Biomobile: sistema de identificação de usuários em dispositivos móveis na plataforma Android utilizando reconhecimento de faces a partir de vídeo

Pós-graduação em Ciência da Computação - IBILCE

Desenvolvimento e aperfeiçoamento de protocolos de conjugação de nanomarcadores luminescentes com sistemas biológicos para aplicação em imunoensaios

Pós-graduação em Química - IBILCE

Síntese e caracterização de híbridos orgânico-inorgânicos luminescentes para aplicação em ensaios biológicos

Pós-graduação em Química - IBILCE

Fusão de métodos baseados em minúcias e em cristas para reconhecimento de impressões digitais

Pós-graduação em Ciência da Computação - IBILCE

Ferramentas e recursos livres para reconhecimento e síntese de voz em português brasileiro

Sistemas de reconhecimento e síntese de voz são constituídos por módulos que dependem da língua e, enquanto existem muitos recursos públicos para alguns idiomas (p.e. Inglês e Japonês), os recursos para Português Brasileiro (PB) ainda são escassos. Outro aspecto é que, para um grande número de tarefas, a taxa de erro dos sistemas de reconhecimento de voz atuais ainda é elevada, quando comparada à obtida por seres humanos. Assim, apesar do sucesso das cadeias escondidas de Markov (HMM), é necessária a pesquisa por novos métodos. Este trabalho tem como motivação esses dois fatos e se divide em duas partes. A primeira descreve o desenvolvimento de recursos e ferramentas livres para reconhecimento e síntese de voz em PB, consistindo de bases de dados de áudio e texto, um dicionário fonético, um conversor grafema-fone, um separador silábico e modelos acústico e de linguagem. Todos os recursos construídos encontram-se publicamente disponíveis e, junto com uma interface de programação proposta, têm sido usados para o desenvolvimento de várias novas aplicações em tempo-real, incluindo um módulo de reconhecimento de voz para a suíte de aplicativos para escritório OpenOffice.org. São apresentados testes de desempenho dos sistemas desenvolvidos. Os recursos aqui produzidos e disponibilizados facilitam a adoção da tecnologia de voz para PB por outros grupos de pesquisa, desenvolvedores e pela indústria. A segunda parte do trabalho apresenta um novo método para reavaliar (rescoring) o resultado do reconhecimento baseado em HMMs, o qual é organizado em uma estrutura de dados do tipo lattice. Mais especificamente, o sistema utiliza classificadores discriminativos que buscam diminuir a confusão entre pares de fones. Para cada um desses problemas binários, são usadas técnicas de seleção automática de parâmetros para escolher a representaçãao paramétrica mais adequada para o problema em questão.

Predição de falhas em redes de grades OBS com plano de controle GMPLS

Este trabalho apresenta uma proposta para predição de falhas em rede de grade OBS com plano de controle GMPLS que auxilia as aplicações em ambientes de colaboração, como exemplo a E-Science. Os agentes de monitoração de tráfego, denominado DQMA-Fuzzy, verificam parâmetros relacionados à QoS e às imperfeições nos enlaces ópticos. Por apresentar uma solução mais rápida e facilmente implementável, foi desenvolvido um sistema baseado em lógica Fuzzy para dar mais robustez às decisões dos agentes. Simulações no NS-2 (Network Simulator – 2) demonstram que a proposta minimiza bloqueios na rede e balanceia o uso dos recursos da grade, garantindo níveis de serviços bem definidos, auxiliando na engenharia de tráfego e na predição de falhas.

Utilização de sensores à base de fibra óptica visando o monitoramento de grandes estruturas na engenharia civil

As fibras ópticas são utilizadas em diferentes áreas e nas mais variadas aplicações. Na Engenharia Civil começaram a ser utilizadas no monitoramento de estruturas como alternativa de substituição dos tradicionais sensores elétricos. Este trabalho tem como objetivo estudar a aplicação e viabilidade dos sensores a base de fibra óptica no monitoramento de grandes estruturas da engenharia civil. Para avaliação dos resultados, foram realizados três diferentes tipos de testes experimentais onde corpos-de-prova foram instrumentados com extensômetros elétricos e ópticos. O primeiro tipo de teste correspondeu a ensaios de tração simples em barras de aço com carregamento monotônico até o rompimento de barras de aço. No segundo tipo de teste foi estudada a automação de um medidor triortogonal de junta que é um instrumento tipicamente utilizado para a instrumentação de barragens de concreto. Finalmente o último tipo de testes foi constituído por ensaios de cilindros de concreto à compressão para a determinação do módulo de elasticidade. Com relação à utilização dos sensores ópticos, durante a realização dos testes surgiram muitos problemas relacionados com a unidade óptica de aquisição de dados sendo necessária a utilização de três diferentes modelos de unidade de aquisição para a conclusão dos testes. No que se refere à exatidão dos resultados, observou-se que os resultados apresentados pelos sensores ópticos foram compatíveis com os resultados dos sensores elétricos. Entretanto, quando os sensores ópticos foram solicitados por grandes deformações implicaram em perda de sinal devido à interrupção do fluxo de luz, inabilitando o sensor para leituras.

Sistema baseado em software livre para reconhecimento de fala em nuvem em português brasileiro com alta disponibilidade

Este trabalho visa propor uma solução contendo um sistema de reconhecimento de fala automático em nuvem. Dessa forma, não há necessidade de um reconhecedor sendo executado na própria máquina cliente, pois o mesmo estará disponível através da Internet. Além do reconhecimento automático de voz em nuvem, outra vertente deste trabalho é alta disponibilidade. A importância desse tópico se d´a porque o ambiente servidor onde se planeja executar o reconhecimento em nuvem não pode ficar indisponível ao usuário. Dos vários aspectos que requerem robustez, tal como a própria conexão de Internet, o escopo desse trabalho foi definido como os softwares livres que permitem a empresas aumentarem a disponibilidade de seus serviços. Dentre os resultados alcançados e para as condições simuladas, mostrou-se que o reconhecedor de voz em nuvem desenvolvido pelo grupo atingiu um desempenho próximo ao do Google.

Morphology and Anatomy of Stem Mines in Cipocereus minensis (Wender.) Ritter (Cactaceae), an Endemic Species to Eastern Brazil

Plant mines are structures with the form of a cavity caused by consumption of host plant tissue by the insect's miner larvae. Plant mines are more common in leaves, but in Cipocereus minensis, a species in which the leaves are modified spines, the miner activity is restricted to the stem. The aim of this paper was to document the morphological and anatomical differences in the infected and uninfected stems of C. minensis due to the feeding habit of the mining agent. Fresh tissue samples of non-mined and mined young stem of C minensis were collected and examined in transverse sections. We hypothesize that the infection begins following mating when the females scratch the surface of the stem or while they feed on fruits and lay eggs, which subsequently develop into larvae, invading the cactus stem. The insect's miner larvae had mostly consumed the parenchyma tissue towards the center of the stem, and periderm formed along the entire path of the insect. This meristematic tissue or "wound periderm" is a common response for compartmentalization to isolate the damaged tissue, in this case the incubating chamber, in which the eggs will be placed. There were no signs of consumption of vascular tissue in the infested samples, further suggesting a compartmentalized infestation. The nest chamber was found in the stem pith region, with periderm surrounding an insect's miner pupa inside identified as a member of the Cerambycidae. The mining insect depends on a host plant to complete the life cycle; however, the nature of this partnership and the long-term effects of the insect on the plant tissue are unknown. The complex mechanisms by which herbivorous insects control the morphogenesis of the plant host are discussed. We propose that C. minensis has a recognition system to identify insect attack and evaluate the effectiveness of early response triggering compartmentalized defense mechanisms by protecting the injured area with a new layer of periderm.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Computer vision based eyewear selector

[EN]This paper describes a low-cost system that allows the user to visualize different glasses models in live video. The user can also move the glasses to adjust its position on the face. The system, which runs at 9.5 frames/s on general-purpose hardware, has a homeostatic module that keeps image parameters controlled. This is achieved by using a camera with motorized zoom, iris, white balance, etc. This feature can be specially useful in environments with changing illumination and shadows, like in an optical shop. The system also includes a face and eye detection module and a glasses management module.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Accident or homicide - virtual crime scene reconstruction using 3D methods

The analysis and reconstruction of forensically relevant events, such as traffic accidents, criminal assaults and homicides are based on external and internal morphological findings of the injured or deceased person. For this approach high-tech methods are gaining increasing importance in forensic investigations. The non-contact optical 3D digitising system GOM ATOS is applied as a suitable tool for whole body surface and wound documentation and analysis in order to identify injury-causing instruments and to reconstruct the course of event. In addition to the surface documentation, cross-sectional imaging methods deliver medical internal findings of the body. These 3D data are fused into a whole body model of the deceased. Additional to the findings of the bodies, the injury inflicting instruments and incident scene is documented in 3D. The 3D data of the incident scene, generated by 3D laser scanning and photogrammetry, is also included into the reconstruction. Two cases illustrate the methods. In the fist case a man was shot in his bedroom and the main question was, if the offender shot the man intentionally or accidentally, as he declared. In the second case a woman was hit by a car, driving backwards into a garage. It was unclear if the driver drove backwards once or twice, which would indicate that he willingly injured and killed the woman. With this work, we demonstrate how 3D documentation, data merging and animation enable to answer reconstructive questions regarding the dynamic development of patterned injuries, and how this leads to a real data based reconstruction of the course of event.

Comparison of freehand-navigated and aiming device-navigated targeting of liver lesions

BACKGROUND Accurate needle placement is crucial for the success of percutaneous radiological needle interventions. We compared three guiding methods using an optical-based navigation system: freehand, using a stereotactic aiming device and active depth control, and using a stereotactic aiming device and passive depth control. METHODS For each method, 25 punctures were performed on a non-rigid phantom. Five 1 mm metal screws were used as targets. Time requirements were recorded, and target positioning errors (TPE) were measured on control scans as the distance between needle tip and target. RESULTS Time requirements were reduced using the aiming device and passive depth control. The Euclidian TPE was similar for each method (4.6 ± 1.2-4.9 ± 1.7 mm). However, the lateral component was significantly lower when an aiming device was used (2.3 ± 1.3-2.8 ± 1.6 mm with an aiming device vs 4.2 ± 2.0 mm without). DISCUSSION Using an aiming device may increase the lateral accuracy of navigated needle insertion.

Seawater carbonate chemistry, survival, metamorphosis and respiration rate of coral Acropora digitifera during experiments, 2011

Ocean acidification may negatively impact the early life stages of some marine invertebrates including corals. Although reduced growth of juvenile corals in acidified seawater has been reported, coral larvae have been reported to demonstrate some level of tolerance to reduced pH. We hypothesize that the observed tolerance of coral larvae to low pH may be partly explained by reduced metabolic rates in acidified seawater because both calcifying and non-calcifying marine invertebrates could show metabolic depression under reduced pH in order to enhance their survival. In this study, after 3-d and 7-d exposure to three different pH levels (8.0, 7.6, and 7.3), we found that the oxygen consumption of Acropora digitifera larvae tended to be suppressed with reduced pH, although a statistically significant difference was not observed between pH conditions. Larval metamorphosis was also observed, confirming that successful recruitment is impaired when metamorphosis is disrupted, despite larval survival. Results also showed that the metamorphosis rate significantly decreased under acidified seawater conditions after both short (2 h) and long (7 d) term exposure. These results imply that acidified seawater impacts larval physiology, suggesting that suppressed metabolism and metamorphosis may alter the dispersal potential of larvae and subsequently reduce the resilience of coral communities in the near future as the ocean pH decreases.