NATURAL PRODUCT SUBSTITUTION PATTERN AND SKELETAL RECOGNITION METHOD

This work describes a methodology for identification of skeletal types of diterpenes based on data base with 1500 compounds isolated from Asteraceae. One program named BOTOCSYS was built with the codification of the compounds and their botanical sources. An example of identification of a new substance is given.

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

Fold, transcritical and pitchfork singularities for time-reversible systems

This paper deals with a class of singularly perturbed reversible planar vector fields around the origin where the normal hyperbolicity assumption is not assumed. We exhibit conditions for the existence of infinitely many periodic orbits and hetero-clinic cycles converging to singular orbits with respect to the Hausdorf distance. In addition, generic normal forms of such singularities are presented.

Aircraft interior failure pattern recognition utilizing text mining and neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Araguaia fold belt, Brazil: A reactivated Brasiliano-Pan-African cycle (550 Ma) geosuture

The Araguaia-Tocantins geosuture, which separates the Araguaia Fold Belt (AFB) from the Archean Amazonian Craton, was active in the late Middle Proterozoic. The Baixo Araguaia Supergroup was deposited, consisting of the Estrondo Group (lower quartzites with intercalated schists), Xambioá Formation (schists), and Canto da Vazante Formation (upper feldspathic schists); and the Tocantins Group consisting of the Couto Magalhaës Formation (phyllites, quartzites, slates, limestones, and metacherts) and Pequizeiro Formation (upper chlorite schists); and associated mafic-ultramafic bodies. The deformational history includes four regional phases of deformation within this supracrustal sequence: recumbent folds with vergence to the west; refolding with a N-S trend; an intense crenulation episode; and late thrusting from east to west. Metamorphism is of intermediate or intermediate-high pressure type with garnet, biotite, chlorite, and sericite isograds succeeded by a slightly or non-metamorphosed zone, from east to west. Rocks surrounding sparse gneissic-cored domes contain isograds of staurolite, kyanite, and fibrolite. These isograds are believed to be associated with the 1100 Ma Uruaçuano event. The Brasiliano Orogeny strongly affected the AFB with displacements due to transcurrent reactivation of great and old faults of the basement, slight folding in the supracrustal sequence, intrusion of small granite bodies, and development of domes with associated normal faults. The area underlain by the Estrondo Group was uplifted at this time, causing the deposition of the Rio das Barreiras polymictic conglomerate of the central area. K-Ar and Rb-Sr analyses date this thermo-tectonic event at 550 ± 100 Ma. The Archean basement is exposed in the cores of domes as a granite-gneiss association, the Colméia complex, which shows thermo-tectonic features that may be interpreted as polycyclic imprints (Jequié, Transamazonian?, Uruaçuano, and Brasiliano Events). © 1989.

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).

Laryngeal electromyography: Contribution to vocal fold immobility diagnosis

Laryngeal Electromyography (LEMG) is a diagnostic test commonly used in patients with vocal fold movement disorder The aim of this study is to describe LEMG in patients with vocalfold immobility. A total of 55 dysphonic patients with vocal fold immobility diagnosed by laryngeal endoscopy were grouped according to probable clinical cause: 1) unknown; 2) traumatic; or 3) tumoral compression. They were submitted to LEMG by percutaneous insertion of concentric needle electrode. LEMG was conclusive in all patients and showed a majority with peripheral nerve injury. LEMG diagnosed peripheral nerve damage in 25 group 1, 12 group 2, and 11 group 3 patients. LEMG was normal in 4 patients, suggesting cricoarytenoid joint fixation. Central nervous system disorders was suggested in 2 and myopathic pattern in 1. As the major cause of vocal fold immobility is peripheral nerve damage, LEMG is an important test to confirm diagnosis.

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.

Morphological and histochemical analysis of the human vestibular fold

A morphological and histochemical study of the human vestibular fold was carried out using routine histological techniques. Seven μm-thick histological sections stained with hematoxylin-eosin (HE) and Calleja showed the presence of elastic collagen fibers and seromucous glands in the vestibular fold. Muscle fibers forming the ventricular muscle were also identified. Ultrastructural analyses of the epithelial layer by scanning electron microscopy (SEM) revealed ciliated cells and gland ducts opening on the epithelial surface. Histochemical analyses were performed on ventricular muscles submitted to nicotinamide-adenine-dinucleotide tetrazolium reductase (NADH-TR), succinate dehydrogenase (SDH), and myofibrillar adenosine triphosphatase (mATPase) reactions. Based on these reactions, it was observed that the muscle is formed by three types of muscle fibers: slow-twitch oxidative (SO), fast-twitch oxydative glycolytic (FOG) and fast-twitch glycolytic (FG) fibers distributed in a mosaic pattern. The fiber frequency was 22.7%, 69.9% and 7.4%, respectively. The higher frequency of SO and FOG fibers characterized the muscle as having aerobic metabolism and resistance to fatigue. The ventricular muscle was considered fast. The study of the neuromuscular junctions performed after nonspecific esterase reaction showed that they are of the en-plaque type and have multiple occurrences in the ventricular muscle.

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.

Labour markets, worker protection and lifelong learning in a global economy: experiences and perspectives of Latin America and the Caribbean

Includes bibliography

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.