827 resultados para Multiple-scale processing
Resumo:
One of the most celebrated qualities of the Internet is its enabling of simultaneity and multiplicity. By allowing users to open as many windows into the world as they (and their computers) can withstand, the Internet is understood to have brought places and cultures together on a scale and in a manner unprecedented. Yet, while the Internet has enabled many to reconnect with cultures and places long distanced and/or lost, it has also led to the belief that these reconnections are established with little correspondent cost to existent ties of belonging. In this paper, I focus on the dilemma multiple belongings engender for the ties of national belonging and question the sanguinity of multiple belongings as practised online. In particular, I use Lefebvre's notion of lived space to unpack the problems and contradictions of what has been called 'Greater China' for the ethnic Chinese minority in nations like Malaysia, Singapore and Australia.
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This paper presents an overview of technical solutions for regional area precise GNSS positioning services such as in Queensland. The research focuses on the technical and business issues that currently constrain GPS-based local area Real Time Kinematic (RTK) precise positioning services so as to operate in future across larger regional areas, and therefore support services in agriculture, mining, utilities, surveying, construction, and others. The paper first outlines an overall technical framework that has been proposed to transition the current RTK services to future larger scale coverage. The framework enables mixed use of different reference GNSS receiver types, dual- or triple-frequency, single or multiple systems, to provide RTK correction services to users equipped with any type of GNSS receivers. Next, data processing algorithms appropriate for triple-frequency GNSS signals are reviewed and some key performance benefits of using triple carrier signals for reliable RTK positioning over long distances are demonstrated. A server-based RTK software platform is being developed to allow for user positioning computations at server nodes instead of on the user's device. An optimal deployment scheme for reference stations across a larger-scale network has been suggested, given restrictions such as inter-station distances, candidates for reference locations, and operational modes. For instance, inter-station distances between triple-frequency receivers can be extended to 150km, which doubles the distance between dual-frequency receivers in the existing RTK network designs.
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In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.
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The development and use of a virtual assessment tool for a signal processing unit is described. It allows students to take a test from anywhere using a web browser to connect to the university server that hosts the test. While student responses are of the multiple choice type, they have to work out problems to arrive at the answer to be entered. CGI programming is used to verify student identification information and record their scores as well as provide immediate feedback after the test is complete. The tool has been used at QUT for the past 3 years and student feedback is discussed. The virtual assessment tool is an efficient alternative to marking written assignment reports that can often take more hours than actual lecture hall contact from a lecturer or tutor. It is especially attractive for very large classes that are now the norm at many universities in the first two years.
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This study explored youth caregiving for a parent with multiple sclerosis (MS) from multiple perspectives, and examined associations between caregiving and child negative (behavioural emotional difficulties, somatisation) and positive (life satisfaction, positive affect, prosocial behaviour) adjustment outcomes overtime. A total of 88 families participated; 85 parents with MS, 55 partners and 130 children completed questionnaires at Time 1. Child caregiving was assessed by the Youth Activities of Caregiving Scale (YACS). Child and parent questionnaire data were collected at Time 1 and child data were collected 12 months later (Time 2). Factor analysis of the child and parent YACS data replicated the four factors (instrumental, social-emotional, personal-intimate, domestic-household care), all of which were psychometrically sound. The YACS factors were related to parental illness and caregiving context variables that reflected increased caregiving demands. The Time 1 instrumental and social-emotional care domains were associated with poorer Time 2 adjustment, whereas personal-intimate was related to better adjustment and domestic-household care was unrelated to adjustment. Children and their parents exhibited highest agreement on personal-intimate, instrumental and total caregiving, and least on domestic-household and social-emotional care. Findings delineate the key dimensions of young caregiving in MS and the differential links between caregiving activities and youth adjustment.
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Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different formulations of objectives and varying regularization strategies. In this paper we present a unifying optimization criterion for multiple kernel learning and show how existing formulations are subsumed as special cases. We also derive the criterion’s dual representation, which is suitable for general smooth optimization algorithms. Finally, we evaluate multiple kernel learning in this framework analytically using a Rademacher complexity bound on the generalization error and empirically in a set of experiments.
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Single particle analysis (SPA) coupled with high-resolution electron cryo-microscopy is emerging as a powerful technique for the structure determination of membrane protein complexes and soluble macromolecular assemblies. Current estimates suggest that ∼104–105 particle projections are required to attain a 3 Å resolution 3D reconstruction (symmetry dependent). Selecting this number of molecular projections differing in size, shape and symmetry is a rate-limiting step for the automation of 3D image reconstruction. Here, we present SwarmPS, a feature rich GUI based software package to manage large scale, semi-automated particle picking projects. The software provides cross-correlation and edge-detection algorithms. Algorithm-specific parameters are transparently and automatically determined through user interaction with the image, rather than by trial and error. Other features include multiple image handling (∼102), local and global particle selection options, interactive image freezing, automatic particle centering, and full manual override to correct false positives and negatives. SwarmPS is user friendly, flexible, extensible, fast, and capable of exporting boxed out projection images, or particle coordinates, compatible with downstream image processing suites.
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A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies
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This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes. A pre-trained system could therefore be used as a turn-key solution for crowd counting across a wide range of environments. The use of local features allows the proposed algorithm to calculate local occupancy statistics, and Gaussian process regression is used to scale to conditions which are unseen in the training data, also providing confidence intervals for the crowd size estimate. A new crowd counting database is introduced to the computer vision community to enable a wider evaluation over multiple scenes, and the proposed algorithm is tested on seven datasets to demonstrate scene invariance and high accuracy. To the authors' knowledge this is the first system of its kind due to its ability to scale between different scenes and viewpoints.
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Few studies have investigated iatrogenic outcomes from the viewpoint of patient experience. To address this anomaly, the broad aim of this research is to explore the lived experience of patient harm. Patient harm is defined as major harm to the patient, either psychosocial or physical in nature, resulting from any aspect of health care. Utilising the method of Consensual Qualitative Research (CQR), in-depth interviews are conducted with twenty-four volunteer research participants who self-report having been severely harmed by an invasive medical procedure. A standardised measure of emotional distress, the Impact of Event Scale (IES), is additionally employed for purposes of triangulation. Thematic analysis of transcript data indicate numerous findings including: (i) difficulties regarding patients‘ prior understanding of risks involved with their medical procedure; (ii) the problematic response of the health system post-procedure; (iii) multiple adverse effects upon life functioning; (iv) limited recourse options for patients; and (v) the approach desired in terms of how patient harm should be systemically handled. In addition, IES results indicate a clinically significant level of distress in the sample as a whole. To discuss findings, a cross-disciplinary approach is adopted that draws upon sociology, medicine, medical anthropology, psychology, philosophy, history, ethics, law, and political theory. Furthermore, an overall explanatory framework is proposed in terms of the master themes of power and trauma. In terms of the theme of power, a postmodernist analysis explores the politics of patient harm, particularly the dynamics surrounding the politics of knowledge (e.g., notions of subjective versus objective knowledge, informed consent, and open disclosure). This analysis suggests that patient care is not the prime function of the health system, which appears more focussed upon serving the interests of those in the upper levels of its hierarchy. In terms of the master theme of trauma, current understandings of posttraumatic stress disorder (PTSD) are critiqued, and based on data from this research as well as the international literature, a new model of trauma is proposed. This model is based upon the principle of homeostasis observed in biology, whereby within every cell or organism a state of equilibrium is sought and maintained. The proposed model identifies several bio-psychosocial markers of trauma across its three main phases. These trauma markers include: (i) a profound sense of loss; (ii) a lack of perceived control; (iii) passive trauma processing responses; (iv) an identity crisis; (v) a quest to fully understand the trauma event; (vi) a need for social validation of the traumatic experience; and (vii) posttraumatic adaption with the possibility of positive change. To further explore the master themes of power and trauma, a natural group interview is carried out at a meeting of a patient support group for arachnoiditis. Observations at this meeting and members‘ stories in general support the homeostatic model of trauma, particularly the quest to find answers in the face of distressing experience, as well as the need for social recognition of that experience. In addition, the sociopolitical response to arachnoiditis highlights how public domains of knowledge are largely constructed and controlled by vested interests. Implications of the data overall are discussed in terms of a cultural revolution being needed in health care to position core values around a prime focus upon patients as human beings.