Aircraft interior failure pattern recognition utilizing text mining and neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Recognition of Cretaceous, Paleocene, and Neogene tectonic reactivation through apatite fission-track analysis in Precambrian areas of southeast Brazil: Association with the opening of the south Atlantic Ocean

Apatite fission-track analysis was used for the determination of thermal histories and ages in Precambrian areas of southeast Brazil. Together with geological and geomorphologic information, these ages enable us to quantify the thermal histories and timing of Mesozoic and Cenozoic epirogenic and tectonic processes. The collected samples are from different geomorphologic blocks: the high Mantiqueira mountain range (HMMR) with altitude above 1000 m, the low Mantiqueira mountain range (LMMR) under 1000 m, the Serra do Mar mountain range (SMMR), the Jundiá and Atlantic Plateaus, and the coastline, all of which have distinct thermal histories. During the Aptian (∼120 Ma), there was an uplift of the HMMR, coincident with opening of the south Atlantic Ocean. Its thermal history indicates heating (from ∼60 to∼80 °C) until the Paleocene, when rocks currently exposed in the LMMR reached temperatures of ∼100 °C. In this period, the Serra do Mar rift system and the Japi erosion surface were formed. The relief records the latter. During the Late Cretaceous, the SMMR was uplifted and probably linked to its origin; in the Tertiary, it experienced heating from ∼60 to ∼90 °C, then cooling that extends to the present. The SMMR, LMMR, and HMMR were reactivated mainly in the Paleocene, and the coastline during the Paleogene. These processes are reflected in the sedimentary sequences and discordances of the interior and continental margin basins. © 2002 Elsevier Science Ltd. All rights reserved.

Evolvable hardware applied to voice recognition

This paper presents some results of the application on Evolvable Hardware (EHW) in the area of voice recognition. Evolvable Hardware is able to change inner connections, using genetic learning techniques, adapting its own functionality to external condition changing. This technique became feasible by the improvement of the Programmable Logic Devices. Nowadays, it is possible to have, in a single device, the ability to change, on-line and in real-time, part of its own circuit. This work proposes a reconfigurable architecture of a system that is able to receive voice commands to execute special tasks as, to help handicapped persons in their daily home routines. The idea is to collect several voice samples, process them through algorithms based on Mel - Ceptrais theory to obtain their numerical coefficients for each sample, which, compose the universe of search used by genetic algorithm. The voice patterns considered, are limited to seven sustained Portuguese vowel phonemes (a, eh, e, i, oh, o, u).

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.

Fusion of fingerprint recognition methods for robust human identification

Biometrics is one of the biggest tendencies in human identification. The fingerprint is the most widely used biometric. However considering the automatic fingerprint recognition a completely solved problem is a common mistake. The most popular and extensively used methods, the minutiae-based, do not perform well on poor-quality images and when just a small area of overlap between the template and the query images exists. The use of multibiometrics is considered one of the keys to overcome the weakness and improve the accuracy of biometrics systems. This paper presents the fusion of a minutiae-based and a ridge-based fingerprint recognition method at rank, decision and score level. The fusion techniques implemented leaded to a reduction of the Equal Error Rate by 31.78% (from 4.09% to 2.79%) and a decreasing of 6 positions in the rank to reach a Correct Retrieval (from rank 8 to 2) when assessed in the FVC2002-DB1A database. © 2008 IEEE.

Routine libraries for pattern recognition in quasispecies.

The results obtained through biological research usually need to be analyzed using computational tools, since manual analysis becomes unfeasible due to the complexity and size of these results. For instance, the study of quasispecies frequently demands the analysis of several, very lengthy sequences of nucleotides and amino acids. Therefore, bioinformatics tools for the study of quasispecies are constantly being developed due to different problems found by biologists. In the present study, we address the development of a software tool for the evaluation of population diversity in quasispecies. Special attention is paid to the localization of genome regions prone to changes, as well as of possible hot spots.

Color alteration of the paint used for iris painting in ocular prostheses

The purpose of this study was to assess color alteration of the paints used for iris painting in artificial eyes. Five disks of heat cured acrylic resin were confectioned by microwave energy for each paint analyzed, in a total of 40 specimens. Each specimen consisted of a colorless acrylic resin disk and another of equal size, of scleral white colored acrylic resin, with the painting interposed between the two disks. The specimens were submitted to an accelerated aging process in a chamber under ultraviolet radiation for 1,008 hours. To assess color variation, a reflective spectrophotometer was used. The results were statistically analyzed by ANOVA and the Tukey test (p < 0.05). All the paints underwent chromatic alteration. The oil paint presented the highest resistance to accelerated aging.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Attitude of Brazilian veterinarians in the recognition and treatment of pain in horses and cattle

Objective: The objective of this study was to assess the use of analgesics, describe the attitudes of Brazilian veterinarians towards pain relief in horses and cattle and evaluate the differences due to gender, year of graduation and type of practice. Study design: Prospective survey. Methods: Questionnaires were sent to 1000 large animal veterinarians by mail, internet and delivered in person during national meetings. The survey investigated the attitudes of Brazilian veterinarians to the recognition and treatment of pain in large animals and consisted of sections asking about demographic data, use of analgesic drugs, attitudes to pain relief and to the assessment of pain. Descriptive statistics were used to analyze frequencies. Simple post hoc comparisons were performed using the chi-square test. Results: Eight hundred questionnaires were collected, but 87 were discarded because they were incomplete or blank. The opioid of choice for use in large animals was butorphanol (43.4%) followed by tramadol (39%). Flunixin (83.2%) and ketoprofen (67.6%) were the most frequently used NSAIDs by Brazilian veterinarians. Respondents indicated that horses received preoperative analgesics for laparotomy more frequently (72.9%) than cattle (58.5%). The most frequently administered preoperative drugs for laparotomy in horses were flunixin (38.4%) and xylazine (23.6%), whereas the preoperative drugs for the same surgical procedure in cattle were xylazine (31.8%) and the local administration of lidocaine (48%). Fracture repair was considered the most painful surgical procedure for both species. Most veterinarians (84.1%) believed that their knowledge in this area was not adequate. Conclusions and clinical relevance: Although these Brazilian veterinarians thought that their knowledge on recognition and treatment of pain was not adequate, the use of analgesic in large animals was similar in Brazil to that reported in other countries. © 2013 Association of Veterinary Anaesthetists and the American College of Veterinary Anesthesia and Analgesia.