895 resultados para EXTRACTION COLUMNS


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This paper focuses on the PSpice model of SiC-JFET element inside a SiCED cascode device. The device model parameters are extracted from the I-V and C-V characterization curves. In order to validate the model, an inductive test rig circuit is designed and tested. The switching loss is estimated both using oscilloscope and calorimeter. These results are found to be in good agreement with the simulated results.

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Triacylglycerols (TAGs) from microalgae have the potential to be used for biodiesel, but several technical and economic hurdles have to be overcome. A major challenge is efficient extraction of intracellular TAGs from algae. Here we investigate the use of enzymes to deconstruct algal cell walls/membranes. We describe a rapid and simple assay that can assess the efficacy of different enzyme treatments on TAG-containing algae. By this means crude papain and bromelain were found to be effective in releasing TAGs from the diatom Phaeodactylum tricornutum, most likely because of their cysteine protease activity. Pre-treating algal biomass with crude papain enabled complete extraction of TAGs using heptane/isopropyl alcohol. Heptane as a single solvent was also effective, although complete recovery of TAG was not obtained. Economic implications of these findings are discussed, with the aim to reduce the complexity of, and energy needed in, TAG extraction.

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There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame. This is because manually inspecting bridges is a time-consuming and costly task, and some state Departments of Transportation (DOT) cannot afford the essential costs and manpower. In this paper, a novel method that can detect large-scale bridge concrete columns is proposed for the purpose of eventually creating an automated bridge condition assessment system. The method employs image stitching techniques (feature detection and matching, image affine transformation and blending) to combine images containing different segments of one column into a single image. Following that, bridge columns are detected by locating their boundaries and classifying the material within each boundary in the stitched image. Preliminary test results of 114 concrete bridge columns stitched from 373 close-up, partial images of the columns indicate that the method can correctly detect 89.7% of these elements, and thus, the viability of the application of this research.

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After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.

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Most of the manual labor needed to create the geometric building information model (BIM) of an existing facility is spent converting raw point cloud data (PCD) to a BIM description. Automating this process would drastically reduce the modeling cost. Surface extraction from PCD is a fundamental step in this process. Compact modeling of redundant points in PCD as a set of planes leads to smaller file size and fast interactive visualization on cheap hardware. Traditional approaches for smooth surface reconstruction do not explicitly model the sparse scene structure or significantly exploit the redundancy. This paper proposes a method based on sparsity-inducing optimization to address the planar surface extraction problem. Through sparse optimization, points in PCD are segmented according to their embedded linear subspaces. Within each segmented part, plane models can be estimated. Experimental results on a typical noisy PCD demonstrate the effectiveness of the algorithm.

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Triacylglycerols (TAGs) from microalgae have the potential to be used for biodiesel, but several technical and economic hurdles have to be overcome. A major challenge is efficient extraction of intracellular TAGs from algae. Here we investigate the use of enzymes to deconstruct algal cell walls/membranes. We describe a rapid and simple assay that can assess the efficacy of different enzyme treatments on TAG-containing algae. By this means crude papain and bromelain were found to be effective in releasing TAGs from the diatom Phaeodactylum tricornutum, most likely because of their cysteine protease activity. Pre-treating algal biomass with crude papain enabled complete extraction of TAGs using heptane/isopropyl alcohol. Heptane as a single solvent was also effective, although complete recovery of TAG was not obtained. Economic implications of these findings are discussed, with the aim to reduce the complexity of, and energy needed in, TAG extraction. © 2012 Elsevier B.V.

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We present an analytical field-effect method to extract the density of subgap states (subgap DOS) in amorphous semiconductor thin-film transistors (TFTs), using a closed-form relationship between surface potential and gate voltage. By accounting the interface states in the subthreshold characteristics, the subgap DOS is retrieved, leading to a reasonably accurate description of field-effect mobility and its gate voltage dependence. The method proposed here is very useful not only in extracting device performance but also in physically based compact TFT modeling for circuit simulation. © 2012 IEEE.

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This paper presents details of the installation and performance of carbonated soil-MgO columns using a laboratory-scale model auger setup. MgO grout was mixed with the soil using the auger and the columns were then carbonated with gaseous CO2 introduced in two different ways: one using auger mixing and the other through a perforated plastic tube system inserted into the treated column. The performance of the columns in terms of unconfined compressive strength (UCS), stiffness, strain at failure and microstructure (using X-ray diffraction and scanning electron microscopy) showed that the soil-MgO columns were carbonated very quickly (in under 1 h) and yielded relatively high strength values, of 2.4-9.4 MPa, which on average were five times that of corresponding 28-day ambient cured uncarbonated columns. This confirmed, together with observations of dense microstructure and hydrated magnesium carbonates, that a good degree of carbonation had taken place. The results also showed that the carbonation method and period have a significant effect on the resulting performance, with the carbonation through the perforated pipe producing the best results. Copyright © 2013 by ASTM International.

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This work applies a variety of multilinear function factorisation techniques to extract appropriate features or attributes from high dimensional multivariate time series for classification. Recently, a great deal of work has centred around designing time series classifiers using more and more complex feature extraction and machine learning schemes. This paper argues that complex learners and domain specific feature extraction schemes of this type are not necessarily needed for time series classification, as excellent classification results can be obtained by simply applying a number of existing matrix factorisation or linear projection techniques, which are simple and computationally inexpensive. We highlight this using a geometric separability measure and classification accuracies obtained though experiments on four different high dimensional multivariate time series datasets. © 2013 IEEE.

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A new amino silica monolithic column was developed for DNA extraction in a miniaturized format. The monolithic column was prepared in situ by polymerization of tetraethoxysilane (TEOS) and N-(beta-aminoethyl)-gamma-aminopropylmethyldimethoxysilane (AEAPMDMS). DNA was loaded in 50 mM tris(hydroxylmethyl)aminomethane-EDTA buffer at pH 7.0 and eluted with 300 mM potassium phosphate solution at pH 10.0. Under optimal condition, a 6.0-cm monolithic column provided a capacity of 56 ng DNA with an extraction efficiency of 71 +/- 5.2% (X +/- RSD). When the amino silica monolithic column was applied to extract genomic DNA from the whole blood of crucian carp, an extraction efficiency of 52 +/- 5.6% (X +/- SD) was obtained by three extractions. Since the chaotropic-based sample loading and organic solvent wash steps were avoided in this procedure, the purified DNA was suitable for downstream processes such as PCR. This amino silica monolithic column was demonstrated to allow rapid and efficient DNA purification in microscale.