153 resultados para Amazon metric
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This important volume on the critical pedagogical approach addresses such topics as critical multiculturalism, gender and language learning, and popular culture. Critical pedagogies are instructional approaches aimed at transforming existing social relations in the interest of greater equity in schools and communities. This paperback edition on the pedagogical approach addresses such topics as critical multiculturalism, gender and language learning, and popular culture. Committed to language education that contributes to social justice - and the political, economic, and sociocultural changes such justice requires - the contributors explore the meaning of creating equitable and critical instructional practices, by exploring diverse representations of knowledge. In addition, recommendations are made for further research, teacher education, and critical testing. Graduate students and researchers in TESOL, applied linguistics, and education will find this volume a thought-provoking and comprehensive presentation of theory and practice in this important new area of scholarship.
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Aileen Moreton-Robinson has brought together scholars from a range of disciplines: philosophy, cultural and gender studies, education, social work, sociology and literary studies. All engage critically with the location of the social and discursive construction of whiteness.
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Struggles over Difference addresses education, schools, textbooks, and pedagogies in various countries of the Asia-Pacific, offering critical curriculum studies and policy analyses of national and regional educational systems. These systems face challenges linked to new economic formations, cultural globalization, and emergent regional and international geopolitical instabilities and conflicts. Contributors offer insights on how official knowledge, text, discourse and discipline should be shaped; who should shape it; through which institutional agencies it should be administered: and social and cultural practices through which this should occur.
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"The 1990s saw the United Nations, the militaries of key member states, and NGOs increasingly entangled in the complex affairs of disrupted states. Whether as deliverers of humanitarian assistance or as agents of political, social, and civic reconstruction, whether in Somalia, Bosnia, Kosovo, or East Timor, these actors have had to learn ways of interacting with each other in order to optimize the benefits for the populations they seek to assist. Yet the challenges have proved daunting. Civil and military actors have different organizational cultures and standard operating procedures and are confronted with the need to work together to perform tasks to which different actors may attach quite different priorities."--BOOK JACKET.
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Aboriginal and Torres Strait Islander perspectives on contemporary cultural issues are presented in this collection of critical essays by indigenous Australians. From museums and anthropology to land rights and feminism, a range of topics are covered that touch on both indigenous and mainstream Australian history. Discussions of identity politics, the concept of Aboriginality, and aesthetic representations of indigenous people are rich with insight about the evolution of indigenous culture, with its shift from marginalization to cultural prominence in modern scholarship.
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This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.
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In November 2009 the researcher embarked on a project aimed at reducing the amount of paper used by Queensland University of Technology (QUT) staff in their daily workplace activities. The key goal was to communicate to staff that excessive printing has a tangible and negative effect on their workplace and local environment. The research objective was to better understand what motivates staff towards more ecologically sustainable printing practises, whilst meeting their job’s demands. The current study is built on previous research that found that one interface does not address the needs of all users when creating persuasive Human Computer Interaction (HCI) interventions targeting resource consumption. In response, the current study created and trialled software that communicates individual paper consumption in precise metrics. Based on preliminary research data different metric sets have been defined to address the different motivations and beliefs of user archetypes using descriptive and injunctive normative information.
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In wireless mobile ad hoc networks (MANETs), packet transmission is impaired by radio link fluctuations. This paper proposes a novel channel adaptive routing protocol which extends the Ad-hoc On-Demand Multipath Distance Vector routing protocol (AOMDV) to accommodate channel fading. Specifically, the proposed Channel Aware AOMDV (CA-AOMDV) uses the channel average non-fading duration as a routing metric to select stable links for path discovery, and applies a preemptive handoff strategy to maintain reliable connections by exploiting channel state information. Using the same information, paths can be reused when they become available again, rather than being discarded. We provide new theoretical results for the downtime and lifetime of a live-die-live multiple path system, as well as detailed theoretical expressions for common network performance measures, providing useful insights into the differences in performance between CA-AOMDV and AOMDV. Simulation and theoretical results show that CA-AOMDV has greatly improved network performance over AOMDV.
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A concise introduction to the key ideas and issues in the study of media economics, drawing on a broad range of case studies - from Amazon and Twitter, to Apple and Netflix - to illustrate how economic paradigms are not just theories, but provide important practical insights into how the media operates today. Understanding the economic paradigms at work in media industries and markets is vitally important for the analysis of the media system as a whole. The changing dynamics of media production, distribution and consumption are stretching the capacity of established economic paradigms. In addition to succinct accounts of neo-classical and critical political economics, the text offers fresh perspectives for understanding media drawn from two 'heterodox' approaches: institutional economics and evolutionary economics. Applying these paradigms to vital topics and case studies, Media Economics stresses the value – and limits – of contending economic approaches in understanding how the media operates today. It is essential reading for all students of Media and Communication Studies, and also those from Economics, Policy Studies, Business Studies and Marketing backgrounds who are studying the media. Table of Contents: 1. Media Economics: The Mainstream Approach 2. Critical Political Economy of the Media 3. Institutional Economics 4. Evolutionary Economics 5. Case Studies and Conclusions
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Shrinking product lifecycles, tough international competition, swiftly changing technologies, ever increasing customer quality expectation and demanding high variety options are some of the forces that drive next generation of development processes. To overcome these challenges, design cost and development time of product has to be reduced as well as quality to be improved. Design reuse is considered one of the lean strategies to win the race in this competitive environment. design reuse can reduce the product development time, product development cost as well as number of defects which will ultimately influence the product performance in cost, time and quality. However, it has been found that no or little work has been carried out for quantifying the effectiveness of design reuse in product development performance such as design cost, development time and quality. Therefore, in this study we propose a systematic design reuse based product design framework and developed a design leanness index (DLI) as a measure of effectiveness of design reuse. The DLI is a representative measure of reuse effectiveness in cost, development time and quality. Through this index, a clear relationship between reuse measure and product development performance metrics has been established. Finally, a cost based model has been developed to maximise the design leanness index for a product within the given set of constraints achieving leanness in design process.
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Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.
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Stereo vision is a method of depth perception, in which depth information is inferred from two (or more) images of a scene, taken from different perspectives. Applications of stereo vision include aerial photogrammetry, autonomous vehicle guidance, robotics, industrial automation and stereomicroscopy. A key issue in stereo vision is that of image matching, or identifying corresponding points in a stereo pair. The difference in the positions of corresponding points in image coordinates is termed the parallax or disparity. When the orientation of the two cameras is known, corresponding points may be projected back to find the location of the original object point in world coordinates. Matching techniques are typically categorised according to the nature of the matching primitives they use and the matching strategy they employ. This report provides a detailed taxonomy of image matching techniques, including area based, transform based, feature based, phase based, hybrid, relaxation based, dynamic programming and object space methods. A number of area based matching metrics as well as the rank and census transforms were implemented, in order to investigate their suitability for a real-time stereo sensor for mining automation applications. The requirements of this sensor were speed, robustness, and the ability to produce a dense depth map. The Sum of Absolute Differences matching metric was the least computationally expensive; however, this metric was the most sensitive to radiometric distortion. Metrics such as the Zero Mean Sum of Absolute Differences and Normalised Cross Correlation were the most robust to this type of distortion but introduced additional computational complexity. The rank and census transforms were found to be robust to radiometric distortion, in addition to having low computational complexity. They are therefore prime candidates for a matching algorithm for a stereo sensor for real-time mining applications. A number of issues came to light during this investigation which may merit further work. These include devising a means to evaluate and compare disparity results of different matching algorithms, and finding a method of assigning a level of confidence to a match. Another issue of interest is the possibility of statistically combining the results of different matching algorithms, in order to improve robustness.
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This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The proposed system, dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM), represents location as a probability distribution along a trajectory, and represents appearance continuously over the trajectory rather than at discrete locations. The distribution is evaluated using a Rao-Blackwellised particle filter, which weights particles based on local appearance and odometric similarity and explicitly models both the likelihood of revisiting previous locations and visiting new locations. A modified resampling scheme counters particle deprivation and allows loop closure updates to be performed in constant time regardless of map size. We compare the performance of CAT-SLAM to FAB-MAP (an appearance-only SLAM algorithm) in an outdoor environment, demonstrating a threefold increase in the number of correct loop closures detected by CAT-SLAM.
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This paper proposes the use of the Bayes Factor as a distance metric for speaker segmentation within a speaker diarization system. The proposed approach uses a pair of constant sized, sliding windows to compute the value of the Bayes Factor between the adjacent windows over the entire audio. Results obtained on the 2002 Rich Transcription Evaluation dataset show an improved segmentation performance compared to previous approaches reported in literature using the Generalized Likelihood Ratio. When applied in a speaker diarization system, this approach results in a 5.1% relative improvement in the overall Diarization Error Rate compared to the baseline.