236 resultados para SURF feature extraction


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Many protocols have been used for extraction of DNA from Thraustochytrids. These generally involve the use of CTAB, phenol/chloroform and ethanol. They also feature mechanical grinding, sonication, N2 freezing or bead beating. However, the resulting chemical and physical damage to extracted DNA reduces its quality. The methods are also unsuitable for large numbers of samples. Commercially-available DNA extraction kits give better quality and yields but are expensive. Therefore, an optimized DNA extraction protocol was developed which is suitable for Thraustochytrids to both minimise expensive and time-consuming steps prior to DNA extraction and also to improve the yield. The most effective method is a combination of single bead in TissueLyser (Qiagen) and Proteinase K. Results were conclusive: both the quality and the yield of extracted DNA were higher than with any other method giving an average yield of 8.5 µg/100 mg biomass.

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A method for determination of tricyclazole in water using solid phase extraction and high performance liquid chromatography (HPLC) with UV detection at 230nm and a mobile phase of acetonitrile:water (20:80, v/v) was developed. A performance comparison between two types of solid phase sorbents, the C18 sorbent of Supelclean ENVI-18 cartridge and the styrene-divinyl benzene copolymer sorbent of Sep-Pak PS2-Plus cartridge was conducted. The Sep-Pak PS2-Plus cartridges were found more suitable for extracting tricyclazole from water samples than the Supelclean ENVI-18 cartridges. For this cartridge, both methanol and ethyl acetate produced good results. The method was validated with good linearity and with a limit of detection of 0.008gL-1 for a 500-fold concentration through the SPE procedure. The recoveries of the method were stable at 80% and the precision was from 1.1-6.0% within the range of fortified concentrations. The validated method was also applied to measure the concentrations of tricyclazole in real paddy water.

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This study investigates the use of unsupervised features derived from word embedding approaches and novel sequence representation approaches for improving clinical information extraction systems. Our results corroborate previous findings that indicate that the use of word embeddings significantly improve the effectiveness of concept extraction models; however, we further determine the influence that the corpora used to generate such features have. We also demonstrate the promise of sequence-based unsupervised features for further improving concept extraction.

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How two powerhouse brands, Billabong and Lorna Jane, took the quintessential Queensland lifestyle to the world stage.

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Feature films remain critical flagships to any national film industry. Australian feature films can be highly commercial endeavours that also perform symbolic functions by embodying the national imaginary in big screen based sound and imagery. They conduct a dialogue with domestic audiences as well as showcase key aspects of Australia in the global film festival circuit. As the pre-eminent filmmaking form, feature films also serve as important launchpads for the careers of many Australian writers, directors, actors and technical crew. In the wake of over a decade of diminished share of local box office obtained by Australian feature films, Australian Feature Films and Distribution: Industry or cottage industry, examines issues in the production sector affecting the performance of Australian feature films and some responses by the central funding and support screen agency, Screen Australia.

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Training for bodybuilding competition is clearly a serious business that inflicts serious demands on the competitor. Not only did Francis commit time and money to compete, but he also arguably put winning before his physical well-being—enduring pain and suffering from his injury. Bodybuilding may seem like an extreme example, but it is not the only activity in which people suffer in pursuit of their goals. Boxers fight each other in the ring; soccer players risk knee and ankle injuries, sometimes playing despite being hurt; and mountaineers risk their lives in dangerous climbs. In the arts there are many examples of people suffering to achieve their goals: Beethoven kept composing, conducting, and performing despite his hearing loss; van Gogh grappled with depression but kept painting, finding fame only posthumously; and Mozart lived the final years of his life impoverished but still composing. These examples show that many great achievements come at a price: severe suffering...

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Organochlorine pesticides (OCPs) are ubiquitous environmental contaminants with adverse impacts on aquatic biota, wildlife and human health even at low concentrations. However, conventional methods for their determination in river sediments are resource intensive. This paper presents an approach that is rapid and also reliable for the detection of OCPs. Accelerated Solvent Extraction (ASE) with in-cell silica gel clean-up followed by Triple Quadrupole Gas Chromatograph Mass Spectrometry (GCMS/MS) was used to recover OCPs from sediment samples. Variables such as temperature, solvent ratio, adsorbent mass and extraction cycle were evaluated and optimised for the extraction. With the exception of Aldrin, which was unaffected by any of the variables evaluated, the recovery of OCPs from sediment samples was largely influenced by solvent ratio and adsorbent mass and, to some extent, the number of cycles and temperature. The optimised conditions for OCPs extraction in sediment with good recoveries were determined to be 4 cycles, 4.5 g of silica gel, 105 ᴼC, and 4:3 v/v DCM: hexane mixture. With the exception of two compounds (α-BHC and Aldrin) whose recoveries were low (59.73 and 47.66 % respectively), the recovery of the other pesticides were in the range 85.35 – 117.97% with precision < 10 % RSD. The method developed significantly reduces sample preparation time, the amount of solvent used, matrix interference, and is highly sensitive and selective.

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Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

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Wildlife conservation involves an understanding of a specific animal, its environment and the interaction within a local ecosystem. Unmanned Aerial Vehicles (UAVs) present cost effective, non-intrusive solution for detecting animals over large areas and the use thermal imaging cameras offer the ability detect animals that would otherwise be concealed to visible light cameras. This report examines some of limitations on using SURF for the development of large maps using multiple stills images extracted from the thermal imaging video camera which contain wildlife (eg. Koala in them).

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The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

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Assessment of heavy metal bioavailability in sediments is complex because of the number of partial extraction methods available for the assessment and the general lack of certified reference materials. This study evaluates five different extraction methodologies to ascertain the relative strengths and weaknesses of each method. The results are then compared to previously published work to ascertain the most effective partial extraction technique, which was established to be dilute (0.75 – 1 M) nitric acid solutions. These results imply that single reagent; weak acid extractions provide a better assessment of potentially bioavailable metals than the chelating agents used in sequential extraction methods.