Optimum-Path Forest Applied for Breast Masses Classification

In Computer-Aided Diagnosis-based schemes in mammography analysis each module is interconnected, which directly affects the system operation as a whole. The identification of mammograms with and without masses is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest for further image segmentation. This study aims to evaluate the performance of three techniques in classifying regions of interest as containing masses or without masses (without clinical findings), as well as the main contribution of this work is to introduce the Optimum-Path Forest (OPF) classifier in this context, which has never been done so far. Thus, we have compared OPF against with two sorts of neural networks in a private dataset composed by 120 images: Radial Basis Function and Multilayer Perceptron (MLP). Texture features have been used for such purpose, and the experiments have demonstrated that MLP networks have been slightly better than OPF, but the former is much faster, which can be a suitable tool for real-time recognition systems.

Estudo das propriedades dinâmicas e sincronização no mapa de rede de Zaslavsky

Synchronization in nonlinear dynamical systems, especially in chaotic systems, is field of research in several areas of knowledge, such as Mechanical Engineering and Electrical Engineering, Biology, Physics, among others. In simple terms, two systems are synchronized if after a certain time, they have similar behavior or occurring at the same time. The sound and image in a film is an example of this phenomenon in our daily lives. The studies of synchronization include studies of continuous dynamic systems, governed by differential equations or studies of discrete time dynamical systems, also called maps. Maps correspond, in general, discretizations of differential equations and are widely used to model physical systems, mainly due to its ease of computational. It is enough to make iterations from given initial conditions for knowing the trajectories of system. This completion of course work based on the study of the map called ”Zaslavksy Web Map”. The Zaslavksy Web Map is a result of the combination of the movements of a particle in a constant magnetic field and a wave electrostatic propagating perpendicular to the magnetic field. Apart from interest in the particularities of this map, there was objective the deepening of concepts of nonlinear dynamics, as equilibrium points, linear stability, stability non-linear, bifurcation and chaos

Coherence characteristics of random lasing in a dye doped hybrid powder

The photon statistics of the random laser emission of a Rhodamine B doped di-ureasil hybrid powder is investigated to evaluate its degree of coherence above threshold. Although the random laser emission is a weighted average of spatially uncorrelated radiation emitted at different positions in the sample, a spatial coherence control was achieved due to an improved detection configuration based on spatial filtering. By using this experimental approach, which also allows for fine mode discrimination and timeresolved analysis of uncoupled modes from mode competition, an area not larger than the expected coherence size of the random laser is probed. Once the spectral and temporal behavior of nonoverlapping modes is characterized, an assessment of the photon-number probability distribution and the resulting second-order correlation coefficient as a function of time delay and wavelength was performed. The outcome of our single photon counting measurements revealed a high degree of temporal coherence at the time of maximum pump intensity and at wavelengths around the Rhodamine B gain maximum.

Desenvolvimento de um simulador virtual de vazamento para testar correlacionadores acústicos comerciais

Pós-graduação em Engenharia Mecânica - FEIS

Fenotipagem para estudos de estudos de tolerância à deficiência hídrica em eucalipto

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Controle robusto de sistemas não lineares e chaveado de sistemas lineares usando realimentação derivativa

Pós-graduação em Engenharia Elétrica - FEIS

Projeto de controlador gain scheduling usando realimentação derivativa via LMI

Pós-graduação em Engenharia Elétrica - FEIS

A simulation tool for transient stability analysis on vector computers

This paper deals with transient stability analysis based on time domain simulation on vector processing. This approach requires the solution of a set of differential equations in conjunction of another set of algebraic equations. The solution of the algebraic equations has presented a scalar as sequential set of tasks, and the solution of these equations, on vector computers, has required much more investigations to speedup the simulations. Therefore, the main objective of this paper has been to present methods to solve the algebraic equations using vector processing. The results, using a GRAY computer, have shown that on-line transient stability assessment is feasible.

Perfil de aptidão cardiorrespiratória em corredores jovens pela cinética do VO2 em testes progressivos e retangulares

Pós-graduação em Desenvolvimento Humano e Tecnologias - IBRC

The influence of connectivity on the firing rate in a neuronal network with electrical and chemical synapses

We study the firing rate properties of a cellular automaton model for a neuronal network with chemical synapses. We propose a simple mechanism in which the nonlocal connections are included, through electrical and chemical synapses. In the latter case, we introduce a time delay which produces self-sustained activity. Nonlocal connections, or shortcuts, are randomly introduced according to a specified connection probability. There is a range of connection probabilities for which neuron firing occurs, as well as a critical probability for which the firing ceases in the absence of time delay. The critical probability for nonlocal shortcuts depends on the network size according to a power-law. We also compute the firing rate amplification factor by varying both the connection probability and the time delay for different network sizes. (C) 2011 Elsevier B.V. All rights reserved.

Order-Disorder Transitions Govern Kinetic Cooperativity and Allostery of Monomeric Human Glucokinase

Glucokinase (GCK) catalyzes the rate-limiting step of glucose catabolism in the pancreas, where it functions as the body's principal glucose sensor. GCK dysfunction leads to several potentially fatal diseases including maturity-onset diabetes of the young type II (MODY-II) and persistent hypoglycemic hyperinsulinemia of infancy (PHHI). GCK maintains glucose homeostasis by displaying a sigmoidal kinetic response to increasing blood glucose levels. This positive cooperativity is unique because the enzyme functions exclusively as a monomer and possesses only a single glucose binding site. Despite nearly a half century of research, the mechanistic basis for GCK's homotropic allostery remains unresolved. Here we explain GCK cooperativity in terms of large-scale, glucose-mediated disorder-order transitions using 17 isotopically labeled isoleucine methyl groups and three tryptophan side chains as sensitive nuclear magnetic resonance (NMR) probes. We find that the small domain of unliganded GCK is intrinsically disordered and samples a broad conformational ensemble. We also demonstrate that small-molecule diabetes therapeutic agents and hyperinsulinemia-associated GCK mutations share a strikingly similar activation mechanism, characterized by a population shift toward a more narrow, well-ordered ensemble resembling the glucose-bound conformation. Our results support a model in which GCK generates its cooperative kinetic response at low glucose concentrations by using a millisecond disorder-order cycle of the small domain as a "time-delay loop," which is bypassed at high glucose concentrations, providing a unique mechanism to allosterically regulate the activity of human GCK under physiological conditions.

3C 273 variability at 7 mm: evidence of shocks and precession in the jet

We report on four years of observations of 3C 273 at 7mm obtained with the Itapetinga radio telescope, in Brazil, between 2009 and 2013. We detected a flare in 2010 March, when the flux density increased by 50 per cent and reached 35 Jy. After the flare, the flux density started to decrease and reached values lower than 10 Jy. We suggest that the 7-mm flare is the radio counterpart of the γ -ray flare observed by the Fermi Large Area Telescope in 2009 September, in which the flux density at high energies reached a factor of 50 of its average value. A delay of 170 d between the radio and γ -ray flares was revealed using the discrete correlation function (DCF) that can be interpreted in the context of a shock model, in which each flare corresponds to the formation of a compact superluminal component that expands and becomes optically thin at radio frequencies at latter epochs. The differences in flare intensity between frequencies and at different times are explained as a consequence of an increase in the Doppler factor δ, as predicted by the 16-yr precession model proposed by Abraham & Romero. This increase has a large effect on boosting at high frequencies while it does not affect the observed optically thick radio emission too much. We discuss other observable effects of the variation in δ, such as the increase in the formation rate of superluminal components, the variations in the time delay between flares and the periodic behaviour of the radio light curve that we have found to be compatible with changes in the Doppler factor.

Muscular and pulmonary O2 uptake kinetics during moderate- and high-intensity sub-maximal knee-extensor exercise in humans

[EN] The purpose of this investigation was to determine the contribution of muscle O(2) consumption (mVO2) to pulmonary O(2) uptake (pVO2) during both low-intensity (LI) and high-intensity (HI) knee-extension exercise, and during subsequent recovery, in humans. Seven healthy male subjects (age 20-25 years) completed a series of LI and HI square-wave exercise tests in which mVO2 (direct Fick technique) and pVO2 (indirect calorimetry) were measured simultaneously. The mean blood transit time from the muscle capillaries to the lung (MTTc-l) was also estimated (based on measured blood transit times from femoral artery to vein and vein to artery). The kinetics of mVO2 and pVO2 were modelled using non-linear regression. The time constant (tau) describing the phase II pVO2 kinetics following the onset of exercise was not significantly different from the mean response time (initial time delay + tau) for mVO2 kinetics for LI (30 +/- 3 vs 30 +/- 3 s) but was slightly higher (P < 0.05) for HI (32 +/- 3 vs 29 +/- 4 s); the responses were closely correlated (r = 0.95 and r = 0.95; P < 0.01) for both intensities. In recovery, agreement between the responses was more limited both for LI (36 +/- 4 vs 18 +/- 4 s, P < 0.05; r = -0.01) and HI (33 +/- 3 vs 27 +/- 3 s, P > 0.05; r = -0.40). MTTc-l was approximately 17 s just before exercise and decreased to 12 and 10 s after 5 s of exercise for LI and HI, respectively. These data indicate that the phase II pVO2 kinetics reflect mVO2 kinetics during exercise but not during recovery where caution in data interpretation is advised. Increased mVO2 probably makes a small contribution to during the first 15-20 s of exercise.

Caracterización y estudio de los sistemas operativos de tiempo real para sistemas embebidos FreeRTOS y ChibiOS/RT sobre un procesador SAM3X8E

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.