959 resultados para local processing bias


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The P0 protein of poleroviruses and P1 protein of sobemoviruses suppress the plant's RNA silencing machinery. Here we identified a silencing suppressor protein (SSP), P0PE, in the Enamovirus Pea enation mosaic virus-1 (PEMV-1) and showed that it and the P0s of poleroviruses Potato leaf roll virus and Cereal yellow dwarf virus have strong local and systemic SSP activity, while the P1 of Sobemovirus Southern bean mosaic virus supresses systemic silencing. The nuclear localized P0PE has no discernable sequence conservation with known SSPs, but proved to be a strong suppressor of local silencing and a moderate suppressor of systemic silencing. Like the P0s from poleroviruses, P0PE destabilizes AGO1 and this action is mediated by an F-box-like domain. Therefore, despite the lack of any sequence similarity, the poleroviral and enamoviral SSPs have a conserved mode of action upon the RNA silencing machinery. © 2012 Elsevier Inc.

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In this paper, we propose a novel online hidden Markov model (HMM) parameter estimator based on Kerridge inaccuracy rate (KIR) concepts. Under mild identifiability conditions, we prove that our online KIR-based estimator is strongly consistent. In simulation studies, we illustrate the convergence behaviour of our proposed online KIR-based estimator and provide a counter-example illustrating the local convergence properties of the well known recursive maximum likelihood estimator (arguably the best existing solution).

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Irradiance profile around the receiver tube (RT) of a parabolic trough collector (PTC) is a key effect of optical performance that affects the overall energy performance of the collector. Thermal performance evaluation of the RT relies on the appropriate determination of the irradiance profile. This article explains a technique in which empirical equations were developed to calculate the local irradiance as a function of angular location of the RT of a standard PTC using a vigorously verified Monte Carlo ray tracing model. A large range of test conditions including daily normal insolation, spectral selective coatings and glass envelop conditions were selected from the published data by Dudley et al. [1] for the job. The R2 values of the equations are excellent that vary in between 0.9857 and 0.9999. Therefore, these equations can be used confidently to produce realistic non-uniform boundary heat flux profile around the RT at normal incidence for conjugate heat transfer analyses of the collector. Required values in the equations are daily normal insolation, and the spectral selective properties of the collector components. Since the equations are polynomial functions, data processing software can be employed to calculate the flux profile very easily and quickly. The ultimate goal of this research is to make the concentrating solar power technology cost competitive with conventional energy technology facilitating its ongoing research.

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This paper considers the role of the public library as a community hub, engagement space, and entrepreneurial incubator in the context of the city, city governance, and local government planning. It considers this role from the perspective of library experts and their future visions for libraries in a networked knowledge economy. Public libraries (often operated by or on behalf of local governments) potentially play a pivotal role for local governments in positioning communities within the global digital network. Fourteen qualitative interviews with library experts informed the study which investigates how the relationship between digital technology and the physical library space can potentially support the community to develop innovative, collaborative environments for transitioning to a digital future. The study found that libraries can capitalise on their position as community hubs for two purposes: first, to build vibrant community networks and forge economic links across urban localities; and second, to cross the digital divide and act as places of innovation and lifelong learning. Libraries provide a specific combination of community and technology spaces and have significant tangible connection points in the digital age. The paper further discusses the potential benefits for libraries in using ICT networks and infrastructure, such as the National Broadband Network in Australia. These networks could facilitate greater use of library assets and community knowledge, which, in turn, could assist knowledge economies and regional prosperity.

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Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

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Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.

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The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

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The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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Cyclone Yasi struck the Cassowary Coast of Northern Queensland, Australia, in the early hours of February 3, 2011, destroying many homes and property, including the destruction of the Cardwell and district historical society’s premises. With their own homes flattened, many residents were forced to live in mobile accommodation, with extended family, or leave the area altogether. The historical society members seemed, however, particularly devastated by their flattened foreshore museum and loss of their precious collection of material. A call for assistance was made through the Oral History Association of Australia’s Queensland branch (OHAA Qld), which along with a Queensland University of Technology (QUT) research team sponsored a trip to best plan how they could start to pick up the pieces to rebuild the museum. This chapter highlights the need for communities to gather, preserve and present their own stories, in a way that is sustainable and meaningful to them – whether that be because of a disaster, or as they go about life in their contemporary communities – the key being that good advice, professional support and embedded evaluation practices at crucial moments along the way can be critically important.

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Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

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Due to the numerous possibilities of voicing concerns and the flood of data we are exposed to, local issues are at a risk of being overlooked. Following a research agenda proposed by Foth et al. (2013), this thesis explored the possible contributions of situated digital and tangible media for communicating local issues. Making use of the location of an issue could thereby not only allow to reach the targeted audience but also for a deeper involvement of citizens. Through the development of a design intervention in public space, called Local Commons, the benefits of this approach were investigated. Therefore, the intervention combined digital and tangible media in order to engage the public to contribute and debate different perspectives on a given local issue. The interaction with the intervention was thereby twofold. First, the intervention invited the audience to submit images of their perspectives on the issue, which were displayed on a public screen. Via tangible buttons in front of the screen, the audience then had the possibility to agree or disagree to the displayed perspectives, creating a space for deliberation. In a field study, the concept was subsequently tested and evaluated. The results of this study, although not generalisable, supported the chosen approach of this thesis.

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In this paper, teachers’ enactment of assessment policy within demands for accountability and consistency of teacher judgements is considered. Evidence is drawn from a qualitative study involving 50 middle school teachers from Queensland, Australia, who participated in online social moderation meetings with teachers located in dispersed areas around the state. The study presents how travelling policy is embedded in local histories and cultures, in particular within systems of accountability; and the different layers of what may be considered ‘local’. The paper examines the intersections of travelling and embedded policy, and global and local contexts as these are enacted through online moderation meetings.