994 resultados para Opportunity Recognition


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Neuroimaging research has shown localised brain activation to different facial expressions. This, along with the finding that schizophrenia patients perform poorly in their recognition of negative emotions, has raised the suggestion that patients display an emotion specific impairment. We propose that this asymmetry in performance reflects task difficulty gradations, rather than aberrant processing in neural pathways subserving recognition of specific emotions. A neural network model is presented, which classifies facial expressions on the basis of measurements derived from human faces. After training, the network showed an accuracy pattern closely resembling that of healthy subjects. Lesioning of the network led to an overall decrease in the network’s discriminant capacity, with the greatest accuracy decrease to fear, disgust and anger stimuli. This implies that the differential pattern of impairment in schizophrenia patients can be explained without having to postulate impairment of specific processing modules for negative emotion recognition.

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A novel shape recognition algorithm was developed to autonomously classify the Northern Pacific Sea Star (Asterias amurenis) from benthic images that were collected by the Starbug AUV during 6km of transects in the Derwent estuary. Despite the effects of scattering, attenuation, soft focus and motion blur within the underwater images, an optimal joint classification rate of 77.5% and misclassification rate of 13.5% was achieved. The performance of algorithm was largely attributed to its ability to recognise locally deformed sea star shapes that were created during the segmentation of the distorted images.

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New digital media surrounds us. Little is known, however, about the influence of technology devices such as tablets (e.g. iPads) and smart phones on young children’s lives in home and school settings, and what it means for them throughout their schooling and beyond. Most research to date has focused on children aged six years and older, and much less (with a few exceptions) on preschool-aged children. This article draws on parent interviews to show how family members engage with technology as part of the flow of everyday life. Only time and increased understandings of everyday practices will tell the real values and scope of using digital media.

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The multiple forms of violence associated with protracted conflict disproportionately affect young people. Literature on conflict-affected children often focuses on the need to provide stability and security through institutions such as schools but rarely considers how young people themselves see these sites as part of their everyday lives. The enduring, pervasive, and complex nature of Colombia’s conflict means many young Colombians face the challenges of poverty, persistent social exclusion, and violence. Such conditions are exacerbated in ‘informal’ barrio communities such as los Altos de Cazucá, just south of the capital Bogotá. Drawing on field research in this community, particularly through interviews conducted with young people aged 10 to 17 this article explores how young people themselves understand the roles of the local school and ngo in their personal conceptualisations of the violence in their everyday lives. The evidence indicates that children use spaces available to them opportunistically and that these actions can and should be read as contributing to local, everyday forms of peacebuilding. The ways in which institutional spaces are understood and used by young people as ‘sites of opportunity’ challenges the assumed illegitimacy of young people’s voices and experiences in these environments.

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This paper presents an approach to mobile robot localization, place recognition and loop closure using a monostatic ultra-wide band (UWB) radar system. The UWB radar is a time-of-flight based range measurement sensor that transmits short pulses and receives reflected waves from objects in the environment. The main idea of the poposed localization method is to treat the received waveform as a signature of place. The resulting echo waveform is very complex and highly depends on the position of the sensor with respect to surrounding objects. On the other hand, the sensor receives similar waveforms from the same positions.Moreover, the directional characteristics of dipole antenna is almost omnidirectional. Therefore, we can localize the sensor position to find similar waveform from waveform database. This paper proposes a place recognitionmethod based on waveform matching, presents a number of experiments that illustrate the high positon estimation accuracy of our UWB radar-based localization system, and shows the resulting loop detection performance in a typical indoor office environment and a forest.

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In this paper we propose a novel approach to multi-action recognition that performs joint segmentation and classification. This approach models each action using a Gaussian mixture using robust low-dimensional action features. Segmentation is achieved by performing classification on overlapping temporal windows, which are then merged to produce the final result. This approach is considerably less complicated than previous methods which use dynamic programming or computationally expensive hidden Markov models (HMMs). Initial experiments on a stitched version of the KTH dataset show that the proposed approach achieves an accuracy of 78.3%, outperforming a recent HMM-based approach which obtained 71.2%.

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Assessments of students in primary and secondary education are debated among practitioners, policy-makers, and parents. In some countries, assessment scores serve a criterion for passage between levels of education, for example, from secondary school to post-secondary education. Those practices are often traditions and while they come under criticism, they are a long-accepted part of the educational practices within a country. In those countries, the students’ assessment and examination scores are posted in public places or published in local news media. In other countries, assessments are used for the periodic checks on individual student progress. The results of assessments may be used for rating schools, and in some cases, they are used for evaluating the performance of teachers. Assessments are used less often to analyze student performance and make judgments regarding the performance of the curriculum. Even less often, assessments serve to critically establish strategies for the improvement of student learning and educational practices. The ends on the continuum of the assessment debate often focus on the opportunities that assessments present to improve education on one end. The other end is that assessments serve as a major distraction from the important work of teachers by removing classroom room time from instruction. The debate on those issues continues.

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This proposal describes the innovative and competitive lunar payload solution developed at the Queensland University of Technology (QUT)–the LunaRoo: a hopping robot designed to exploit the Moon's lower gravity to leap up to 20m above the surface. It is compact enough to fit within a 10cm cube, whilst providing unique observation and mission capabilities by creating imagery during the hop. This first section is deliberately kept short and concise for web submission; additional information can be found in the second chapter.

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Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.

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The comments I make are based on my nearly twenty years involvement in the dementia cause at both a national and international level. In preparation, I read two papers namely the Ministerial Dementia Forum – Option Paper produced by KPMG Management Consultants (2014) and Analysis of Dementia Programmes and Services Funded by the Department of Social Services: Conversation Starter prepared by KPMG as a preparation document for those attending a workshop in Brisbane on April 22nd 2015. Dementia is a complex “syndrome” and as is often said, “when you meet one person with dementia, you have met one” meaning that no two persons with dementia are the same. Even in dementia care, Australia is a “lucky country” and there is much to be said for the quality and diversity of dementia care available for people living with dementia. Despite this, I agree with the many views expressed in the material I read that there is scope for improvement, especially in the way that services are coordinated. In saying that, I do not purport to have all the solutions nor claim to have the knowledge required to comment on all the programs covered by this review. If I appear to be a “biased” advocate for Alzheimer’s Australia across the States and Territories, it is because I have seen constant evidence of ordinary people doing extraordinary things with inadequate resources. Dementia care is not cheap and if those funding dementia services are primarily only interested in economic outcomes and benefits, the real purpose of this consultation will be defeated. In addition, nowhere in the material I have read is there any recognition that in many instances program funding is a complex mix of government (at all levels) and private funding. This makes reviewing those programs more complex and less able to be coordinated at a Departmental level. It goes without saying therefore that the Federal Government is not” the only player in this game”. Of all those participating in this review, Alzheimer’s Australia is best placed to comment on programs as it is more connected to people living with dementia and has probably the best record of consulting with them. It would appear however that their role has been reduced to that of a “bit player”. Without wanting to be critical, the Forum Report which deals with the comments made at a gathering of 70 individuals and organisations, only three (3) or 4.28% were actual carers of people living with dementia. Even if it is argued that a number of organisations present represented consumers, the percentage goes up only marginally to 8.57% which is hardly an endorsement of the forum being “consumer driven”. The predominance of those present were service providers, each with their own agenda and each seeking advantage for their “business”. The final point I want to make before commenting on more specific, program related issues, is that many programs being reviewed have a much longer history than is reflected in the material I have read. Their growth and development was pioneered by Alzheimer’s Australia organisations across the country often with no government funding. Attempts to bring about better coordination of programs were often at the behest of Alzheimer’s Australia but in the main were ignored. The opportunity to now put this right is long overdue.

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The benefits for university graduates in growing skills and capabilities through volunteering experiences are gaining increased attention. Building leadership self-efficacy supports students develop their capacity for understanding, articulating and evidencing their learning. Reward and recognition is fundamental in the student’s journey to build self-efficacy. Through this research, concepts of reward and recognition have been explored and articulated through the experiences and perceptions of actively engaged student peer leaders. The research methodology has enabled a collaborative, student-centred approach in shaping an innovative Rewards Framework, which supports, recognises and rewards the learning journey from beginning peer leader to competent and confident graduate.

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Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.