958 resultados para Models, Educational
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PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.
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We propose a method for learning specific object representations that can be applied (and reused) in visual detection and identification tasks. A machine learning technique called Cartesian Genetic Programming (CGP) is used to create these models based on a series of images. Our research investigates how manipulation actions might allow for the development of better visual models and therefore better robot vision. This paper describes how visual object representations can be learned and improved by performing object manipulation actions, such as, poke, push and pick-up with a humanoid robot. The improvement can be measured and allows for the robot to select and perform the `right' action, i.e. the action with the best possible improvement of the detector.
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Epigenetic changes correspond to heritable modifications of the chromosome structure, which do not involve alteration of the DNA sequence but do affect gene expression. These mechanisms play an important role in normal cell differentiation, but aberration is associated also with several diseases, including cancer and neural disorders. In consequence, despite intensive studies in recent years, the contribution of modifications remains largely unquantified due to overall system complexity and insufficient data. Computational models can provide powerful auxiliary tools to experimentation, not least as scales from the sub-cellular through cell populations (or to networks of genes) can be spanned. In this paper, the challenges to development, of realistic cross-scale models, are discussed and illustrated with respect to current work.
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The United Nations Convention on the Rights of the Child provides a significant platform to include children’s views on issues that affect their lives, yet, in many contexts, particularly in educational practice, children’s perspectives continue to be irregularly sought and are rarely acted upon. By providing children’s perspectives on what they would like adults to know, this article explores a unique view of childhood and the interactions with family, community, educational experiences and well-being. The children’s insights about their worlds that they feel adults are missing potentiate the development and incorporation of voice-inclusive practice. While the sense that each child makes of their Lebenswelt – the ‘ingredients’ – is idiosyncratic and will be influenced by many factors, including peers, teachers, parents, other adults and the media, it is the nature of this personal understanding that is poorly understood, and consequently ignored by adults. By exploring the commentary of more than 1000 children across five countries – Australia, England, New Zealand, Italy and Sweden – this research reveals an overwhelming collection of what the authors describe as ‘comments that rhyme’ in terms of the identification of expressed sentiment and thematic representations of their perspectives.
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Tumour microenvironment greatly influences the development and metastasis of cancer progression. The development of three dimensional (3D) culture models which mimic that displayed in vivo can improve cancer biology studies and accelerate novel anticancer drug screening. Inspired by a systems biology approach, we have formed 3D in vitro bioengineered tumour angiogenesis microenvironments within a glycosaminoglycan-based hydrogel culture system. This microenvironment model can routinely recreate breast and prostate tumour vascularisation. The multiple cell types cultured within this model were less sensitive to chemotherapy when compared with two dimensional (2D) cultures, and displayed comparative tumour regression to that displayed in vivo. These features highlight the use of our in vitro culture model as a complementary testing platform in conjunction with animal models, addressing key reduction and replacement goals of the future. We anticipate that this biomimetic model will provide a platform for the in-depth analysis of cancer development and the discovery of novel therapeutic targets.
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GVHD remains the major complication of allo-HSCT. Murine models are the primary system used to understand GVHD, and to develop potential therapies. Several factors are critical for GVHD in these models; including histo- compatibility, conditioning regimen, and T-cell number. We serendipitously found that environmental factors such as the caging system and bedding also significantly impact the kinetics of GVHD in these models. This is important because such factors may influence the experimental conditions required to cause GVHD and how mice respond to various treatments. Consequently, this is likely to alter interpretation of results between research groups, and the perceived effectiveness of experimental therapies.
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Those who teach film and media need to use screen content to illustrate their subjects. For example, students want illustrations to accompany lectures on film or television genres. Our experience has been that student access to the film and television screen content underpinning a study of genres is not only desirable but is, in fact, crucial for effective teaching and learning outcomes. Not so long ago, a screening during or at the completion of a lecture was the expected method by which educators delivered screen content to illustrate their teaching. Even if student attendance fluctuated from week to week a quick head count confirmed that a certain number of students were physically present. It was assumed that this physical attendance encouraged students to reflect upon and contextualize the material post lecture. While simply attending a lecture will not translate into actual student learning, it does demonstrate a willingness by students to engage with the course content by making a commitment to attend a scheduled and recurring lecture and screening program. However, as flipped classroom models gain acceptance in educational institutions, this traditional lecture-screening model is giving way to online, off-site, and student-controlled mechanisms for screen content delivery and viewing. Nevertheless, care should be taken when assessing how online delivery translates into student engagement and learning. As Junco (2012) points out, “it’s not the technology that generates learning, but the ways in which the technology are used.” Discussed, debated, and embraced to varying degrees by educators, there remains no definitive model for the flipped classroom – although many models involve ‘flipping’ content and knowledge acquisition (including viewing films and television shows) from scheduled on-campus classes to online material viewed by students in advance of an on-campus lecture or class. The classroom or tutorial room then becomes a space to problem-solve, engage in collaborate learning, and advance and explain concepts. From an institutional perspective, the flipped classroom model could deliver an additional benefit beyond immediate pedagogical concerns. Tucker (2012) suggests through the flipped classroom model “all aspects of instruction can be rethought to best maximize the scarcest learning resource — time.” The narrative most often associated with this shift is that the move to online content delivery of lecture and cinematic / televisual material may also provide educators with more time to do other work such as engage in research, plan strategies to empower students. Experimentation with the flipped classroom model is playing out in various educational institutions. Yet several core concerns remain — one of these concerns is the crucial question of whether an online/digital flipped approach is more effective for student engagement and learning than the traditional lecture-screening mode for screen content delivery. Some urge caution in this regard, arguing that “new technology isn’t always supported by change management and professional development to ensure that digital isn’t just a goal within itself, but actually helps to transform education” (Fleming cited in Blain 2014). The most fundamental concern remains how do lecturers, instructors, and tutors know students have watched the films and television shows associated with a subject? The remainder of this discussion deals with these concerns, and possible solutions offered, through an analysis of the Film, Television and Screen Genres subject at the Queensland University of Technology (QUT) in Brisbane, Queensland.
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To identify current ED models of care and their impact on care quality, care effectiveness, and cost. A systematic search of key health databases (Medline, CINAHL, Cochrane, EMbase) was conducted to identify literature on ED models of care. Additionally, a focused review of the contents of 11 international and national emergency medicine, nursing and health economic journals (published between 2010 and 2013) was undertaken with snowball identification of references of the most recent and relevant papers. Articles published between 1998 and 2013 in the English language were included for initial review by three of the authors. Studies in underdeveloped countries and not addressing the objectives of the present study were excluded. Relevant details were extracted from the retrieved literature, and analysed for relevance and impact. The literature was synthesised around the study's main themes. Models described within the literature mainly focused on addressing issues at the input, throughput or output stages of ED care delivery. Models often varied to account for site specific characteristics (e.g. onsite inpatient units) or to suit staffing profiles (e.g. extended scope physiotherapist), ED geographical location (e.g. metropolitan or rural site), and patient demographic profile (e.g. paediatrics, older persons, ethnicity). Only a few studies conducted cost-effectiveness analysis of service models. Although various models of delivering emergency healthcare exist, further research is required in order to make accurate and reliable assessments of their safety, clinical effectiveness and cost-effectiveness.
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Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.
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In this paper we present a new method for performing Bayesian parameter inference and model choice for low count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel pseudo-marginal algorithm, which we refer to as alive SMC^2. The advantages of this approach over competing approaches is that it is naturally adaptive, it does not involve between-model proposals required in reversible jump Markov chain Monte Carlo and does not rely on potentially rough approximations. The algorithm is demonstrated on Markov process and integer autoregressive moving average models applied to real biological datasets of hospital-acquired pathogen incidence, animal health time series and the cumulative number of poison disease cases in mule deer.
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There has, in recent decades, been considerable scholarship regarding the moral aspects of corporate governance,and differences in corporate governance practices around the world have been widely documented and investigated. In such a context, the claims associated with moral relativism are relevant. The purpose of this paper is to provide a detailed consideration of how the metaethical and normative claims of moral relativism in particular can be applied to corporate governance. This objective is achieved, firstly, by reviewing what is meant by metaethical moral relativism and identifying two ways in which the metaethical claim can be assessed. The possibility of a single, morally superior model of corporate governance is subsequently considered through an analysis of prominent works justifying the shareholder and stakeholder approaches, together with a consideration of academic agreement in this area. The paper then draws on the work of Wong (Moral relativity, University of California Press, Berkeley, CA, 1984, A companion to ethics, Blackwell, Malden, 1993, Natural moralities: A defense of pluralistic relativism,Oxford University Press, Oxford, 2006), firstly in providing an argument supporting metaethical moral relativism and secondly regarding values of tolerance and/or accommodation that can contribute to the normative claim. The paper concludes by proposing an argument that it is morally wrong to impose a model of corporate governance where there are differences in moral judgements relevant to corporate governance, or to interfere with a model in similar circumstances, and closes with consideration of the argument’s implications.
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This work addresses fundamental issues in the mathematical modelling of the diffusive motion of particles in biological and physiological settings. New mathematical results are proved and implemented in computer models for the colonisation of the embryonic gut by neural cells and the propagation of electrical waves in the heart, offering new insights into the relationships between structure and function. In particular, the thesis focuses on the use of non-local differential operators of non-integer order to capture the main features of diffusion processes occurring in complex spatial structures characterised by high levels of heterogeneity.
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The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.
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To report the outcomes of a randomised educational trial of a new methodology for extended immersion in medical simulation for senior medical students. Clinical Learning through Extended Immersion in Medical Simulation (CLEIMS) is a new methodology for medical student learning. It involves senior students working in teams of 4-5 through the clinical progress of one or more patients over a week, utilising a range of simulation methodologies (simulated patient assessment, simulated significant other briefing, virtual story continuations, pig-trotter wound repair, online simulated on-call modules, interprofessional simulated ward rounds and high fidelity mannequin-based emergency simulations), to enhance learning in associated workshops and seminars. A randomised educational trial comparing the methodology to seminars and workshops alone began in 2010 and interim results were reported at last year’s conference. Updated results are presented here and final primary endpoint outcomes will be available by the time of the conference.
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Objective This review aims to summarize the importance of animal models for research on psychiatric illnesses, particularly schizophrenia. Method and Results Several aspects of animal models are addressed, including animal experimentation ethics and theoretical considerations of different aspects of validity of animal models. A more specific discussion is included on two of the most widely used behavioural models, psychotropic drug-induced locomotor hyperactivity and prepulse inhibition, followed by comments on the difficulty of modelling negative symptoms of schizophrenia. Furthermore, we emphasize the impact of new developments in molecular biology and the generation of genetically modified mice, which have generated the concept of behavioural phenotyping. Conclusions Complex psychiatric illnesses, such as schizophrenia, cannot be exactly reproduced in species such as rats and mice. Nevertheless, by providing new information on the role of neurotransmitter systems and genes in behavioural function, animal 'models' can be an important tool in unravelling mechanisms involved in the symptoms and development of such illnesses, alongside approaches such as post-mortem studies, cognitive and psychophysiological studies, imaging and epidemiology.