drenagem na região centro-sul do Estado do Paraná, Sul do Brasil

Three small rivers belonging to the Rio das Pedras basin, located in the mid-southern region of Paraná state, were studied in order to evaluate the seasonal variation pattern of some physical and chemical parameters. Monthly samplings were carried out from April 2004 to March 2005. The following limnological parameters were measured: water temperature, specific conductance, oxygen saturation, pH, turbidity, current velocity and depth. The waters of the Rio das Pedras basin presented very peculiar characteristics, showing typical seasonal patterns for some of the studied limnological variables. An Analysis of Variance (Anova) showed significant differences only for pH and depth among streams. A Principal Component Analysis (PCA) showed a weak tendency to form groups based on seasons instead of sampling sites. The results, in general, indicate that temporal variations of the environmental parameters analyzed were not sufficient to draw a clear seasonal pattern in the Rio das Pedras basin. Most likely, the lack of an obvious seasonal pattern has been provoked by a particular regional precipitation regime, where rains are frequent and well-distributed throughout the year.

Influence of the environment on behavior patterns of laying hens kept in cages

The aim of this paper is to verify the correlation between environmental indicators and behaviors expressed by laying hens kept in cages. The birds react to a severe environment through their behaviors, end the behaviors can be monitored to identify the birds' welfare conditions. The behaviors birds display ere the result of stress caused by the combination of environmental temperature, relative humidity, radiant heat, and air speed (environmental temperature being the most important). In order to check the influence of the environment, an experiment was carried out on a commercial poultry farm, located in the city of Bastos. The study was initiated in March 2007, during four non-consecutive weeks. The birds' behaviors were recorded using video, by cameras installed in the cages. The birds behaviors were identified and noted for the frequency of occurrence for each bird, and the average duration of each behavior (in seconds), using video samples of 15 minutes recorded from 1 PM to 4 PM. The environmental variables collected were: air temperature, concentration of ammonia, relative air humidity, velocity of the air, noise, roof temperature, and light intensity. The observed behaviors were: opening wings, stretching, threatening, ruffling feathers, drinking water, aggressive pecking, eating, running, lying down, stretching head out of the cage, preening, mounting and prostrating. Principal Components Analysis was used to determine associations between the behavior variables and environmental variables described above. In this experiment, there were no significant correlations between behavioral variables and environmental variables.

Análise multivariada na determinação do risco de erosão em solos sob irrigação

The objective of this work was to verify the application of cluster analysis to evaluate soil erosion risk for different soil classes, soil slopes and soil managements. The study was conducted in a 33 ha section of a large field located in Carmo do Rio Claro County, MG, Brazil. The field had been managed in a corn/bean rotation under conventional tillage and under coffee plantation for seven years, both under sprinkle irrigation. Soil samples were obtained at every 10 m at 0.20 m depth along a transect of 1050 m. Soil erosion risk (A), natural potential erosion (PN), and erosion expectation (EE) were determined and submitted to a cluster and principal component analysis. The application of clustering analysis showed high correlation between the clusters and soil types. With clustering analysis plus principal components analysis, it was possible to identify groups of high and low soil erosion expectation, showing that the areas with higher soil erosion expectation are correlated to the soil class, soil slope and soil management. Among the studied variables, the natural potential erosion (PN) showed to be the most important factor to identify different soil erosion groups. The cluster analysis showed that 98% of the variables were classified within each group, and that they should be managed differently due to the soil erosive potential of each group,.