Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Inclusive search for a vector-like T quark with charge 2/3 in pp collisions at root s=8 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fractional fermion charges induced by axial-vector and vector gauge potentials and parity anomaly in planar graphenelike structures

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Temporal and Spatial Scaling of the Genetic Structure of a Vector-Borne Plant Pathogen

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Thermal and structural study of glasses in the binary system TeO2-Pb(PO3)(2)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Characterization, inclusion mode, phase-solubility and in vitro release studies of inclusion binary complexes with cyclodextrins and meglumine using sulfamerazine as model drug

In order to investigate the effect on the aqueous solubility and release rate of sulfamerazine (SMR) as model drug, inclusion complexes with beta-cyclodextrin (beta CD), methyl-beta-cyclodextrin (M beta CD) and hydroxypropyl-beta-cyclodextrin (HP beta CD) and a binary system with meglumine (MEG) were developed. The formation of 1: 1 inclusion complexes of SMR with the CDs and a SMR: MEG binary system in solution and in solid state was revealed by phase solubility studies (PSS), nuclear magnetic resonance (NMR), Fourier-transform infrared spectroscopy (FT-IR), thermal analysis and X-Ray diffractometry (XRD) studies. The CDs solubilization of SMR could be improved by ionization of the drug molecule through pH adjustments. The higher apparent stability constants of SMR:CDs complexes were obtained in pH 2.00, demonstrating that CDs present more affinity for the unionized drug. The best approach for SMR solubility enhancement results from the combination of MEG and pH adjustment, with a 34-fold increment and a S-max of 54.8 mg/ml. The permeability of the drug was reduced due to the presence of beta CD, M beta CD, HP beta CD and MEG when used as solubilizers. The study then suggests interesting applications of CD or MEG complexes for modulating the release rate of SMR through semipermeable membranes.

Seasonal genetic partitioning in the neotropical malaria vector, Anopheles darlingi

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

Entoepidemiology of Chagas disease in northwest Sao Paulo and cytogenetic analysis of its main vector, Triatoma sordida (Hemiptera: Triatominae)

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

Demixing and symmetry breaking in binary dipolar Bose-Einstein-condensate solitons

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

Measuring the Spin of Black Holes in Binary Systems Using Gravitational Waves

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

Statics and dynamics of a binary dipolar Bose-Einstein condensate soliton

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

The NINJA-2 project: detecting and characterizing gravitational waveforms modelled using numerical binary black hole simulations

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave (GW) astrophysics communities. The purpose of NINJA is to study the ability to detect GWs emitted from merging binary black holes (BBH) and recover their parameters with next-generation GW observatories. We report here on the results of the second NINJA project, NINJA-2, which employs 60 complete BBH hybrid waveforms consisting of a numerical portion modelling the late inspiral, merger, and ringdown stitched to a post-Newtonian portion modelling the early inspiral. In a 'blind injection challenge' similar to that conducted in recent Laser Interferometer Gravitational Wave Observatory (LIGO) and Virgo science runs, we added seven hybrid waveforms to two months of data recoloured to predictions of Advanced LIGO (aLIGO) and Advanced Virgo (AdV) sensitivity curves during their first observing runs. The resulting data was analysed by GW detection algorithms and 6 of the waveforms were recovered with false alarm rates smaller than 1 in a thousand years. Parameter-estimation algorithms were run on each of these waveforms to explore the ability to constrain the masses, component angular momenta and sky position of these waveforms. We find that the strong degeneracy between the mass ratio and the BHs' angular momenta will make it difficult to precisely estimate these parameters with aLIGO and AdV. We also perform a large-scale Monte Carlo study to assess the ability to recover each of the 60 hybrid waveforms with early aLIGO and AdV sensitivity curves. Our results predict that early aLIGO and AdV will have a volume-weighted average sensitive distance of 300 Mpc (1 Gpc) for 10M circle dot + 10M circle dot (50M circle dot + 50M circle dot) BBH coalescences. We demonstrate that neglecting the component angular momenta in the waveform models used in matched-filtering will result in a reduction in sensitivity for systems with large component angular momenta. This reduction is estimated to be up to similar to 15% for 50M circle dot + 50M circle dot BBH coalescences with almost maximal angular momenta aligned with the orbit when using early aLIGO and AdV sensitivity curves.

Semliki Forest Virus as a Vector: Pros and Cons for Its Use in Biopharmaceuticals Production

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

Genetic Variability and Geographical Diversity of the Main Chagas' Disease Vector Panstrongylus megistus (Hemiptera: Triatominae) in Brazil Based on Ribosomal DNA Intergenic Sequences

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Wide vector solitons in systems with time- and space-modulated nonlinearities

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)