Análise wavelet em curvas de luz estelares de sistemas binários da missão espacial CoRoT

Binary systems are key environments to study the fundamental properties of stars. In this work, we analyze 99 binary systems identified by the CoRoT space mission. From the study of the phase diagrams of these systems, our sample is divided into three groups: those whose systems are characterized by the variability relative to the binary eclipses; those presenting strong modulations probably due to the presence of stellar spots on the surface of star; and those whose systems have variability associated with the expansion and contraction of the surface layers. For eclipsing binary stars, phase diagrams are used to estimate the classification in regard to their morphology, based on the study of equipotential surfaces. In this context, to determine the rotation period, and to identify the presence of active regions, and to investigate if the star exhibits or not differential rotation and study stellar pulsation, we apply the wavelet procedure. The wavelet transform has been used as a powerful tool in the treatment of a large number of problems in astrophysics. Through the wavelet transform, one can perform an analysis in time-frequency light curves rich in details that contribute significantly to the study of phenomena associated with the rotation, the magnetic activity and stellar pulsations. In this work, we apply Morlet wavelet (6th order), which offers high time and frequency resolution and obtain local (energy distribution of the signal) and global (time integration of local map) wavelet power spectra. Using the wavelet analysis, we identify thirteen systems with periodicities related to the rotational modulation, besides the beating pattern signature in the local wavelet map of five pulsating stars over the entire time span.

Análise wavelet em curvas de luz estelares de sistemas binários da missão espacial CoRoT

Binary systems are key environments to study the fundamental properties of stars. In this work, we analyze 99 binary systems identified by the CoRoT space mission. From the study of the phase diagrams of these systems, our sample is divided into three groups: those whose systems are characterized by the variability relative to the binary eclipses; those presenting strong modulations probably due to the presence of stellar spots on the surface of star; and those whose systems have variability associated with the expansion and contraction of the surface layers. For eclipsing binary stars, phase diagrams are used to estimate the classification in regard to their morphology, based on the study of equipotential surfaces. In this context, to determine the rotation period, and to identify the presence of active regions, and to investigate if the star exhibits or not differential rotation and study stellar pulsation, we apply the wavelet procedure. The wavelet transform has been used as a powerful tool in the treatment of a large number of problems in astrophysics. Through the wavelet transform, one can perform an analysis in time-frequency light curves rich in details that contribute significantly to the study of phenomena associated with the rotation, the magnetic activity and stellar pulsations. In this work, we apply Morlet wavelet (6th order), which offers high time and frequency resolution and obtain local (energy distribution of the signal) and global (time integration of local map) wavelet power spectra. Using the wavelet analysis, we identify thirteen systems with periodicities related to the rotational modulation, besides the beating pattern signature in the local wavelet map of five pulsating stars over the entire time span.

Avaliação da integridade estrutural de uma prótese cimentada por emissão acústica

Mestrado em Engenharia Electrotécnica e de Computadores

Classificação automática do sono: Contribuição utilizando distância de Itakura-Saito e Wavelets

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

SleepLab V.2.0: plataforma integrada de teste de algoritmos para classificação não supervisionada do sono

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Análise espectral com wavelets do ECoG em crises epilépticas

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Sistema de detecção de fogo e detecção e seguimento de objectos

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

BOI 2.0: disseny d'una implementació de JPEG 2000

JPEG 2000 és un estàndard de compressió d'imatges que utilitza tècniques estat de l’art basades en la transformada wavelet. Els principals avantatges són la millor compressió, la possibilitat d’operar amb dades comprimides i que es pot comprimir amb i sense pèrdua amb el mateix mètode. BOI és la implementació de JPEG 2000 del Grup de Compressió Interactiva d’Imatges del departament d’Enginyeria de la Informació i les Comunicacions, pensada per entendre, criticar i millorar les tecnologies de JPEG 2000. La nova versió intenta arribar a tots els extrems de l’estàndard on la versió anterior no va arribar.

Representació no-lineal de les imatges per a codificació perceptiva

JPEG2000 és un estàndard de compressió d’imatges que utilitza la transformada wavelet i, posteriorment, una quantificació uniforme dels coeficients amb dead-zone. Els coeficients wavelet presenten certes dependències tant estadístiques com visuals. Les dependències estadístiques es tenen en compte a l'esquema JPEG2000, no obstant, no passa el mateix amb les dependències visuals. En aquest treball, es pretén trobar una representació més adaptada al sistema visual que la que proporciona JPEG2000 directament. Per trobar-la utilitzarem la normalització divisiva dels coeficients, tècnica que ja ha demostrat resultats tant en decorrelació estadística de coeficients com perceptiva. Idealment, el que es voldria fer és reconvertir els coeficients a un espai de valors en els quals un valor més elevat dels coeficients impliqui un valor més elevat d'aportació visual, i utilitzar aquest espai de valors per a codificar. A la pràctica, però, volem que el nostre sistema de codificació estigui integrat a un estàndard. És per això que utilitzarem JPEG2000, estàndard de la ITU que permet una elecció de les distorsions en la codificació, i utilitzarem la distorsió en el domini de coeficients normalitzats com a mesura de distorsió per a escollir quines dades s'envien abans.

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Sistema auxiliar na análise de mamogramas digitais

This work proposes the development of a Computer System for Analysis of Mammograms SCAM, that aids the doctor specialist in the identification and analysis of existent lesions in digital mammograms. The computer system for digital mammograms processing will make use of a group of techniques of Digital Image Processing (DIP), with the purpose of aiding the medical professional to extract the information contained in the mammogram. This system possesses an interface of easy use for the user, allowing, starting from the supplied mammogram, a group of processing operations, such as, the enrich of the images through filtering techniques, the segmentation of areas of the mammogram, the calculation the area of the lesions, thresholding the lesion, and other important tools for the medical professional's diagnosis. The Wavelet Transform will used and integrated into the computer system, with the objective of allowing a multiresolution analysis, thus supplying a method for identifying and analyzing microcalcifications

Processamento embarcado aplicado a um sistema de deteccão de vazamentos

Embedded systems are widely spread nowadays. An example is the Digital Signal Processor (DSP), which is a high processing power device. This work s contribution consist of exposing DSP implementation of the system logic for detecting leaks in real time. Among the various methods of leak detection available today this work uses a technique based on the pipe pressure analysis and usesWavelet Transform and Neural Networks. In this context, the DSP, in addition to do the pressure signal digital processing, also communicates to a Global Positioning System (GPS), which helps in situating the leak, and to a SCADA, sharing information. To ensure robustness and reliability in communication between DSP and SCADA the Modbus protocol is used. As it is a real time application, special attention is given to the response time of each of the tasks performed by the DSP. Tests and leak simulations were performed using the structure of Laboratory of Evaluation of Measurement in Oil (LAMP), at Federal University of Rio Grande do Norte (UFRN)

Estudo da detecção preventiva da osteoporose pela aplicação da variação da permissividade elétrica a partir da sondagem eletromagnética

This paper proposes a method based on the theory of electromagnetic waves reflected to evaluate the behavior of these waves and the level of attenuation caused in bone tissue. For this, it was proposed the construction of two antennas in microstrip structure with resonance frequency at 2.44 GHz The problem becomes relevant because of the diseases osteometabolic reach a large portion of the population, men and women. With this method, the signal is classified into two groups: tissue mass with bony tissues with normal or low bone mass. For this, techniques of feature extraction (Wavelet Transform) and pattern recognition (KNN and ANN) were used. The tests were performed on bovine bone and tissue with chemicals, the methodology and results are described in the work