995 resultados para supersymmetric affine Toda models


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This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering performance is experimentally examined in the context of an important image based aircraft target tracking application. Surprisingly, tracking of dim small-sized targets (as small as 5-10 pixels, with local detectability/SNR as low as − 1.05 dB) was only mildly impacted by compressed sensing down to 15% of original image size.

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Recent natural disasters such as the Haitian earthquake 2011, the South East Queensland floods 2011, the Japanese earthquake and tsunami 2011 and Hurricane Sandy in the United States of America in 2012, have seen social media platforms changing the face of emergency management communications, not only in times of crisis and also during business-as-usual operations. With social media being such an important and powerful communication tool, especially for emergency management organisations, the question arises as to whether the use of social media in these organisations emerged by considered strategic design or more as a reactive response to a new and popular communication channel. This paper provides insight into how the social media function has been positioned, staffed and managed in organisations throughout the world, with a particular focus on how these factors influence the style of communication used on social media platforms. This study has identified that the social media function falls on a continuum between two polarised models, namely the authoritative one-way communication approach and the more interactive approach that seeks to network and engage with the community through multi-way communication. Factors such the size of the organisation; dedicated resourcing of the social media function; organisational culture and mission statement; the presence of a social media champion within the organisation; management style and knowledge about social media play a key role in determining where on the continuum organisations sit in relation to their social media capability. This review, together with a forthcoming survey of Australian emergency management organisations and local governments, will fill a gap in the current body of knowledge about the evolution, positioning and usage of social media in organisations working in the emergency management field in Australia. These findings will be fed back to Industry for potential inclusion in future strategies and practices.

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In this paper, a novel data-driven approach to monitoring of systems operating under variable operating conditions is described. The method is based on characterizing the degradation process via a set of operation-specific hidden Markov models (HMMs), whose hidden states represent the unobservable degradation states of the monitored system while its observable symbols represent the sensor readings. Using the HMM framework, modeling, identification and monitoring methods are detailed that allow one to identify a HMM of degradation for each operation from mixed-operation data and perform operation-specific monitoring of the system. Using a large data set provided by a major manufacturer, the new methods are applied to a semiconductor manufacturing process running multiple operations in a production environment.

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Adolescent idiopathic scoliosis (AIS) is a spinal deformity, which may require surgical correction by attaching rods to the patient’s spine using screws inserted into the vertebrae. Complication rates for deformity correction surgery are unacceptably high. Determining an achievable correction without overloading the adjacent spinal tissues or implants requires an understanding of the mechanical interaction between these components. We have developed novel patient specific modelling software to create individualized finite element models (FEM) representing the thoracolumbar spine and ribcage of scoliosis patients. We are using these models to better understand the biomechanics of spinal deformity correction.

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Objective To describe women’s reports of the model of care options General Practitioners (GPs) discussed with them at the first pregnancy consultation and women’s self-reported role in decisionmaking about model of care. Methods Women who had recently given birth responded to survey items about the models of care GPs discussed, their role in final decision-making, and socio-demographic, obstetric history, and early pregnancy characteristics. Results The proportion of women with whom each model of care was discussed varied between 8.2% (for private midwifery care with home birth) and 64.4% (GP shared care). Only 7.7% of women reported that all seven models were discussed. Exclusive discussion about private obstetric care and about all public models was common, and women’s health insurance status was the strongest predictor of the presence of discussions about each model. Most women (82.6%) reported active involvement in final decision-making about model of care. Conclusion Although most women report involvement in maternity model of care decisions, they remain largely uninformed about the breadth of available model of care options. Practical implications Strategies that facilitate women’s access to information on the differentiating features and outcomes for all models of care should be prioritized to better ensure equitable and quality decisions.

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Background  Models of service provision and professional training differ between countries. This study aims to investigate a specialist intellectual disabilities model and a generic mental health model, specifically comparing psychiatrists’ knowledge and competencies, and service quality and accessibility in meeting the mental health needs of people with intellectual disabilities. Method  Data were collected from consultant and trainee psychiatrists within a specialist intellectual disabilities model (UK) and a generic mental health model (Australia). Results  The sample sizes were 294 (UK) and 205 (Australia). Statistically significant differences were found, with UK participants having positive views about the specialist intellectual disabilities service model they worked within, demonstrating flexible and accessible working practices and service provision, responsive to the range of mental health needs of the population with intellectual disabilities, and providing a wide range of treatments and supports. The UK participants were knowledgeable, well trained and confident in their work. They wanted to work with people with intellectual disabilities. In all of these areas, the converse was found from the Australian generic mental health service model. Conclusions  The specialist intellectual disabilities model of service provision and training has advantages over the generic mental health model.

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Channels are becoming an increasingly important area for companies to innovate, specifically as they provide direct points of contact with their customers. However, little is known in regards to multi-channel strategies that embody strategic brand values and how customers experience these channels collectively. The purpose of this paper is to investigate how organisations configure multi- channel strategies to communicate their brand value and experience to their customers. Data was collated from sixty companies through a content analysis methodology within the retail sector. Results uncovered commonalities through the identification of four meta-models surrounding common brand values, intended emotive experience, individual channels and the customer segment. These meta-models are titled: High Quality, Trust, Convenience and Community. This research also presents implications of a multi-channel design tool based on findings from this study to help reinforce company brand values and design an overall connected customer experience.

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"This collection of papers offers a broad synopsis of state-of-the-art mathematical methods used in modeling the interaction between tumors and the immune system. These papers were presented at the four-day workshop on Mathematical Models of Tumor-Immune System Dynamics held in Sydney, Australia from January 7th to January 10th, 2013. The workshop brought together applied mathematicians, biologists, and clinicians actively working in the field of cancer immunology to share their current research and to increase awareness of the innovative mathematical tools that are applicable to the growing field of cancer immunology. Recent progress in cancer immunology and advances in immunotherapy suggest that the immune system plays a fundamental role in host defense against tumors and could be utilized to prevent or cure cancer. Although theoretical and experimental studies of tumor-immune system dynamics have a long history, there are still many unanswered questions about the mechanisms that govern the interaction between the immune system and a growing tumor. The multidimensional nature of these complex interactions requires a cross-disciplinary approach to capture more realistic dynamics of the essential biology. The papers presented in this volume explore these issues and the results will be of interest to graduate students and researchers in a variety of fields within mathematical and biological sciences."--Publisher website

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This paper presents an event-based failure model to predict the number of failures that occur in water distribution assets. Often, such models have been based on analysis of historical failure data combined with pipe characteristics and environmental conditions. In this paper weather data have been added to the model to take into account the commonly observed seasonal variation of the failure rate. The theoretical basis of existing logistic regression models is briefly described in this paper, along with the refinements made to the model for inclusion of seasonal variation of weather. The performance of these refinements is tested using data from two Australian water authorities.

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The business model concept is gaining traction in different disciplines but is still criticized for being fuzzy and vague and lacking consensus on its definition and compositional elements. In this paper we set out to advance our understanding of the business model concept by addressing three areas of foundational research: business model definitions, business model elements, and business model archetypes. We define a business model as a representation of the value logic of an organization in terms of how it creates and captures customer value. This abstract and generic definition is made more specific and operational by the compositional elements that need to address the customer, value proposition, organizational architecture (firm and network level) and economics dimensions. Business model archetypes complement the definition and elements by providing a more concrete and empirical understanding of the business model concept. The main contributions of this paper are (1) explicitly including the customer value concept in the business model definition and focussing on value creation, (2) presenting four core dimensions that business model elements need to cover, (3) arguing for flexibility by adapting and extending business model elements to cater for different purposes and contexts (e.g. technology, innovation, strategy),(4) stressing a more systematic approach to business model archetypes by using business model elements for their description, and (5) suggesting to use business model archetype research for the empirical exploration and testing of business model elements and their relationships.

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A discrete agent-based model on a periodic lattice of arbitrary dimension is considered. Agents move to nearest-neighbor sites by a motility mechanism accounting for general interactions, which may include volume exclusion. The partial differential equation describing the average occupancy of the agent population is derived systematically. A diffusion equation arises for all types of interactions and is nonlinear except for the simplest interactions. In addition, multiple species of interacting subpopulations give rise to an advection-diffusion equation for each subpopulation. This work extends and generalizes previous specific results, providing a construction method for determining the transport coefficients in terms of a single conditional transition probability, which depends on the occupancy of sites in an influence region. These coefficients characterize the diffusion of agents in a crowded environment in biological and physical processes.

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This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

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This thesis has contributed to the advancement of knowledge in disease modelling by addressing interesting and crucial issues relevant to modelling health data over space and time. The research has led to the increased understanding of spatial scales, temporal scales, and spatial smoothing for modelling diseases, in terms of their methodology and applications. This research is of particular significance to researchers seeking to employ statistical modelling techniques over space and time in various disciplines. A broad class of statistical models are employed to assess what impact of spatial and temporal scales have on simulated and real data.

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Identifying railway capacity is an important task that can identify "in principal" whether the network can handle an intended traffic flow, and whether there is any free capacity left for additional train services. Capacity determination techniques can also be used to identify how best to improve an existing network, and at least cost. In this article an optimization approach has been applied to a case study of the Iran national railway, in order to identify its current capacity and to optimally expand it given a variety of technical conditions. This railway is very important in Iran and will be upgraded extensively in the coming years. Hence the conclusions in this article may help in that endeavor. A sensitivity analysis is recommended to evaluate a wider range of possible scenarios. Hence more useful lower and upper bounds can be provided for the performance of the system