Topological triangle characterization with application to object detection from images

A novel mathematical framework inspired on Morse Theory for topological triangle characterization in 2D meshes is introduced that is useful for applications involving the creation of mesh models of objects whose geometry is not known a priori. The framework guarantees a precise control of topological changes introduced as a result of triangle insertion/removal operations and enables the definition of intuitive high-level operators for managing the mesh while keeping its topological integrity. An application is described in the implementation of an innovative approach for the detection of 2D objects from images that integrates the topological control enabled by geometric modeling with traditional image processing techniques. (C) 2008 Published by Elsevier B.V.

An aspect-oriented reference architecture for Software Engineering Environments

Reusable and evolvable Software Engineering Environments (SEES) are essential to software production and have increasingly become a need. In another perspective, software architectures and reference architectures have played a significant role in determining the success of software systems. In this paper we present a reference architecture for SEEs, named RefASSET, which is based on concepts coming from the aspect-oriented approach. This architecture is specialized to the software testing domain and the development of tools for that domain is discussed. This and other case studies have pointed out that the use of aspects in RefASSET provides a better Separation of Concerns, resulting in reusable and evolvable SEEs. (C) 2011 Elsevier Inc. All rights reserved.

Sustentabilidade e responsabilidade socioambiental: crenças provendo a formação de graduandos em administração

This research aims to focus on the education problem, since its source of development is the Research Base: Teachers Training and Qualification of UFRN. Therefore, we seek guidance in the beliefs in sustainability to propose plausible alternatives to promote the education process of UFRN administration undergraduates in order to meet the demands of a market-oriented society, since the market trend is to evolve from environmental guided activities, and future administrators should be trained to meet those conditions. The need to develop an instrument capable of understanding the beliefs of undergraduates on the sustainability problem becomes the object of analysis. This research aims to develop a normative questionnaire to study administration students beliefs in sustainability. The complexity and sensitivity of this research required the integration of various methodological procedures. These proposals were made as follows: analysis and selection of literature, expert validation procedures and psychometric methods and statistics. As for the literature, types of sustainability were identified and categorized, such as: political, social, economic and environmental sustainability. However, it is understood that the educational type, although included in all of those, needed to be converted into another type to fit the theme, since education is believed to be the best way to raise awareness about sustainability. Thus, it was required the categorization of the types, which was defined using criteria such as: contexts, objectives, goals, pathways and hypotheses. The normative questionnaire was the guiding instrument to investigate the role of administration students, regarding the level of knowledge established and regulated by social educational context, especially by becoming a basic condition for carrying out research on beliefs. The study confirmed that the types of sustainability - political, social, economic, environmental and educational - for having institutionalized literatures as sources, in international and national levels, are representative in the identification of future administrators. Therefore, it is believed that the types of sustainability categorized to provide a characterization of sustainability include the structuring of knowledge for undergraduates. The economic and political types, however, were not as representative with respect to their typicality and polarity indices as the educational, environmental and social ones. Although the beliefs of the undergraduates show how much they share ideas on all types, they present more identification with the educational and environmental types. Finally, it is expected that this instrument be subject to application in similar contexts so that it can ascertain whether such statements are part of the knowledge structure of future administrators from other institutions. Therefore, it is expected this strategy to strengthen the validation of the normative questionnaire

Role of the oriented attachment mechanism in the phase transformation of oxide nanocrystals

Bottom-up methods to obtain nanocrystals usually result in metastable phases, even in processes carried out at room temperature or under soft annealing conditions. However, stable phases, often associated with anisotropic shapes, are obtained in only a few special cases. In this paper we report on the synthesis of two well-studied oxides-titanium and zirconium oxide-in the nanometric range, by a novel route based on the decomposition of peroxide complexes of the two metals under hydrothermal soft conditions, obtaining metastable and stable phases in both cases through transformation. High-resolution transmission electron microscopy analysis reveals the existence of typical defects relating to growth by the oriented attachment mechanism in the stable crystals. The results suggest that the mechanism is associated to the phase transformation of these structures.

Structural and surface morphology characterizations of oriented LiNbO3 thin films grown by polymeric precursor method

Polymeric precursor solution was used to deposit LiNbO3 thin films by dip coating on sapphire substrates. The effects of processing variables, such as heat treatment conditions and number of deposited layers, on crystallinity and morphology of the final films were investigated. X-ray diffraction patterns show the oriented growth of the films. The rocking curves, obtained around the (006) LiNbO3 peak, revealed that the shape peak and the FWHM value were influenced by the processing variables. According to these parameters, some films presented very homogeneous dense and smooth surfaces, as shown by the SEM and AFM studies.

High-voltage electrophoretic deposition of preferentially oriented films from multiferroic YMn2O5 nanopowders

Processing of the YMn2O5 powder is very challenging, since it decomposes to YMnO3 and Mn3O4 at temperatures close to 1180 °C, while samples consolidation commonly demands high temperatures. The main goal of this work is to investigate a possibility to prepare thick films of YMn2O5, since their deposition generally requires significantly lower temperatures. Multiferroic YMn 2O5 was synthesized by the hydrothermal method from Y(CH3COO)3·xH2O, Mn(CH 3COO)2·4H2O and KMnO4 precursors. XRD, FE-SEM and TEM analysis showed that the obtained powder was monophasic, with orthorhombic crystal structure and columnar particle shape with mean diameter and length of around 20 and 50 nm, respectively. The obtained powder was suspended in isopropyl alcohol with addition of appropriate binder and deflocculant. This suspension was used for electrophoretic deposition of YMn2O5 thick films under the high-voltage conditions and electric fields ranging from 250 to 2125 V/cm. The films obtained at 1000 V/cm and higher electric fields showed good adhesion, particle packing, homogeneity and very low porosity. It was shown that the deposition in extremely high electric fields (KC=2125 V/cm) can influence the crystal orientation of the films, resulting in formation of preferentially oriented films. © 2012 Elsevier Ltd and Techna Group S.r.l.

Study of Brazilian commercial Oriented Strand Board panels using stress wave

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analysis of the lightning attractive radius of power transmission lines through the use of a physically-oriented model

Models of different degrees of complexity are found in the literature for the estimation of lightning striking distances and attractive radius of objects and structures. However, besides the oversimplifications of the physical nature of the lightning discharge on which most of them are based, till recently the tridimensional structure configuration could not be considered. This is an important limitation, as edges and other details of the object affect the electric field and, consequently, the upward leader initiation. Within this context, the Self-consistent leader initiation and propagation model (SLIM) proposed by Becerra and Cooray is state-of-the-art leader inception and propagation leader model based on the physics of leader discharges which enables the tridimensional geometry of the structure to be taken into account. In this paper, the model is used for estimating the striking distance and attractive radius of power transmission lines. The results are compared with those obtained from the electrogeometric and Eriksson's models. © 2003-2012 IEEE.

Arranjos de Guerra-Peixe para a orquestra da Rádio Nacional do Rio de Janeiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A motivação do aprendiz para a aprendizagem escolar: a perspectiva histórico-cultural

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Discontinuity preserving in TV-L1 optical flow methods

[EN] We analyze the discontinuity preserving problem in TV-L1 optical flow methods. This type of methods typically creates rounded effects at flow boundaries, which usually do not coincide with object contours. A simple strategy to overcome this problem consists in inhibiting the diffusion at high image gradients. In this work, we first introduce a general framework for TV regularizers in optical flow and relate it with some standard approaches. Our survey takes into account several methods that use decreasing functions for mitigating the diffusion at image contours. Consequently, this kind of strategies may produce instabilities in the estimation of the optical flows. Hence, we study the problem of instabilities and show that it actually arises from an ill-posed formulation. From this study, it is possible to come across with different schemes to solve this problem. One of these consists in separating the pure TV process from the mitigating strategy. This has been used in another work and we demonstrate here that it has a good performance. Furthermore, we propose two alternatives to avoid the instability problems: (i) we study a fully automatic approach that solves the problem based on the information of the whole image; (ii) we derive a semi-automatic approach that takes into account the image gradients in a close neighborhood adapting the parameter in each position. In the experimental results, we present a detailed study and comparison between the different alternatives. These methods provide very good results, especially for sequences with a few dominant gradients. Additionally, a surprising effect of these approaches is that they can cope with occlusions. This can be easily achieved by using strong regularizations and high penalizations at image contours.

Sviluppo di un tomografo multi-energy per lo studio pre-clinico di nuove metodiche diagnostiche finalizzate al riconoscimento precoce della patologia tumorale

A new multi-energy CT for small animals is being developed at the Physics Department of the University of Bologna, Italy. The system makes use of a set of quasi-monochromatic X-ray beams, with energy tunable in a range from 26 KeV to 72 KeV. These beams are produced by Bragg diffraction on a Highly Oriented Pyrolytic Graphite crystal. With quasi-monochromatic sources it is possible to perform multi-energy investigation in a more effective way, as compared with conventional X-ray tubes. Multi-energy techniques allow extracting physical information from the materials, such as effective atomic number, mass-thickness, density, that can be used to distinguish and quantitatively characterize the irradiated tissues. The aim of the system is the investigation and the development of new pre-clinic methods for the early detection of the tumors in small animals. An innovative technique, the Triple-Energy Radiography with Contrast Medium (TER), has been successfully implemented on our system. TER consist in combining a set of three quasi-monochromatic images of an object, in order to obtain a corresponding set of three single-tissue images, which are the mass-thickness map of three reference materials. TER can be applied to the quantitative mass-thickness-map reconstruction of a contrast medium, because it is able to remove completely the signal due to other tissues (i.e. the structural background noise). The technique is very sensitive to the contrast medium and is insensitive to the superposition of different materials. The method is a good candidate to the early detection of the tumor angiogenesis in mice. In this work we describe the tomographic system, with a particular focus on the quasi-monochromatic source. Moreover the TER method is presented with some preliminary results about small animal imaging.

Structure learning of graphical models for task-oriented robot grasping

In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the main problems is the development of interaction skills with the surrounding environment, which include the ability to grasp objects. To perform this task the robot needs to sense the environment and acquire the object informations, physical attributes that may influence a grasp. Humans can solve this grasping problem easily due to their past experiences, that is why many researchers are approaching it from a machine learning perspective finding grasp of an object using information of already known objects. But humans can select the best grasp amongst a vast repertoire not only considering the physical attributes of the object to grasp but even to obtain a certain effect. This is why in our case the study in the area of robot manipulation is focused on grasping and integrating symbolic tasks with data gained through sensors. The learning model is based on Bayesian Network to encode the statistical dependencies between the data collected by the sensors and the symbolic task. This data representation has several advantages. It allows to take into account the uncertainty of the real world, allowing to deal with sensor noise, encodes notion of causality and provides an unified network for learning. Since the network is actually implemented and based on the human expert knowledge, it is very interesting to implement an automated method to learn the structure as in the future more tasks and object features can be introduced and a complex network design based only on human expert knowledge can become unreliable. Since structure learning algorithms presents some weaknesses, the goal of this thesis is to analyze real data used in the network modeled by the human expert, implement a feasible structure learning approach and compare the results with the network designed by the expert in order to possibly enhance it.

Application-oriented Mixed Integer Non-Linear Programming

In the most recent years there is a renovate interest for Mixed Integer Non-Linear Programming (MINLP) problems. This can be explained for different reasons: (i) the performance of solvers handling non-linear constraints was largely improved; (ii) the awareness that most of the applications from the real-world can be modeled as an MINLP problem; (iii) the challenging nature of this very general class of problems. It is well-known that MINLP problems are NP-hard because they are the generalization of MILP problems, which are NP-hard themselves. However, MINLPs are, in general, also hard to solve in practice. We address to non-convex MINLPs, i.e. having non-convex continuous relaxations: the presence of non-convexities in the model makes these problems usually even harder to solve. The aim of this Ph.D. thesis is to give a flavor of different possible approaches that one can study to attack MINLP problems with non-convexities, with a special attention to real-world problems. In Part 1 of the thesis we introduce the problem and present three special cases of general MINLPs and the most common methods used to solve them. These techniques play a fundamental role in the resolution of general MINLP problems. Then we describe algorithms addressing general MINLPs. Parts 2 and 3 contain the main contributions of the Ph.D. thesis. In particular, in Part 2 four different methods aimed at solving different classes of MINLP problems are presented. Part 3 of the thesis is devoted to real-world applications: two different problems and approaches to MINLPs are presented, namely Scheduling and Unit Commitment for Hydro-Plants and Water Network Design problems. The results show that each of these different methods has advantages and disadvantages. Thus, typically the method to be adopted to solve a real-world problem should be tailored on the characteristics, structure and size of the problem. Part 4 of the thesis consists of a brief review on tools commonly used for general MINLP problems, constituted an integral part of the development of this Ph.D. thesis (especially the use and development of open-source software). We present the main characteristics of solvers for each special case of MINLP.