985 resultados para testing platform
Resumo:
When designing a new passenger ship or modifying an existing design, how do we ensure that the proposed design and crew emergency procedures are safe from an evacuation point of view? In the wake of major maritime disasters such as the Herald of Free Enterprise and the Estonia and in light of the growth in the numbers of high density, high-speed ferries and large capacity cruise ships, issues concerned with the evacuation of passengers and crew at sea are receiving renewed interest. In the maritime industry, ship evacuation models offer the promise to quickly and efficiently bring evacuation considerations into the design phase, while the ship is "on the drawing board". maritimeEXODUS-winner of the BCS, CITIS and RINA awards - is such a model. Features such as the ability to realistically simulate human response to fire, the capability to model human performance in heeled orientations, a virtual reality environment that produces realistic visualisations of the modelled scenarios and with an integrated abandonment model, make maritimeEXODUS a truly unique tool for assessing the evacuation capabilities of all types of vessels under a variety of conditions. This paper describes the maritimeEXODUS model, the SHEBA facility from which data concerning passenger/crew performance in conditions of heel is derived and an example application demonstrating the models use in performing an evacuation analysis for a large passenger ship partially based on the requirements of MSC circular 1033.
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Using Acoustic Emission Testing (AET) to determine the onset of paper damage will be demonstrated on tensile coupons made from mechanical pulp. This technique is part of an EU funded project named the Fifth Frame Program. Its aim is to develop methods for determining specific damage mechanisms through AET. Various such techniques of damage detection will be demonstrated in the coming work.
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This report covers the testing and evaluation of the airEXODUS evacuation model. airEXODUS has been developed for evacuation certification testing, crew training and aircraft design. The report demonstrates the effectiveness of the model.
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This paper describes work towards the deployment of flexible self-management into real-time embedded systems. A challenging project which focuses specifically on the development of a dynamic, adaptive automotive middleware is described, and the specific self-management requirements of this project are discussed. These requirements have been identified through the refinement of a wide-ranging set of use cases requiring context-sensitive behaviours. A sample of these use-cases is presented to illustrate the extent of the demands for self-management. The strategy that has been adopted to achieve self-management, based on the use of policies is presented. The embedded and real-time nature of the target system brings the constraints that dynamic adaptation capabilities must not require changes to the run-time code (except during hot update of complete binary modules), adaptation decisions must have low latency, and because the target platforms are resource-constrained the self-management mechanism have low resource requirements (especially in terms of processing and memory). Policy-based computing is thus and ideal candidate for achieving the self-management because the policy itself is loaded at run-time and can be replaced or changed in the future in the same way that a data file is loaded. Policies represent a relatively low complexity and low risk means of achieving self-management, with low run-time costs. Policies can be stored internally in ROM (such as default policies) as well as externally to the system. The architecture of a designed-for-purpose powerful yet lightweight policy library is described. A suitable evaluation platform, supporting the whole life-cycle of feasibility analysis, concept evaluation, development, rigorous testing and behavioural validation has been devised and is described.
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Brusilovsky and Millan (2007) state that learning styles are typically defined as the way people prefer to learn. Learning styles and how we learn is a vast research area and many research projects (SMILE, INSPIRE, iWeaver amongst others) attempt to incorporate these learning styles into e-Learning systems. This paper describes commonly used learning styles and how they are currently being used within the area of adaptive e-Learning. This work also builds upon current research and evaluates learning styles using criteria proposed by Sampson and Karagiannidis (2004) in order to select a suitable learning methodology for the iLearn e-Learning platform. The Sampson and Karagiannidis (2004) criteria is adapted for the purpose of the research and describes the measurability, time effectiveness and descriptiveness and prescriptiveness of the specific learning style. A suitable learning style for the iLearn e-Learning platform is then proposed within the paper and finally the research briefly introduces how the chosen learning style will be used for the proposed e-Learning platform.
Resumo:
Rule testing in transport scheduling is a complex and potentially costly business problem. This paper proposes an automated method for the rule-based testing of business rules using the extensible Markup Language for rule representation and transportation. A compiled approach to rule execution is also proposed for performance-critical scheduling systems.
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Scepticism over stated preference surveys conducted online revolves around the concerns over “professional respondents” who might rush through the questionnaire without sufficiently considering the information provided. To gain insight on the validity of this phenomenon and test the effect of response time on choice randomness, this study makes use of a recently conducted choice experiment survey on ecological and amenity effects of an offshore windfarm in the UK. The positive relationship between self-rated and inferred attribute attendance and response time is taken as evidence for a link between response time and cognitive effort. Subsequently, the generalised multinomial logit model is employed to test the effect of response time on scale, which indicates the weight of the deterministic relative to the error component in the random utility model. Results show that longer response time increases scale, i.e. decreases choice randomness. This positive scale effect of response time is further found to be non-linear and wear off at some point beyond which extreme response time decreases scale. While response time does not systematically affect welfare estimates, higher response time increases the precision of such estimates. These effects persist when self-reported choice certainty is controlled for. Implications of the results for online stated preference surveys and further research are discussed.
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The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.
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This chapter describes methods for testing biocides against microbes. The first part describes a method using flow cytometry to test biocides against multispecies communities of planktonic microbial assemblage and Part 2 describes methods to test biocides against both single and multispecies biofilms.