Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Perfil de índices de refração do cristalino humano: simulação computacional

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sequenciamento de linhas de montagem múltiplas em ambiente de produção enxuta utilizando simulação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Peptídeos cíclicos em espécies do semiárido brasileiro e uma cultivada: caracterização e atividade biológica

Pós-graduação em Química - IQ

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

Modelagem e otimização por metodologia de superfícies de resposta: um estudo em arames de aço SAE 9254 para molas automobilísticas

Pós-graduação em Engenharia Mecânica - FEG

Jatrophidin I, a cyclic peptide from Brazilian Jatropha curcas L.: Isolation, characterization, conformational studies and biological activity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de extensões para um sistema de carregamento e descarregamento de navios

One of the reasons that influences the efficience of a port terminal that is especialized in movement of containers is in the process of their loading and unloading. The fundamental idea is to determine a plan, to each port in order to decrease the number of total movement of loading and unloading that are necessary during the ship route to every port so that they save time and consequently reduce costs. The goal of this research was to present improvement in the program, written in language C, used to solve to problem of loading and unloading of ships, a NP-complete problem, through the meta-heuristics Simulated Annealing. With the improvement made, an average of 50% reduction of necessary time was gotten to solve the problem in 45 analised instances and in a specific group of these instances the average reduction reached 77 and in 10 instances there was even an improvement in the solution

Estudo dos efeitos do tamanho e comensurabilidade nas correntes críticas em fitas supercondutoras do tipo II com redes periódicas de pinnings à temperatura finita

Pós-graduação em Ciência e Tecnologia de Materiais - FC

Ribifolin, an orbitide from jatropha ribifolia, and its potential antimalarial activity

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A radial basis function network (RBFN) for function approximation

A radial basis function network (RBFN) circuit for function approximation is presented. Simulation and experimental results show that the network has good approximation capabilities. The RBFN was a squared hyperbolic secant with three adjustable parameters amplitude, width and center. To test the network a sinusoidal and sine function,vas approximated.

Correntes críticas e comportamento dinâmico dos vórtices em fitas supercondutoras do tipo II com arranjos conformes de centros de aprisionamento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.