Java software platform for the development of advanced robotic virtual laboratories

This article presents an interactive Java software platform which enables any user to easily create advanced virtual laboratories (VLs) for Robotics. This novel tool provides both support for developing applications with full 3D interactive graphical interface and a complete functional framework for modelling and simulation of arbitrary serial-link manipulators. In addition, its software architecture contains a high number of functionalities included as high-level tools, with the advantage of allowing any user to easily develop complex interactive robotic simulations with a minimum of programming. In order to show the features of the platform, the article describes, step-by-step, the implementation methodology of a complete VL for Robotics education using the presented approach. Finally, some educational results about the experience of implementing this approach are reported.

Constrained self-organizing feature map to preserve feature extraction topology

In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In the same way, the same features extracted from different locations could mean different actions for a 3D HCI system. In this paper, we present a self-organizing feature map able to preserve the topology of locations of an n-dimensional space in which the vector of features have been extracted. The main contribution is to implicitly preserving the topology of the original space because considering the locations of the extracted features and their topology could ease the solution to certain problems. Specifically, the paper proposes the n-dimensional constrained self-organizing map preserving the input topology (nD-SOM-PINT). Features in adjacent areas of the n-dimensional space, used to extract the feature vectors, are explicitly in adjacent areas of the nD-SOM-PINT constraining the neural network structure and learning. As a study case, the neural network has been instantiate to represent and classify features as trajectories extracted from a sequence of images into a high level of semantic understanding. Experiments have been thoroughly carried out using the CAVIAR datasets (Corridor, Frontal and Inria) taken into account the global behaviour of an individual in order to validate the ability to preserve the topology of the two-dimensional space to obtain high-performance classification for trajectory classification in contrast of non-considering the location of features. Moreover, a brief example has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.

Características de ecossistema e sustentabilidade: estudo sobre a vegetação original e remanescente da bacia hidrográfica do Rio Canoas

Com o objetivo de comparar em termos de paisagem, a vegetação florestal nativa com os fragmentos da vegetação remanescente na bacia hidrográfica do Rio Canoas, situada na divisa dos Estados de São Paulo (à Nordeste) e Minas Gerais (à Centro-Oeste), busca-se dar subsídios aos atores locais para trabalhar políticas públicas com vistas à sustentabilidade do uso dos recursos naturais na região. Foram mapeados sete tipos de vegetação, com destaque para o cerrado e a floresta estacional semidecidual. O método do estudo é exploratório, realizado em fontes secundárias, pesquisa bibliográfica e documental, baseado no estudo de mapas e suas simulações, dados do IBGE, Embrapa, Ministério do Meio Ambiente e trabalhos de autores, como: Cogo (1987), Coutinho (2000) e Bozini (2005). Observou-se que a bacia hidrográfica objeto em estudo é degradada historicamente pelos diversos usos e ocupações do solo e sua maior parte ainda está sujeita à um elevado nível de perturbação, seja pela pecuária, ou mesmo pelas plantações de laranja, milho, eucalipto, cana-de-açúcar e, principalmente, pela cultura do café.

Application-Based Analysis of Register File Criticality for Reliability Assessment in Embedded Microprocessors

There is an increasing concern to reduce the cost and overheads during the development of reliable systems. Selective protection of most critical parts of the systems represents a viable solution to obtain a high level of reliability at a fraction of the cost. In particular to design a selective fault mitigation strategy for processor-based systems, it is mandatory to identify and prioritize the most vulnerable registers in the register file as best candidates to be protected (hardened). This paper presents an application-based metric to estimate the criticality of each register from the microprocessor register file in microprocessor-based systems. The proposed metric relies on the combination of three different criteria based on common features of executed applications. The applicability and accuracy of our proposal have been evaluated in a set of applications running in different microprocessors. Results show a significant improvement in accuracy compared to previous approaches and regardless of the underlying architecture.