982 resultados para Biology, Bioinformatics|Computer Science
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In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.
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This paper presents a usability evaluation of the MTE (Ministry of Labor e Employment) website in order to measure the effectiveness, efficiency and user satisfaction regarding the website. The participants were 12 users (07 users were female and 05 male). The results indicate that although the education level of all participants and computing experience, many of them have had difficulty in finding information and do not recommend the site. © 2013 Springer-Verlag Berlin Heidelberg.
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The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.
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Many topics related to association mining have received attention in the research community, especially the ones focused on the discovery of interesting knowledge. A promising approach, related to this topic, is the application of clustering in the pre-processing step to aid the user to find the relevant associative patterns of the domain. In this paper, we propose nine metrics to support the evaluation of this kind of approach. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Some experiments were done in order to present how the metrics can be used and their usefulness. © 2013 Springer-Verlag GmbH.
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Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.
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Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Bio-molecular computing, 'computations performed by bio-molecules', is already challenging traditional approaches to computation both theoretically and technologically. Often placed within the wider context of ´bio-inspired' or 'natural' or even 'unconventional' computing, the study of natural and artificial molecular computations is adding to our understanding of biology, physical sciences and computer science well beyond the framework of existing design and implementation paradigms. In this introduction, We wish to outline the current scope of the field and assemble some basic arguments that, bio-molecular computation is of central importance to computer science, physical sciences and biology using HOL - Higher Order Logic. HOL is used as the computational tool in our R&D work. DNA was analyzed as a chemical computing engine, in our effort to develop novel formalisms to understand the molecular scale bio-chemical computing behavior using HOL. In our view, our focus is one of the pioneering efforts in this promising domain of nano-bio scale chemical information processing dynamics.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Image segmentation is a process frequently used in several different areas including Cartography. Feature extraction is a very troublesome task, and successful results require more complex techniques and good quality data. The aims of this paper is to study Digital Image Processing techniques, with emphasis in Mathematical Morphology, to use Remote Sensing imagery, making image segmentation, using morphological operators, mainly the multi-scale morphological gradient operator. In the segmentation process, pre-processing operators of Mathematical Morphology were used, and the multi-scales gradient was implemented to create one of the images used as marker image. Orbital image of the Landsat satellite, sensor TM was used. The MATLAB software was used in the implementation of the routines. With the accomplishment of tests, the performance of the implemented operators was verified and carried through the analysis of the results. The extration of linear feature, using mathematical morphology techniques, can contribute in cartographic applications, as cartographic products updating. The comparison to the best result obtained was performed by means of the morphology with conventional techniques of features extraction. © Springer-Verlag 2004.
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In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.
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An antioxidant structure-activity study is carried out in this work with ten flavonoid compounds using quantum chemistry calculations with the functional of density theory method. According to the geometry obtained by using the B3LYP/6-31G(d) method, the HOMO, ionization potential, stabilization energies, and spin density distribution showed that the flavonol is the more antioxidant nucleus. The spin density contribution is determinant for the stability of the free radical. The number of resonance structures is related to the pi-type electron system. 3-hydroxyflavone is the basic antioxidant structure for the simplified flavonoids studied here. The electron abstraction is more favored in the molecules where ether group and 3-hydroxyl are present, nonetheless 2,3-double bond and carbonyl moiety are facultative.
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A theoretical study of structures of the 1,7,1 l,17-tetraoxa-2,6,12,16-tetraaza-cycloeicosane ligand ([20]AneN(4)O(4)) coordinated to Fe2+, Co2+, Ni2+, Ru2+, Rh2+, and Pd2+ transition metals ions was carried out with the DFT/B3LYP method. Complexes were fully optimized in C-s symmetry with the metal ions coordinated either to nitrogen (1a) or oxygen atoms (1b). For all the cases performed in this work, 1a was always more stable than 1b. Considering each row it is possible to see that the binding energy increases with the atomic number. The M2+ cation binding energies increase in the following order: Fe2+ < Ru2+ < Co2+ < Ni2+ < Rh2+ < Pd2+. In addition, it was observed the preference of Pd2+ and Rh2+ complexes for a tetrahedral arrangement, while Fe2+, Ru2+, Co2+, Ni2+ complexes had a preference for the octahedral arrangement. From the orbital representation results, it was seen that 1b unsymmetrical orbitals may influence the susceptibility over metal ions orientation toward heteroatoms orbitals.
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Molecular dynamics simulations of the model protein chignolin with explicit solvent were carried out, in order to analyze the influence of the Berendsen thermostat on the evolution and folding of the peptide. The dependence of the peptide behavior on temperature was tested with the commonly employed thermostat scheme consisting of one thermostat for the protein and another for the solvent. The thermostat coupling time of the protein was increased to infinity, when the protein is not in direct contact with the thermal bath, a situation known as minimally invasive thermostat. In agreement with other works, it was observed that only in the last situation the instantaneous temperature of the model protein obeys a canonical distribution. As for the folding studies, it was shown that, in the applications of the commonly utilized thermostat schemes, the systems are trapped in local minima regions from which it has difficulty escaping. With the minimally invasive thermostat the time that the protein needs to fold was reduced by two to three times. These results show that the obstacles to the evolution of the extended peptide to the folded structure can be overcome when the temperature of the peptide is not directly controlled.
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Xylanases (EC 3.2.1.8 endo-1,4-glycosyl hydrolase) catalyze the hydrolysis of xylan, an abundant hemicellulose of plant cell walls. Access to the catalytic site of GH11 xylanases is regulated by movement of a short beta-hairpin, the so-called thumb region, which can adopt open or closed conformations. A crystallographic study has shown that the D11F/R122D mutant of the GH11 xylanase A from Bacillus subtilis (BsXA) displays a stable "open" conformation, and here we report a molecular dynamics simulation study comparing this mutant with the native enzyme over a range of temperatures. The mutant open conformation was stable at 300 and 328 K, however it showed a transition to the closed state at 338 K. Analysis of dihedral angles identified thumb region residues Y113 and T123 as key hinge points which determine the open-closed transition at 338 K. Although the D11F/R122D mutations result in a reduction in local inter-intramolecular hydrogen bonding, the global energies of the open and closed conformations in the native enzyme are equivalent, suggesting that the two conformations are equally accessible. These results indicate that the thumb region shows a broader degree of energetically permissible conformations which regulate the access to the active site region. The R122D mutation contributes to the stability of the open conformation, but is not essential for thumb dynamics, i.e., the wild type enzyme can also adapt to the open conformation.