897 resultados para Wax Pattern


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For many landholders in the South Pacific, weed control of Mikania micrantha Kunth is conducted by manual or mechanical means, leaving fragments on or below the ground to reshoot and grow. Effects of age, length (number of nodes), and pattern of burial on the survival of stem sections of M. micrantha were examined in the field in Viti Levu, Fiji. The experiment was arranged in a randomized factorial design, with number of nodes, age of stem sections, and pattern (depth and orientation) of stem burial as factors. Stem sections with two or three nodes had significantly greater survival (30% and 25%, respectively) than those with one node (12%). Mature stem sections had a significantly greater survival rate (31%) than young stem sections (13%) when buried in either the horizontal or the vertical position. Vertical plantings had significantly greater survival (43%) than horizontal plantings (10%), and for both orientations survival decreased with depth of burial. Only 8% of stem sections survived when cut into smaller (3 to 5 cm) sections and buried at a depth of 10 cm. This study revealed that cutting the M. micrantha stems into smaller sections (<3 cm) and burying them at depths of 10 cm or greater would improve the overall management of M. micrantha in crop and noncrop systems.

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A high temperature source has been developed and coupled to a high resolution Fourier transform spectrometer to record emission spectra of acetylene around 3 mu m up to 1455 K under Doppler limited resolution (0.015 cm(-1)). The nu(3)-ground state (GS) and nu(2)+nu(4)+nu(5)(Sigma(+)(u) and Delta(u))-GS bands and 76 related hot bands, counting e and f parities separately, are assigned using semiautomatic methods based on a global model to reproduce all related vibration-rotation states. Significantly higher J-values than previously reported are observed for 40 known substates while 37 new e or f vibrational substates, up to about 6000 cm(-1), are identified and characterized by vibration-rotation parameters. The 3 811 new or improved data resulting from the analysis are merged into the database presented by Robert et al. [Mol. Phys. 106, 2581 (2008)], now including 15 562 lines accessing vibrational states up to 8600 cm(-1). A global model, updated as compared to the one in the previous paper, allows all lines in the database to be simultaneously fitted, successfully. The updates are discussed taking into account, in particular, the systematic inclusion of Coriolis interaction.

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We present two discriminative language modelling techniques for Lempel-Ziv-Welch (LZW) based LID system. The previous approach to LID using LZW algorithm was to directly use the LZW pattern tables forlanguage modelling. But, since the patterns in a language pattern table are shared by other language pattern tables, confusability prevailed in the LID task. For overcoming this, we present two pruning techniques (i) Language Specific (LS-LZW)-in which patterns common to more than one pattern table are removed. (ii) Length-Frequency product based (LF-LZW)-in which patterns having their length-frequency product below a threshold are removed. These approaches reduce the classification score (Compression Ratio [LZW-CR] or the weighted discriminant score [LZW-WDS]) for non native languages and increases the LID performance considerably. Also the memory and computational requirements of these techniques are much less compared to basic LZW techniques.

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Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

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A detailed understanding of the mode of packing patterns that leads to the gelation of low molecular mass gelators derived from bile acid esters was carried out using solid state NMR along with complementary techniques such as powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and polarizing optical microscopy (POM). Solid state C-13{H-1} cross polarization (CP) magic angle spinning (MAS) NMR of the low molecularmass gel in its native state was recorded for the first time. A close resemblance in the packing patterns of the gel, xerogel and bulk solid states was revealed upon comparing their C-13{H-1} CPMAS NMR spectral pattern. A doublet resonance pattern of C-13 signals in C-13{H-1}CPMAS NMR spectra were observed for the gelator molecules, whereas the non-gelators showed simple singlet resonance or resulted inthe formation of inclusion complexes/solvates. PXRD patterns revealed a close isomorphous nature of the gelators indicating the similarity in the mode of the packing pattern in their solid state. Direct imaging of the evolution of nanofibers (sol-gel transition) was carried out using POM, which proved the presence of self-assembled fibrillar networks (SAFINs) in the gel. Finally powder X-ray structure determination revealed the presence of two non-equivalent molecules in an asymmetric unit which is responsible for the doublet resonance pattern in the solid state NMR spectra.

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A novel approach for measurement of small rotation angles using imaging method is proposed and demonstrated. A plane mirror placed on a precision rotating table is used for imaging the newly designed composite coded pattern. The imaged patterns are captured with the help of a CCD camera. The angular rotation of the plane mirror is determined from a pair of the images of the pattern, captured once before and once after affecting the tilt of the mirror. Both simulation and experimental results suggest that the proposed approach not only retains the advantages of the original imaging method but also contributes significantly to the enhancement of its measuring range (+/- 4.13 degrees with accuracy of the order of 1 arcsec).

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Template matching is concerned with measuring the similarity between patterns of two objects. This paper proposes a memory-based reasoning approach for pattern recognition of binary images with a large template set. It seems that memory-based reasoning intrinsically requires a large database. Moreover, some binary image recognition problems inherently need large template sets, such as the recognition of Chinese characters which needs thousands of templates. The proposed algorithm is based on the Connection Machine, which is the most massively parallel machine to date, using a multiresolution method to search for the matching template. The approach uses the pyramid data structure for the multiresolution representation of templates and the input image pattern. For a given binary image it scans the template pyramid searching the match. A binary image of N × N pixels can be matched in O(log N) time complexity by our algorithm and is independent of the number of templates. Implementation of the proposed scheme is described in detail.

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Joint decoding of multiple speech patterns so as to improve speech recognition performance is important, especially in the presence of noise. In this paper, we propose a Multi-Pattern Viterbi algorithm (MPVA) to jointly decode and recognize multiple speech patterns for automatic speech recognition (ASR). The MPVA is a generalization of the Viterbi Algorithm to jointly decode multiple patterns given a Hidden Markov Model (HMM). Unlike the previously proposed two stage Constrained Multi-Pattern Viterbi Algorithm (CMPVA),the MPVA is a single stage algorithm. MPVA has the advantage that it cart be extended to connected word recognition (CWR) and continuous speech recognition (CSR) problems. MPVA is shown to provide better speech recognition performance than the earlier techniques: using only two repetitions of noisy speech patterns (-5 dB SNR, 10% burst noise), the word error rate using MPVA decreased by 28.5%, when compared to using individual decoding. (C) 2010 Elsevier B.V. All rights reserved.