Chemical gas sensors based on functionalized self-actuated piezo-resistive cantilevers

Der Schwerpunkt dieser Arbeit liegt in der Anwendung funktionalisierter Mikrocantilever mit integrierter bimorpher Aktuation und piezo-resistiver Detektion als chemische Gassensoren für den schnellen, tragbaren und preisgünstigen Nachweis verschiedener flüchtiger Substanzen. Besondere Beachtung erfährt die Verbesserung der Cantilever-Arbeitsleistung durch den Betrieb in speziellen Modi. Weiterer Schwerpunkt liegt in der Untersuchung von spezifischen Sorptionswechselwirkungen und Anwendung von innovativen Funktionsschichten, die bedeutend auf die Sensorselektivität wirken.

Relação da higiene bucal com a sensibilidade gustativa e nutrição em idosos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Damage detection by using FBGs and strain field pattern recognition techniques

A novel methodology for damage detection and location in structures is proposed. The methodology is based on strain measurements and consists in the development of strain field pattern recognition techniques. The aforementioned are based on PCA (principal component analysis) and damage indices (T 2 and Q). We propose the use of fiber Bragg gratings (FBGs) as strain sensors

Human-computer interaction based on visual hand-gesture recognition using volumetric spatiograms of local binary patterns

A more natural, intuitive, user-friendly, and less intrusive Human–Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.

Polarization vision and its role in biological signaling

Visual pigments, the molecules in photoreceptors that initiate the process of vision, are inherently dichroic, differentially absorbing light according to its axis of polarization. Many animals have taken advantage of this property to build receptor systems capable of analyzing the polarization of incoming light, as polarized light is abundant in natural scenes (commonly being produced by scattering or reflection). Such polarization sensitivity has long been associated with behavioral tasks like orientation or navigation. However, only recently have we become aware that it can be incorporated into a high-level visual perception akin to color vision, permitting segmentation of a viewed scene into regions that differ in their polarization. By analogy to color vision, we call this capacity polarization vision. It is apparently used for tasks like those that color vision specializes in: contrast enhancement, camouflage breaking, object recognition, and signal detection and discrimination. While color is very useful in terrestrial or shallow-water environments, it is an unreliable cue deeper in water due to the spectral modification of light as it travels through water of various depths or of varying optical quality. Here, polarization vision has special utility and consequently has evolved in numerous marine species, as well as at least one terrestrial animal. In this review, we consider recent findings concerning polarization vision and its significance in biological signaling.

Hand gesture recognition system based in computer vision and machine learning : applications on human-machine interaction

Sendo uma forma natural de interação homem-máquina, o reconhecimento de gestos implica uma forte componente de investigação em áreas como a visão por computador e a aprendizagem computacional. O reconhecimento gestual é uma área com aplicações muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utilização de dispositivos extras. Assim, o objectivo principal da investigação na área de reconhecimento de gestos aplicada à interacção homemmáquina é o da criação de sistemas, que possam identificar gestos específicos e usálos para transmitir informações ou para controlar dispositivos. Para isso as interfaces baseados em visão para o reconhecimento de gestos, necessitam de detectar a mão de forma rápida e robusta e de serem capazes de efetuar o reconhecimento de gestos em tempo real. Hoje em dia, os sistemas de reconhecimento de gestos baseados em visão são capazes de trabalhar com soluções específicas, construídos para resolver um determinado problema e configurados para trabalhar de uma forma particular. Este projeto de investigação estudou e implementou soluções, suficientemente genéricas, com o recurso a algoritmos de aprendizagem computacional, permitindo a sua aplicação num conjunto alargado de sistemas de interface homem-máquina, para reconhecimento de gestos em tempo real. A solução proposta, Gesture Learning Module Architecture (GeLMA), permite de forma simples definir um conjunto de comandos que pode ser baseado em gestos estáticos e dinâmicos e que pode ser facilmente integrado e configurado para ser utilizado numa série de aplicações. É um sistema de baixo custo e fácil de treinar e usar, e uma vez que é construído unicamente com bibliotecas de código. As experiências realizadas permitiram mostrar que o sistema atingiu uma precisão de 99,2% em termos de reconhecimento de gestos estáticos e uma precisão média de 93,7% em termos de reconhecimento de gestos dinâmicos. Para validar a solução proposta, foram implementados dois sistemas completos. O primeiro é um sistema em tempo real capaz de ajudar um árbitro a arbitrar um jogo de futebol robótico. A solução proposta combina um sistema de reconhecimento de gestos baseada em visão com a definição de uma linguagem formal, o CommLang Referee, à qual demos a designação de Referee Command Language Interface System (ReCLIS). O sistema identifica os comandos baseados num conjunto de gestos estáticos e dinâmicos executados pelo árbitro, sendo este posteriormente enviado para um interface de computador que transmite a respectiva informação para os robôs. O segundo é um sistema em tempo real capaz de interpretar um subconjunto da Linguagem Gestual Portuguesa. As experiências demonstraram que o sistema foi capaz de reconhecer as vogais em tempo real de forma fiável. Embora a solução implementada apenas tenha sido treinada para reconhecer as cinco vogais, o sistema é facilmente extensível para reconhecer o resto do alfabeto. As experiências também permitiram mostrar que a base dos sistemas de interação baseados em visão pode ser a mesma para todas as aplicações e, deste modo facilitar a sua implementação. A solução proposta tem ainda a vantagem de ser suficientemente genérica e uma base sólida para o desenvolvimento de sistemas baseados em reconhecimento gestual que podem ser facilmente integrados com qualquer aplicação de interface homem-máquina. A linguagem formal de definição da interface pode ser redefinida e o sistema pode ser facilmente configurado e treinado com um conjunto de gestos diferentes de forma a serem integrados na solução final.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction

Tese de Doutoramento em Engenharia de Eletrónica e de Computadores

Formulation and Implementation of Air Quality Control Pogrammes : Patterns of Interest Consideration

This article investigates some central aspects of the relationships between programme structure and implementation of sulphur dioxide air quality control policies. Previous implementation research, primarily adopting American approaches, has neglected the connections between the processes of programme formulation and implementation. 'Programme', as the key variable in implementation studies, has been defined too narrowly. On the basis of theoretical and conceptual reflections and provisional empirical results from studies in France, Italy, England, and the Federal Republic of Germany, the authors demonstrate that an integral process analysis using a more extended programme concept is necessary if patterns of interest recognition in policies are to be discovered. Otherwise, the still important question of critical social science cannot be answered, namely, what is the impact of special interests upon implementation processes.

Community introduction of practice parameters for autistic spectrum disorders: Advancing early recognition.

OBJECTIVES: Within a strong interdisciplinary framework, improvement in the quality of care for children with autistic spectrum disorders through a 2 year implementation program of Practice Parameters, aimed principally at improving early detection and intervention. METHOD: We developed Practice Parameters (PPs) for Pervasive Developmental Disorders and circulated the PPs to all child and adolescent psychiatrists practicing in the region. RESULTS: PP development and parallel information strategies resulted in a significant decrease of 1.5 years in the mean-age-at-diagnosis. However, further analysis indicated that improvement was only transient. CONCLUSION: Despite the encouraging improvement in mean-age-at-diagnosis 2 years after PP implementation, other indicators showed a failure to maintain the improvements. A systematic screening program would be the most reliable method to reinforce the PPs.

Development of a duplex real-time PCR for the detection of Rickettsia spp. and typhus group rickettsia in clinical samples.

Molecular diagnosis using real-time polymerase chain reaction (PCR) may allow earlier diagnosis of rickettsiosis. We developed a duplex real-time PCR that amplifies (1) DNA of any rickettsial species and (2) DNA of both typhus group rickettsia, that is, Rickettsia prowazekii and Rickettsia typhi. Primers and probes were selected to amplify a segment of the 16S rRNA gene of Rickettsia spp. for the pan-rickettsial PCR and the citrate synthase gene (gltA) for the typhus group rickettsia PCR. Analytical sensitivity was 10 copies of control plasmid DNA per reaction. No cross-amplification was observed when testing human DNA and 22 pathogens or skin commensals. Real-time PCR was applied to 16 clinical samples. Rickettsial DNA was detected in the skin biopsies of three patients. In one patient with severe murine typhus, the typhus group PCR was positive in a skin biopsy from a petechial lesion and seroconversion was later documented. The two other patients with negative typhus group PCR suffered from Mediterranean and African spotted fever, respectively; in both cases, skin biopsy was performed on the eschar. Our duplex real-time PCR showed a good analytical sensitivity and specificity, allowing early diagnosis of rickettsiosis among three patients, and recognition of typhus in one of them.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

Example Based Learning for View-Based Human Face Detection

We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face'' and "non-face'' prototype clusters. At each image location, the local pattern is matched against the distribution-based model, and a trained classifier determines, based on the local difference measurements, whether or not a human face exists at the current image location. We provide an analysis that helps identify the critical components of our system.

Motion cue analysis for parkinsonian gait recognition

This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.

Chlamydial infection in a high risk population: association with vaginal flora patterns

This study aimed to determine the frequency of Chlamydia trachomatis (CT) infection among high risk Brazilian women and evaluate its association with vaginal flora patterns.This was a cross-sectional study, performed in an outpatient clinic of Bauru State Hospital, So Paulo, Brazil. A total of 142 women were included from 2006 to 2008. Inclusion criteria was dyspareunia, pain during bimanual exam, presence of excessive cervical mucus, cervical ectopy or with three or more episodes of abnormal vaginal flora (AVF) in the previous year before enrollment. Endocervical CT testing was performed by PCR. Vaginal swabs were collected for microscopic assessment of the microbial flora pattern. Gram-stained smears were classified in normal, intermediate or bacterial vaginosis (BV), and recognition of Candida sp. morphotypes. Wet mount smears were used for detection of Trichomonas vaginalis and aerobic vaginitis (AV).Thirty-four of 142 women (23.9%) tested positive for CT. AVF was found in 50 (35.2%) cases. The most frequent type of AVF was BV (17.6%). CT was strongly associated with the presence of AV (n = 7, 4.9%, P = 0.018), but not BV (n = 25, 17.6%, P = 0.80) or intermediate flora (n = 18, 12.7%, P = 0.28).A high rate of chlamydial infection was found in this population. Chlamydia infection is associated with aerobic vaginitis.