23 resultados para , Design Experiment
Resumo:
Benefiting from design in theory learning is not common in architecture schools. The general practice is to design in studio and to theorise in lectures. In the undergraduate module History and Theory in Architecture II at Queen’s University Belfast, students attend interactive lectures, participate in reading group discussions, design TextObjects, and write essays. TextObjects contain textual, audio and/or graphic representations that highlight a single concept or a complex set of issues derived from readings. Students experiment with diverse media, such as filmmaking, photography, and graphic design, some of which they experience for the first time. Lectures and readings revolve around theories of architectural representation, media and communication, which are practiced through TextObjects. This is a new way to link theory and practice in architectural education. Through action research, this study analyses this innovative teaching method called TextObject, which brings design and practice into architectural theory education to stimulate students towards critical thinking. The pedagogical research of architectural theoretician Necdet Teymur (1992, 1996, 2002) underlies the study.
Resumo:
Objective: Establish maternal preferences for a third-trimester ultrasound scan in a healthy, low-risk pregnant population.
Design: Cross-sectional study incorporating a discrete choice experiment.
Setting: A large, urban maternity hospital in Northern Ireland.
Participants: One hundred and forty-six women in their second trimester of pregnancy.
Methods: A discrete choice experiment was designed to elicit preferences for four attributes of a third-trimester ultrasound scan: health-care professional conducting the scan, detection rate for abnormal foetal growth, provision of non-medical information, cost. Additional data collected included age, marital status, socio-economic status, obstetric history, pregnancy-specific stress levels, perceived health and whether pregnancy was planned. Analysis was undertaken using a mixed logit model with interaction effects.
Main outcome measures: Women's preferences for, and trade-offs between, the attributes of a hypothetical scan and indirect willingness-to-pay estimates.
Results: Women had significant positive preference for higher rate of detection, lower cost and provision of non-medical information, with no significant value placed on scan operator. Interaction effects revealed subgroups that valued the scan most: women experiencing their first pregnancy, women reporting higher levels of stress, an adverse obstetric history and older women.
Conclusions: Women were able to trade on aspects of care and place relative importance on clinical, non-clinical outcomes and processes of service delivery, thus highlighting the potential of using health utilities in the development of services from a clinical, economic and social perspective. Specifically, maternal preferences exhibited provide valuable information for designing a randomized trial of effectiveness and insight for clinical and policy decision makers to inform woman-centred care.
Resumo:
Efficiently exploring exponential-size architectural design spaces with many interacting parameters remains an open problem: the sheer number of experiments required renders detailed simulation intractable.We attack this via an automated approach that builds accurate predictive models. We simulate sampled points, using results to teach our models the function describing relationships among design parameters. The models can be queried and are very fast, enabling efficient design tradeoff discovery. We validate our approach via two uniprocessor sensitivity studies, predicting IPC with only 1–2% error. In an experimental study using the approach, training on 1% of a 250-K-point CMP design space allows our models to predict performance with only 4–5% error. Our predictive modeling combines well with techniques that reduce the time taken by each simulation experiment, achieving net time savings of three-four orders of magnitude.
Resumo:
Background: There is a dearth of evidence regarding the impact of urban regeneration projects on public health, particularly the nature and degree to which urban regeneration impacts upon health-related behaviour change. Natural experiment methodology enables comprehensive large-scale evaluations of such interventions. The Connswater Community Greenway in Belfast is a major urban regeneration project involving the development of a 9 km linear park, including the provision of new cycle paths and walkways. In addition to the environmental improvements, this complex intervention involves a number of programmes to promote physical activity in the regenerated area. The project affords a unique opportunity to investigate the public health impact of urban regeneration.
Methods/Design: The evaluation framework was informed by the socio-ecological model and guided by the RE-AIM Framework. Key components include: (1) a quasi-experimental before-and-after survey of the Greenway population (repeated cross-sectional design), in tandem with data from a parallel Northern Ireland-wide survey for comparison; (2) an assessment of changes in the local built environment and of walkability using geographic information systems; (3) semi-structured interviews with a purposive sample of survey respondents, and a range of community stakeholders, before and after the regeneration project; and (4) a cost-effectiveness analysis. The primary outcome is change in proportion of individuals identified as being regularly physically active, according to the current UK recommendations. The RE-AIM Framework will be used to make an overall assessment of the impact of the Greenway on the physical activity behaviour of local residents.
Discussion: The Connswater Community Greenway provides a significant opportunity to achieve long-term, population level behaviour change. We argue that urban regeneration may be conceptualised meaningfully as a complex intervention comprising multiple components with the potential, individually and interactively, to affect the behaviour of a diverse population. The development and implementation of our comprehensive evaluation framework reflects this complexity and illuminates an approach to the empirical, rigorous evaluation of urban regeneration. More specifically, this study will add to the much needed evidence-base about the impact of urban regeneration on public health as well as having important implications for the development of natural experiment methodology.
Resumo:
Objective: We explored whether readers can understand key messages without having to read the full review, and if there were differences in understanding between various types of summary.
Design: A randomised experiment of review summaries which compared understanding of a key outcome.
Participants: Members of university staff (n = 36).
Setting: Universities on the island of Ireland.
Method: The Cochrane Review chosen examines the health impacts of the use of electric fans during heat waves. Participants were asked their expectation of the effect these would have on mortality. They were then randomly assigned a summary of the review (i.e. abstract, plain language summary, podcast or podcast transcription) and asked to spend a short time reading/listening to the summary. After this they were again asked about the effects of electric fans on mortality and to indicate if they would want to read the full Review.
Main outcome measure: Correct identification of a key review outcome.
Results: Just over half (53%) of the participants identified its key message on mortality after engaging with their summary. The figures were 33% for the abstract group, 50% for both the plain language and transcript groups and 78% for the podcast group.
Conclusions: The differences between the groups were not statistically significant but suggest that the audio summary might improve knowledge transfer compared to written summaries. These findings should be explored further using a larger sample size and with other reviews.
Resumo:
The objective of this research was to design granulated iron oxide for the adsorption of heavy metals from wastewater. Polyvinyl acetate (PVAc) was chosen as a suitable binder; as it is water insoluble. Initial experiments on selection of suitable solvent of the polymer were carried out using three solvents namely; methanol, acetone and toluene. Based on the initial tests on product yield and mechanical strength, acetone was selected as the solvent for the polyvinyl acetate binder. Design of experiment was then used to investigate the influence of granulation process variables; impeller speed, binder concentration and liquid to solid ratio on the properties of the granular materials. The response variables in the study were granules mean size, stability in water and granule strength. The results showed that the combination of high impeller speed and high binder concentration favour the formation of strong and stable granules. Results also showed that leaching of the binder into the simulated was water was negligible. Trial adsorption experiments carried out using the strongest and most stable iron oxide granules produced in this work showed removal efficiency of around 70% of synthetic arsenic solutions with initial concentration of 1000 ppb.
Resumo:
Laboratory classes provide a visual and practical way of supplementing traditional teaching through lectures and tutorial classes. A criticism of laboratories in our School is that they are largely based on demonstration with insufficient participation by students. This provided the motivation to create a new laboratory experiment which would be interactive, encourage student enthusiasm with the subject and improve the quality of student learning.
The topic of the laboratory is buoyancy. While this is a key topic in the first-year fluids module, the laboratory has been designed in such a way that prior knowledge of the topic is unnecessary and therefore it would be accessible by secondary school pupils. The laboratory climaxes in a design challenge. However, it begins with a simple task involving students identifying some theoretical background information using given websites. They then have to apply their knowledge by developing some equations. Next, given some materials (a sheet of tinfoil, card and blu-tack), they have to design a vessel to carry the greatest mass without sinking. Thus, they are given an open-ended problem and have to provide a mathematical justification for their design. Students are expected to declare the maximum mass for their boat in advance of it being tested to create a sense of competition and fun. Overall, the laboratory involves tasks which begin at a low level and progressively get harder, incorporating understanding, applying, evaluating and designing (with reference to Bloom’s taxonomy).
The experiment has been tested in a modern laboratory with wall-mounted screens and access to the internet. Students enjoyed the hands-on aspect and thought the format helped their learning.
The use of cheap materials which are readily available means that many students can be involved at one time. Support documentation has been produced, both for the student participants and the facilitator. The latter is given advice on how to guide the students (without simply giving them the answer) and given some warning about potential problems the students might have.
The authors believe that the laboratory can be adapted for use by secondary school pupils and hope that it will be used to promote engineering in an engaging and enthusing way to a wider audience. To this end, contact has already been made with the Widening Participation Unit at the University to gain advice on possible next steps.
Resumo:
In the highly competitive world of modern finance, new derivatives are continually required to take advantage of changes in financial markets, and to hedge businesses against new risks. The research described in this paper aims to accelerate the development and pricing of new derivatives in two different ways. Firstly, new derivatives can be specified mathematically within a general framework, enabling new mathematical formulae to be specified rather than just new parameter settings. This Generic Pricing Engine (GPE) is expressively powerful enough to specify a wide range of stand¬ard pricing engines. Secondly, the associated price simulation using the Monte Carlo method is accelerated using GPU or multicore hardware. The parallel implementation (in OpenCL) is automatically derived from the mathematical description of the derivative. As a test, for a Basket Option Pricing Engine (BOPE) generated using the GPE, on the largest problem size, an NVidia GPU runs the generated pricing engine at 45 times the speed of a sequential, specific hand-coded implementation of the same BOPE. Thus a user can more rapidly devise, simulate and experiment with new derivatives without actual programming.