991 resultados para Wave-front coding


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The work described in this technical report is part of an ongoing project to build practical tools for the manipulation, analysis and visualisation of recordings of the natural environment. This report describes the methods we use to remove background noise from spectrograms. It updates techniques previously described in Towsey and Planitz (2011), Technical report: acoustic analysis of the natural environment, downloadable from: http://eprints.qut.edu.au/41131/. It also describes noise removal from wave-forms, a technique not described in the above 2011 technical report.

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While user-generated short online videos have existed since the emergence of video sharing sites in China, they have undergone a process of formalisation and commercialisation, culminating in the wave of micro-movies in recent years. By addressing the wider context of globalisation alongside relevant state policies and shifting viewing habits, this article analyses the local and global causes of this wave. It offers evidence that illustrates how online video service providers in China have adapted in a changing industry landscape as they negotiate state policies, advertiser interests and user preference. It then examines the production and distribution dynamics, where professional producers draw on social media, grassroots creativity and creative talents in regional markets. Finally, it discusses the cultural implications of this process in terms of both the nature and flow of creativity. Based on these analyses, the article also sheds light on the interplay between the state and the market in the context of globalisation and marketisation of media sectors, which becomes more complicated when the state-owned or controlled media enter the emerging market sectors.

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The performance of visual speech recognition (VSR) systems are significantly influenced by the accuracy of the visual front-end. The current state-of-the-art VSR systems use off-the-shelf face detectors such as Viola- Jones (VJ) which has limited reliability for changes in illumination and head poses. For a VSR system to perform well under these conditions, an accurate visual front end is required. This is an important problem to be solved in many practical implementations of audio visual speech recognition systems, for example in automotive environments for an efficient human-vehicle computer interface. In this paper, we re-examine the current state-of-the-art VSR by comparing off-the-shelf face detectors with the recently developed Fourier Lucas-Kanade (FLK) image alignment technique. A variety of image alignment and visual speech recognition experiments are performed on a clean dataset as well as with a challenging automotive audio-visual speech dataset. Our results indicate that the FLK image alignment technique can significantly outperform off-the shelf face detectors, but requires frequent fine-tuning.

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The International Classification of Diseases, Version 10, Australian modification (ICD-10- AM) is commonly used to classify diseases in hospital patients. ICD-10-AM defines malnutrition as “BMI < 18.5 kg/m2 or unintentional weight loss of ≥ 5% with evidence of suboptimal intake resulting in subcutaneous fat loss and/or muscle wasting”. The Australasian Nutrition Care Day Survey (ANCDS) is the most comprehensive survey to evaluate malnutrition prevalence in acute care patients from Australian and New Zealand hospitals1. This study determined if malnourished participants were assigned malnutritionrelated codes as per ICD-10-AM. The ANCDS recruited acute care patients from 56 hospitals. Hospital-based dietitians evaluated participants’ nutritional status using BMI and Subjective Global Assessment (SGA). In keeping with the ICD-10-AM definition, malnutrition was defined as BMI <18.5kg/m2, SGA-B (moderately malnourished) or SGA-C (severely malnourished). After three months, in this prospective cohort study, hospitals’ health information/medical records department provided coding results for malnourished participants. Although malnutrition was prevalent in 32% (n= 993) of the cohort (N= 3122), a significantly small number were coded for malnutrition (n= 162, 16%, p<0.001). In 21 hospitals, none of the malnourished participants were coded. This is the largest study to provide a snapshot of malnutrition-coding in Australian and New Zealand hospitals. Findings highlight gaps in malnutrition documentation and/or subsequent coding, which could potentially result in significant loss of casemix-related revenue for hospitals. Dietitians must lead the way in developing structured processes for malnutrition identification, documentation and coding.

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The first version of the Standard PREanalytical Code (SPREC) was developed in 2009 by the International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group to facilitate documentation and communication of the most important preanalytical quality parameters of different types of biospecimens used for research. This same Working Group has now updated the SPREC to version 2.0, presented here, so that it contains more options to allow for recent technological developments. Existing elements have been fine tuned. An interface to the Biospecimen Reporting for Improved Study Quality (BRISQ) has been defined, and informatics solutions for SPREC implementation have been developed. A glossary with SPRECrelated definitions has also been added.

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Background. In isotropic materials, the speed of acoustic wave propagation is governed by the bulk modulus and density. For tendon, which is a structural composite of fluid and collagen, however, there is some anisotropy requiring an adjustment for Poisson's ratio. This paper explores these relationships using data collected, in vivo, on human Achilles tendon and then compares estimates of elastic modulus and hysteresis against published values from in vitro mechanical tests. Methods. Measurements using conventional B-model ultrasound imaging, inverse dynamics and acoustic transmission techniques were used to determine dimensions, loading conditions and longitudinal speed of sound in the Achilles tendon during a series of isometric plantar flexion exercises against body weight. Upper and lower bounds for speed of sound versus tensile stress in the tendon were then modelled and estimates of the elastic modulus and hysteresis of the Achilles tendon derived. Results. Axial speed of sound varied between 1850 and 2090 ms-1 with a non-linear, asymptotic dependency on the level of tensile stress (5-35 MPa) in the tendon. Estimates derived for the elastic modulus of the Achilles tendon ranged between 1-2 GPa. Hysteresis derived from models of the stress-strain relationship, ranged from 3-11%. Discussion. Estimates of elastic modulus agree closely with those previously reported from direct measurements obtained via mechanical tensile tests on major weight bearing tendons in vitro [1,2]. Hysteresis derived from models of the stress-strain relationship is consistent with direct measures from various mamalian tendon (7-10%) but is lower than previous estimates in human tendon (17-26%) [3]. This non-invasive method would appear suitable for monitoring changes in tendon properties during dynamic sporting activities.

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In a large interconnected power system, disturbances initiated by a fault or other events cause acceleration in the generator rotors with respect to their synchronous reference frame. This acceleration of rotors can be described by two different dynamic phenomena, as shown in existing literature. One of the phenomena is simultaneous acceleration and the other is electromechanical wave propagation, which is characterized by travelling waves in terms of a wave equation. This paper demonstrates that depending on the structure of the system, the exhibited dynamic response will be dominated by one phenomenon or the other or a mixture of both. Two system structures of choice are examined, with each structure exemplifying each phenomenon present to different degrees in their dynamic responses. Prediction of dominance of either dynamic phenomenon in a particular system can be determined by taking into account the relative sizes of the values of its reduced admittance matrix.

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Subterranean clover stunt disease is an economically important aphid-borne virus disease affecting certain pasture and grain legumes in Australia. The virus associated with the disease, subterranean clover stunt virus (SCSV), was previously found to be representative of a new type of single-stranded DNA virus. Analysis of the virion DNA and restriction mapping of double-stranded cDNA synthesized from virion DNA suggested that SCSV has a segmented genome composed of 3 or 4 different species of circular ssDNA each of about 850-880 nucleotides. To further investigate the complexity of the SCSV genome, we have isolated the replicative form DNA from infected pea and from it prepared putative full-length clones representing the SCSV genome segments. Analysis of these clones by restriction mapping indicated that clones representing at least 4 distinct genomic segments were obtained. This method is thus suitable for generating an extensive genomic library of novel ssDNA viruses containing multiple genome segments such as SCSV and banana bunchy top virus. The N-terminal amino acid sequence and amino acid composition of the coat protein of SCSV were determined. Comparison of the amino acid sequence with partial DNA sequence data, and the distinctly different restriction maps obtained for the full-length clones suggested that only one of these clones contained the coat protein gene. The results confirmed that SCSV has a functionally divided genome composed of several distinct ssDNA circles each of about 1 kb.

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Recent welfare reform in Australia has been constructed around the now-familiar principle of paid work and willingness to work as the fundamental marker of social citizenship. Beginning with the long-term unemployed in Australia in the mid 1990s, the scope of welfare reform has now extended to include people with a disability – which is a category of income support that has been growing in Australia. From the national government’s point of view this growth is a financial concern as it seeks to move as many people as possible into paid work to support the costs of an ageing population (DEWR, 2005). In doing so, the government has changed the meaning of disability in terms of eligibility for financial support from the state, and at the same time redefined the role of people with a disability with regard to work, and the role of the state with regard to the disabled. This has been a matter of some political contention in Australia.

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An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

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Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

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The existence of travelling wave solutions to a haptotaxis dominated model is analysed. A version of this model has been derived in Perumpanani et al. (1999) to describe tumour invasion, where diffusion is neglected as it is assumed to play only a small role in the cell migration. By instead allowing diffusion to be small, we reformulate the model as a singular perturbation problem, which can then be analysed using geometric singular perturbation theory. We prove the existence of three types of physically realistic travelling wave solutions in the case of small diffusion. These solutions reduce to the no diffusion solutions in the singular limit as diffusion as is taken to zero. A fourth travelling wave solution is also shown to exist, but that is physically unrealistic as it has a component with negative cell population. The numerical stability, in particular the wavespeed of the travelling wave solutions is also discussed.

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We study a version of the Keller–Segel model for bacterial chemotaxis, for which exact travelling wave solutions are explicitly known in the zero attractant diffusion limit. Using geometric singular perturbation theory, we construct travelling wave solutions in the small diffusion case that converge to these exact solutions in the singular limit.

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Malignant Pleural Mesothelioma (MPM) is an aggressive cancer that is often diagnosed at an advanced stage and is characterized by a long latency period (20-40 years between initial exposure and diagnosis) and prior exposure to asbestos. Currently accurate diagnosis of MPM is difficult due to the lack of sensitive biomarkers and despite minor improvements in treatment, median survival rates do not exceed 12 months. Accumulating evidence suggests that aberrant expression of long non-coding RNAs (lncRNAs) play an important functional role in cancer biology. LncRNAs are a class of recently discovered non-protein coding RNAs >200 nucleotides in length with a role in regulating transcription. Here we used NCode long noncoding microarrays to identify differentially expressed lncRNAs potentially involved in MPM pathogenesis. High priority candidate lncRNAs were selected on the basis of statistical (P<0.05) and biological significance (>3-fold difference). Expression levels of 9 candidate lncRNAs were technically validated using RT-qPCR, and biologically validated in three independent test sets: (1) 57 archived MPM tissues obtained from extrapleural pneumonectomy patients, (2) 15 cryopreserved MPM and 3 benign pleura, and (3) an extended panel of 10 MPM cell lines. RT-qPCR analysis demonstrated consistent up-regulation of these lncRNAs in independent datasets. ROC curve analysis showed that two candidates were able to separate benign pleura and MPM with high sensitivity and specificity, and were associated with nodal metastases and survival following induction chemotherapy. These results suggest that lncRNAs have potential to serve as biomarkers in MPM.

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The molecular mechanisms involved in non‑small cell lung cancer tumourigenesis are largely unknown; however, recent studies have suggested that long non-coding RNAs (lncRNAs) are likely to play a role. In this study, we used public databases to identify an mRNA-like, candidate long non-coding RNA, GHSROS (GHSR opposite strand), transcribed from the antisense strand of the ghrelin receptor gene, growth hormone secretagogue receptor (GHSR). Quantitative real-time RT-PCR revealed higher expression of GHSROS in lung cancer tissue compared to adjacent, non-tumour lung tissue. In common with many long non-coding RNAs, GHSROS is 5' capped and 3' polyadenylated (mRNA-like), lacks an extensive open reading frame and harbours a transposable element. Engineered overexpression of GHSROS stimulated cell migration in the A549 and NCI-H1299 non-small cell lung cancer cell lines, but suppressed cell migration in the Beas-2B normal lung-derived bronchoepithelial cell line. This suggests that GHSROS function may be dependent on the oncogenic context. The identification of GHSROS, which is expressed in lung cancer and stimulates cell migration in lung cancer cell lines, contributes to the growing number of non-coding RNAs that play a role in the regulation of tumourigenesis and metastatic cancer progression.