366 resultados para proposed action
Resumo:
Government action is essential to increase the healthiness of food environments and reduce obesity, diet-related non-communicable diseases (NCDs), and their related inequalities. This paper proposes a monitoring framework to assess government policies and actions for creating healthy food environments. Recommendations from relevant authoritative organizations and expert advisory groups for reducing obesity and NCDs were examined, and pertinent components were incorporated into a comprehensive framework for monitoring government policies and actions. A Government Healthy Food Environment Policy Index (Food-EPI) was developed, which comprises a ‘policy’ component with seven domains on specific aspects of food environments, and an ‘infrastructure support’ component with seven domains to strengthen systems to prevent obesity and NCDs. These were revised through a week-long consultation process with international experts. Examples of good practice statements are proposed within each domain, and these will evolve into benchmarks established by governments at the forefront of creating and implementing food policies for good health. A rating process is proposed to assess a government's level of policy implementation towards good practice. The Food-EPI will be pre-tested and piloted in countries of varying size and income levels. The benchmarking of government policy implementation has the potential to catalyse greater action to reduce obesity and NCDs.
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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%.
Resumo:
Language processing is an example of implicit learning of multiple statistical cues that provide probabilistic information regarding word structure and use. Much of the current debate about language embodiment is devoted to how action words are represented in the brain, with motor cortex activity evoked by these words assumed to selectively reflect conceptual content and/or its simulation. We investigated whether motor cortex activity evoked by manual action words (e.g., caress) might reflect sensitivity to probabilistic orthographic-phonological cues to grammatical category embedded within individual words. We first review neuroimaging data demonstrating that nonwords evoke activity much more reliably than action words along the entire motor strip, encompassing regions proposed to be action category specific. Using fMRI, we found that disyllabic words denoting manual actions evoked increased motor cortex activity compared with non-body-part-related words (e.g., canyon), activity which overlaps that evoked by observing and executing hand movements. This result is typically interpreted in support of language embodiment. Crucially, we also found that disyllabic nonwords containing endings with probabilistic cues predictive of verb status (e.g., -eve) evoked increased activity compared with nonwords with endings predictive of noun status (e.g., -age) in the identical motor area. Thus, motor cortex responses to action words cannot be assumed to selectively reflect conceptual content and/or its simulation. Our results clearly demonstrate motor cortex activity reflects implicit processing of ortho-phonological statistical regularities that help to distinguish a word's grammatical class.
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This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.
Resumo:
This paper examines empirically the relative influence of the degree of endangerment of wildlife species and their stated likeability on individuals' allocation of funds for their conservation. To do this, it utilises data obtained from the IUCN Red List, and likeability and fund allocation data obtained from two serial surveys of a sample of the Australian public who were requested to assess 24 Australian wildlife species from three animal classes: mammals, birds and reptiles. Between the first and second survey, respondents were provided with extra information about the focal species. This information resulted in the dominance of endangerment as the major influence on the allocation of funding of respondents for the conservation of the focal wildlife species. Our results throw doubts on the proposition in the literature that the likeability of species is the dominant influence on willingness to pay for conservation of wildlife species. Furthermore, because the public's allocation of fund for conserving wildlife species seems to be more sensitive to information about the conservation status of species than to factors influencing their likeability, greater attention to providing accurate information about the former than the latter seems justified. Keywords: Conservation of wildlife species; Contingent valuation; Endangerment of species; Likeability of species; Willingness to pay
The Use of Yin's Case Study Research Approach as a Means to Stimulating Emancipatory Action Research
Resumo:
Organizations generally are not responding effectively to rising IT security threats because people issues receive inadequate attention. The stark example of IT security is just the latest strategic IT priority demonstrating deficient IT leadership attention to the social dimension of IT. Universities in particular, with their devolved people organization, diverse adoption of IT, and split central/local federated approach to governance and leadership of IT, demand higher levels of interpersonal sophistication and strategic engagement from their IT leaders. An idealized model for IT leaders for the 21st century university is proposed to be developed as a framework for further investigation. The testing of this model in an action research study is proposed.
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Developing an effective impact evaluation framework, managing and conducting rigorous impact evaluations, and developing a strong research and evaluation culture within development communication organisations presents many challenges. This is especially so when both the community and organisational context is continually changing and the outcomes of programs are complex and difficult to clearly identify.----- This paper presents a case study from a research project being conducted from 2007-2010 that aims to address these challenges and issues, entitled Assessing Communication for Social Change: A New Agenda in Impact Assessment. Building on previous development communication projects which used ethnographic action research, this project is developing, trailing and rigorously evaluating a participatory impact assessment methodology for assessing the social change impacts of community radio programs in Nepal. This project is a collaboration between Equal Access – Nepal (EAN), Equal Access – International, local stakeholders and listeners, a network of trained community researchers, and a research team from two Australian universities. A key element of the project is the establishment of an organisational culture within EAN that values and supports the impact assessment process being developed, which is based on continuous action learning and improvement. The paper describes the situation related to monitoring and evaluation (M&E) and impact assessment before the project began, in which EAN was often reliant on time-bound studies and ‘success stories’ derived from listener letters and feedback. We then outline the various strategies used in an effort to develop stronger and more effective impact assessment and M&E systems, and the gradual changes that have occurred to date. These changes include a greater understanding of the value of adopting a participatory, holistic, evidence-based approach to impact assessment. We also critically review the many challenges experienced in this process, including:----- • Tension between the pressure from donors to ‘prove’ impacts and the adoption of a bottom-up, participatory approach based on ‘improving’ programs in ways that meet community needs and aspirations.----- • Resistance from the content teams to changing their existing M&E practices and to the perceived complexity of the approach.----- • Lack of meaningful connection between the M&E and content teams.----- • Human resource problems and lack of capacity in analysing qualitative data and reporting results.----- • The contextual challenges, including extreme poverty, wide cultural and linguistic diversity, poor transport and communications infrastructure, and political instability.----- • A general lack of acceptance of the importance of evaluation within Nepal due to accepting everything as fate or ‘natural’ rather than requiring investigation into a problem.
Resumo:
This study examines consumers' emotional responses to receiving viral mobile marketing communications in comparison to receiving mobile marketing communications where permission has not been given. The study also examines the relationship between these experienced emotions and what action tendencies consumers might consider as a result of these emotions, as well as how they attribute causality for their emotions. Using scenarios in an experimental design, the findings show that there are differences in consumer emotions as a result of the two marketing approaches. The findings also identify relationships between consumers' causal attributions and action tendencies in relation to themselves, the friend sending the viral m-marketing communication and the company involved.
Resumo:
The epilogue pulls together the conceptual and methodological significance of the papers in the special issue exploring childhood and social interaction in everyday life in Sweden, Norway, United States and Australia. In considering the special issue, four domains of childhood are identified and discussed: childhood is a social construct where children learn how to enter into and participate in their social organizations, competency is best understood when communicative practices are examined in situ, children’s talk and interaction show situated culture in action, and childhood consists of shared social orders between children and adults. Emerging analytic interests are proposed, including investigating how children understand locations and place. Finally, the epilogue highlights the core focus of this special issue, which is showing children’s own methods for making sense of their everyday contexts using the interactional and cultural resources they have to hand.