Numerical Assessment of the out-of-plane response of a brick masonry structure without box behaviour

This paper presents the assessment of the out-of-plane response due to seismic loading of a masonry structure without rigid diaphragm. This structure corresponds to real scale brick masonry specimen with a main façade connected to two return walls. Two modelling approaches were defined for this evaluation. The first one consisted on macro modelling, whereas the second one on simplified micro modelling. As a first step of this study, static nonlinear analyses were conducted to the macro model aiming at evaluating the out-of-plane response and failure mechanism of the masonry structure. A sensibility analyses was performed in order to assess the mesh size and material model dependency. In addition, the macro models were subjected to dynamic nonlinear analyses with time integration in order to assess the collapse mechanism. Finally, these analyses were also applied to a simplified micro model of the masonry structure. Furthermore, these results were compared to experimental response from shaking table tests. It was observed that these numerical techniques simulate correctly the in-plane behaviour of masonry structures. However, the

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

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

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Tecnologias da informação e comunicação na formação continuada de professores: estudode caso em escolas do Brasil e Portugal com recursos e aplicação do Google+

Tese de Doutoramento em Ciências da Educação (área de especialização em Tecnologia Educativa)

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

Structure and composition of the ground-herb community in a terra-firme Central Amazonian forest

The herb community of tropical forests is very little known, with few studies addressing its structure quantitatively. Even with this scarce body of information, it is clear that the ground herbs are a rich group, comprising 14 to 40% of the species found in total species counts in tropical forests. The present study had the objective of increasing the knowledge about the structure and composition of the ground-herb community and to compare the sites for which there are similar studies. The study was conducted in a tropical non-inundated and evergreen forest 90 km north of Manaus, AM. Ground herbs were surveyed in 22 transects of 40 m², distributed in five plots of 4 ha. The inventoried community was composed of 35 species, distributed in 24 genera and 18 families. Angiosperms were represented by 8 families and Pteridophytes by 10 families. Marantaceae (12 sp) and Cyperaceae (4 sp) were the richest families. Marantaceae and Poaceae were the families with greatest abundance and cover. Marantaceae, Poaceae, Heliconiaceae and Pteridophytes summed 96% of total herb cover, and therefore were responsible for almost all the cover of the community. The 10 most important species had 83.7% of the individuals. In general, the most abundant species were also the most frequent. Richness per transect varied from 7 to 19 species, and abundance varied from 30 to 114 individuals. The community structure was quite similar to 3 other sites in South America and one site in Asia.

Adoção e difusão de aplicações das tecnologias da informação: iniciativas lançadas no âmbito de processos de implantação de aplicações em organizações – estudo de práticas profissionais e proposta de ferramenta de suporte

Tese de Doutoramento Tecnologias e Sistemas de Informação

Structure-property relationships in polymer nanocomposites

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Abundance of two Dendrocincla woodcreepers (aves: Dendrocolaptidae) in relation to forest structure in Central Amazonia

Few studies have been conducted to verify how the structure of the forest affects the occurence and abundance of neotropical birds. Our research was undertaken between January 2002 and July 2004 at the Reserva Ducke, near Manaus (02º55',03º01'S; 59º53',59º59'W) in central Amazonia, to verify how the forest structure affects the occurrence and abundance of two bird species: the Plain-brown Woodcreeper Dendrocincla fuliginosa and the White-chinned Woodcreeper Dendrocincla merula. Bird species occurrence was recorded using lines of 20 mist-nets (one sample unit), along 51 1-km transects distributed along 9 pararel 8 km trails covering an area of 6400 ha. Along these transects, we placed 50 x 50m plots where we recorded forest structure components (tree abundance, canopy openness, leaf litter, standing dead trees, logs, proximity to streams, and altitude). We then related these variables to bird occurence and abundance using multiple logistic and multiple linear regression models, respectively. We found that D. fuliginosa frequently used plateau areas; being more abundant in areas with more trees. On the other hand, D. merula occurred more frequently and was more abundant in areas with low tree abundance. Our results suggest that although both species overlap in the reserve (both were recorded in at least 68% of the sampled sites), they differ in the way they use the forest microhabitats. Therefore, local variation in the forest structure may contribute to the coexistence of congeneric species and may help to maintain local alpha diversity.

Effects of forest structure components on the occurence, group size and density of groups of bare-face tamarin (Saguinus bicolor - primates: Callitrichinae) in Central Amazonia

This study analyzed the influence of forest structural components on the occurence, size and density of groups of Bare-face Tamarin (Saguinus bicolor) - the most threatened species in the Amazon - and produced the first map of distribution of groups in large-scale spatial within the area of continuous forest. Population censuses were conducted between November 2002 and July 2003, covering 6400 hectares in the Ducke Reserve, Manaus-AM, Brazil. Groups of S. bicolor were recorded 41 times accordingly distributed in the environments: plateau (20); slopes (12); and lowlands (09). The mean group size was 4.8 indiv./group, and ranged from 2 to 11 individuals. In the sites where the groups were recorded, and in an equivalent number of sites where no tamarins were found located at least 500 m from those where they had been recorded, we placed 50 m x 50 m plots to record the following forest structural components: abundance of trees; abundance of lianas; abundance of fruiting trees and lianas; abundance of snags; abundance of logs; percentage of canopy opening; leaf litter depth; and altitude. Bare-face Tamarin more often uses areas with lower abundance of forest logs, smaller canopy opening and with higher abundance of snags, areas in the forest with smaller canopy opening present higher density of S. bicolor groups. Apparently this species does not use the forest in a random way, and may select areas for its daily activities depending on the micro-environmental heterogeneity produced by the forest structural components.

Relationship between galactomannan structure and physicochemical properties of films produced thereof

In this work five sources of galactomannans, Adenanthera pavonina, Cyamopsis tetragonolobus, Caesalpinia pulcherrima, Ceratonia siliqua and Sophora japonica, presenting mannose/galactose ratios of 1.3, 1.7, 2.9, 3.4 and 5.6, respectively, were used to produce galactomannan-based films. These films were characterized in terms of: water vapour, oxygen and carbon dioxide permeabilities (WVP, O 2 P and CO 2 P); moisture content, water solubility, contact angle, elongation-at-break (EB), tensile strength (TS) and glass transition temperature (T g ). Results showed that films properties vary according to the galactomannan source (different galactose distribution) and their mannose/galactose ratio. Water affinity of mannan and galactose chains and the intermolecular interactions of mannose backbone should also be considered being factors that affect films properties. This work has shown that knowing mannose/galactose ratio of galactomannans is possible to foresee galactomannan-based edible films properties.

Influence of glucose concentration on the structure and quantity of biofilms formed by Candida parapsilosis

Candida parapsilosis is nowadays an emerging opportunistic pathogen and its increasing incidence is part related to the capacity to produce biofilm. In addition, one of the most important C. parapsilosis pathogenic risk factors includes the organisms\textquoteright selective growth capabilities in hyper alimentation solutions. Thus, in this study, we investigated the role of glucose in C. parapsilosis biofilm modulation, by studying biofilm formation, matrix composition and structure. Moreover, the expression of biofilm-related genes (BCR1, FKS1 and OLE1) were analyzed in the presence of different glucose percentages. The results demonstrated the importance of glucose in the modulation of C. parapsilosis biofilm. The concentration of glucose had direct implications on the C. parapsilosis transition of yeast cells to pseudohyphae. Additionally, it was demonstrated that biofilm related genes BCR1, FKS1 and OLE1 are involved in biofilm modulation by glucose. The mechanism by which glucose enhances biofilm formation is not fully understood, however with this study we were able to demonstrate that C. parapsilosis respond to stress conditions caused by elevated levels of glucose by up-regulating genes related to biofilm formation (BCR1, FKS1 and OLE1).