Potencial da espectroscopia no infravermelho próximo para distinção de carvão de madeira de Eucalyptus e nativa

The objective of this study was to evaluate the potential of near infrared spectroscopy (NIRS) associated with multivariate statistics to distinguish coal produced from wood of planted and native forests. Timber forest species from the C errado (Cedrela sp., Aspidosperma sp., Jacaranda sp. and unknown species) and Eucalyptus clones from forestry companies (Vallourec and Cenibra) were carbonized in the final temperatures of 300, 500 and 700°C. In each heat treatment were carbonized 15 specimens of each vegetal material totaling 270 samples (3 treatments x 15 reps x 6 materials) produced in 18 carbonization (3 treatments x 6 materials). The acquisition of the spectra of coals in the near infrared using a spectrometer was performed. Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS-R) were carried out in the spectra. NIR Spectroscopy associated with PCA was not able to differentiate charcoals produced from native and planted woods when utilizing all carbonized samples at different temperatures in the same analysis; The PCA of all charcoals was able to distinguish the samples depending on temperature in which they were carbonized. However, the separation of native and planted charcoal was possible when the samples were analyzed separately by final temperature. The prediction of native or planted classes by PLS-R presented better performance for samples carbonized at 300°C followed by those at 500°C, 700°C and for all together.

SIRCo: uma arquitetura para Sensoriamento Inteligente de Rádios Cognitivos

The increased demand for using the Industrial, Scientific and Medical (ISM) unlicensed frequency spectrum has caused interference problems and lack of resource availability for wireless networks. Cognitive radio (CR) have emerged as an alternative to reduce interference and intelligently use the spectrum. Several protocols were proposed aiming to mitigate these problems, but most have not been implemented in real devices. This work presents an architecture for Intelligent Sensing for Cognitive Radios (ISCRa), and a spectrum decision model (SDM) based on Artificial Neural Networks (ANN), which uses as input a database with local spectrum behavior and a database with primary users information. For comparison, a spectrum decision model based on AHP, which employs advanced techniques in its spectrum decision method was implemented. Another spectrum decision model that considers only a physical parameter for channel classification was also implemented. Spectrum decision models evaluated, as well as ISCRa's architecture were developed in GNU-Radio framework and implemented on real nodes. Evaluation of SDMs considered metrics of: delivery rate, latency (Round Trip Time - RTT) and handoff. Experiments on real nodes showed that ISCRa architecture with ANN based SDM increased packet delivery rate and presented fewer frequency variation (handoff) while maintaining latency. Considering higher bandwidth as application's Quality of Service requirement, ANN-SDM obtained the best results when compared to other SDM for cognitive radio networks (CRN).

Análise energética da madeira e do carvão de híbridos entre Corymbia citriodora (Hook.) K.D. Hill & L.A.S. Johnson e Corymbia torelliana (F. Muell.) K.D. Hill & L.A.S. Johnson

This research aimed to evaluate the wood and charcoal quality of hybrids clone of the crossing C. citriodora with C. torelliana in two different locations for charcoal production. Seven with 3,75 years old clones, planted at country of Itamarandiba – MG, and six 6,42 years old clones, planted in Dionísio – MG, were studied. For wood and charcoal quality analysis, samples were collected along the stem of the trees until the commercial height. Properties study of the wood was done by chemical analysis, basic density, superior heat power, and thermogravimetric analysis. The wood samples were carbonized in laboratory conditions with heating rate of 1.67 0 C.min -1 , starting at 100 0 C until 450 0 C and keeping on this temperature for 30 minutes. It were determined the carbonizations gravimetric yield, all in dry basis. The wood quality was evaluated based on the chemical immediate analysis, relative apparent density, and gross heating value. The experiment was installed according to the completely randomized design, with five repetitions. The collected data were submitted to analysis of variance and, when the evaluated effects were significant by “F” test, was applied the Scott-Knott test at 5% probability for multiple comparisons. For correlation analysis, Pearson correlation coefficient, tested by the "t" test at 5% probability was used. Results showed variability of wood between the genetic materials evaluated in relation to place and plant crossing. The thermal analysis of the wood showed significant variation between clones and it was possible to differentiate two stages of degradation (hemicelluloses and cellulose). The majority of the clones presented satisfactory properties for the charcoal production, while, clone 3, planted in Itamarandiba, obtained the best performance due it have the higher yield and energetic efficiency, thus, achieving the best potential for charcoal production. However, clone 9, planted in Dionísio, was the less indicated for charcoal production since it presented the lowest energetic efficiency, gravimetric yield, and densities.