858 resultados para Reconhecimento de Faces
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Dhaka, Bangladesh faces chronic traffic congestion Funding for major infrastructure proves challenging This research is investigating feasibility of adopting: -Road Pricing -with significant Bus Rapid Transit (BRT) project
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The increasing popularity of video consumption from mobile devices requires an effective video coding strategy. To overcome diverse communication networks, video services often need to maintain sustainable quality when the available bandwidth is limited. One of the strategy for a visually-optimised video adaptation is by implementing a region-of-interest (ROI) based scalability, whereby important regions can be encoded at a higher quality while maintaining sufficient quality for the rest of the frame. The result is an improved perceived quality at the same bit rate as normal encoding, which is particularly obvious at the range of lower bit rate. However, because of the difficulties of predicting region-of-interest (ROI) accurately, there is a limited research and development of ROI-based video coding for general videos. In this paper, the phase spectrum quaternion of Fourier Transform (PQFT) method is adopted to determine the ROI. To improve the results of ROI detection, the saliency map from the PQFT is augmented with maps created from high level knowledge of factors that are known to attract human attention. Hence, maps that locate faces and emphasise the centre of the screen are used in combination with the saliency map to determine the ROI. The contribution of this paper lies on the automatic ROI detection technique for coding a low bit rate videos which include the ROI prioritisation technique to give different level of encoding qualities for multiple ROIs, and the evaluation of the proposed automatic ROI detection that is shown to have a close performance to human ROI, based on the eye fixation data.
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Process modelling – the design and use of graphical documentations of an organisation’s business processes – is a key method to document and use information about business processes in organisational projects. Still, despite current interest in process modelling, this area of study still faces essential challenges. One of the key unanswered questions concerns the impact of process modelling in organisational practice. Process modelling initiatives call for tangible results in the form of returns on the substantial investments that organisations undertake to achieve improved processes. This study explores the impact of process model use on end-users and its contribution to organisational success. We posit that the use of conceptual models creates impact in organisational process teams. We also report on a set of case studies in which we explore tentative evidence for the development of impact of process model use. The results of this work provide a better understanding of process modelling impact from information practices and also lead to insights into how organisations should conduct process modelling initiatives in order to achieve an optimum return on their investment.
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A well-characterized kaolinite has been hydrated in order to test the hypothesis that platey kaolinite will roll upon hydration. Kaolinite hydrates are prepared by repeated intercalation of kaolinite with potassium acetate and subsequent washing with water. On hydration, kaolinite plates roll along the major crystallographic directions to form tubes identical to proper tubular halloysite. Most tubes are elongated along the b crystallographic axis, while some are elongated along the a axis. Overall, the tubes exhibit a range of crystallinity. Well-ordered examples show a 2-layer structure, while poorly ordered tubes show little or no 3-dimensional order. Cross-sectional views of the formed tubes show both smoothly curved layers and planar faces. These characteristics of the experimentally formed tubes are shared by natural halloysites. Therefore, it is proposed that planar kaolinite can transform to tubular halloysite.
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Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology (IT) infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry’s technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry’s services to be offered through cloud-based “apps.”
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The preparedness theory of classical conditioning proposed by Seligman (1970, 1971) has been applied extensively over the past 40 years to explain the nature and "source" of human fear and phobias. In this review we examine the formative studies that tested the four defining characteristics of prepared learning with animal fear-relevant stimuli (typically snakes and spiders) and consider claims that fear of social stimuli, such as angry faces, or faces of racial out-group members, may also be acquired utilising the same preferential learning mechanism. Exposition of critical differences between fear learning to animal and social stimuli suggests that a single account cannot adequately explain fear learning with animal and social stimuli. We demonstrate that fear conditioned to social stimuli is less robust than fear conditioned to animal stimuli as it is susceptible to cognitive influence and propose that it may instead reflect on negative stereotypes and social norms. Thus, a theoretical model that can accommodate the influence of both biological and cultural factors is likely to have broader utility in the explanation of fear and avoidance responses than accounts based on a single mechanism.
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Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry's technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry's services to be offered through cloud-based “apps.”
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The LiteSteel Beam (LSB) is a new hollow flange section developed in Australia with a unique geometry consisting of torsionally rigid rectangular hollow flanges and a relatively slender web. The LSB is subjected to a relatively new Lateral Distortional Buckling (LDB) mode when used as flexural members. Unlike the commonly observed lateral torsional buckling, lateral distortional buckling of LSBs is characterised by cross sectional change due to web distortion. Lateral distortional buckling causes significant moment capacity reduction for LSBs with intermediate spans. Therefore a detailed investigation was undertaken to determine the methods of reducing the effects of lateral distortional buckling in LSB flexural members. For this purpose the use of web stiffeners was investigated using finite element analyses of LSBs with different web stiffener spacing and sizes. It was found that the use of 5 mm steel plate stiffeners welded or screwed to the inner faces of the top and bottom flanges at third span points considerably reduced the lateral distortional buckling effects in LSBs. Suitable design rules were then developed to calculate the enhanced elastic lateral distortional buckling moments and the higher ultimate moment capacities of LSBs with the chosen web stiffener arrangement. This paper presents the details of this investigation and the results.
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In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.
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Cyclone Yasi struck the Cassowary Coast of Queensland in the early hours of Feb 3, 2011, destroying many homes sand property, including the destruction of the Cardwell and district historical society’s premises. With their own homes flattened, many were forced to live in mobile accommodation, with extended family, or leave altogether. The historical society members however were more devastated by their flattened foreshore museum and loss of their collection material. A call for assistance was made through the OHAA Qld branch, who along with QUT sponsored a trip to somehow plan how they could start to pick up the pieces to start again. This presentation highlights the need for communities to gather, preserve and present their own stories, in a way that is sustainable and meaningful to them, but that good advice and support along the way is important. Two 2 day workshops were held in March and then September, augmented by plenty of email correspondence and phone calls in between. Participants learnt that if they could conduct quality oral history interviews, they could later use these in many exhibitable ways including: documentary pieces; digital stories; photographic collections; creative short stories; audio segments –while also drawing closely together a suffering community. This story is not only about the people who were interviewed about the night Yasi struck, but the amazing women (all over 50) of the historical society who were willing to try and leap the digital divide that faces older Australians, especially those in rural Australia, so that their older local stories would not be lost and so that new stories could also be remembered.
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Palygorskite has a fibrous like morphology with a distinctive layered appearance. The simplified formula of palygorskite (Mg5Si8O20(OH)2(OH2)4 nH2O) indicates that two different types of water are present. The dehydration and rehydration of palygorskite have been studied using thermogravimetry and H2O-tem- perature programmed desorption. X-ray diffractograms, NH3 adsorption profiles, and NH3 desorption profiles were obtained for thermally treated palygorskite as a function of temperature. The results proved water molecules were mainly derived from Si–OH units. In addition, five kinds of acid sites were found for palygorskite. The number of acid sites of external surfaces was larger than that of the internal sur- faces. Bonding on the internal surface acid sites was stronger than the bonding of the external surfaces. Rehydration restored the folded structure of palygorskite when thermal treatment temperature was lower than 300 oC.
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Trajectory basis Non-Rigid Structure From Motion (NRSFM) currently faces two problems: the limit of reconstructability and the need to tune the basis size for different sequences. This paper provides a novel theoretical bound on 3D reconstruction error, arguing that the existing definition of reconstructability is fundamentally flawed in that it fails to consider system condition. This insight motivates a novel strategy whereby the trajectory's response to a set of high-pass filters is minimised. The new approach eliminates the need to tune the basis size and is more efficient for long sequences. Additionally, the truncated DCT basis is shown to have a dual interpretation as a high-pass filter. The success of trajectory filter reconstruction is demonstrated quantitatively on synthetic projections of real motion capture sequences and qualitatively on real image sequences.
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To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.
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Transport processes within heterogeneous media may exhibit non-classical diffusion or dispersion; that is, not adequately described by the classical theory of Brownian motion and Fick's law. We consider a space fractional advection-dispersion equation based on a fractional Fick's law. The equation involves the Riemann-Liouville fractional derivative which arises from assuming that particles may make large jumps. Finite difference methods for solving this equation have been proposed by Meerschaert and Tadjeran. In the variable coefficient case, the product rule is first applied, and then the Riemann-Liouville fractional derivatives are discretised using standard and shifted Grunwald formulas, depending on the fractional order. In this work, we consider a finite volume method that deals directly with the equation in conservative form. Fractionally-shifted Grunwald formulas are used to discretise the fractional derivatives at control volume faces. We compare the two methods for several case studies from the literature, highlighting the convenience of the finite volume approach.
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Information literacy is increasingly recognised as an important educational outcomes for university students. How it is experienced, however, has only recently become the subject of scrutiny. THe study reported here examines varying conception of information literacy amongst a group of lecturers, librarians, staff developers and learning counsellors. A phenomenographic approach was used to discover their conceptions. Data were gathered from participants, both male and female, through interviews, e-mail discussions and workshops. As an outcomes of the analysis, seven categories, or 'faces' of information literacy were discovered. These categories depict information literacy as it is conceived or experienced. They provide target conceptions for the educational process which differ from the more conventional competencies or skill-based objectives.