http://hdl.handle.net/10468/568 2013-06-19T19:12:35Z 2013-06-19T19:12:35Z O'Mahony, Conor Wilson, Nic http://hdl.handle.net/10468/910 2013-01-24T03:00:12Z 2012-11-07T00:00:00Z

Sorted-pareto dominance: an extension to pareto dominance and its application in soft constraints O'Mahony, Conor; Wilson, Nic The Pareto dominance relation compares decisions with each other over multiple aspects, and any decision that is not dominated by another is called Pareto optimal, which is a desirable property in decision making. However, the Pareto dominance relation is not very discerning, and often leads to a large number of non-dominated or Pareto optimal decisions. By strengthening the relation, we can narrow down this nondominated set of decisions to a smaller set, e.g., for presenting a smaller number of more interesting decisions to a decision maker. In this paper, we look at a particular strengthening of the Pareto dominance called Sorted-Pareto dominance, giving some properties that characterise the relation, and giving a semantics in the context of decision making under uncertainty. We then examine the use of the relation in a Soft Constraints setting, and explore some algorithms for generating Sorted-Pareto optimal solutions to Soft Constraints problems.

2012-11-07T00:00:00Z Ma, Ji Murphy, David Provan, Gregory Hayes, Michael Ó Mathúna, S. Cian http://hdl.handle.net/10468/567 2012-07-11T02:00:19Z 2011-09-01T00:00:00Z

Trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms: a model-based framework Ma, Ji; Murphy, David; Provan, Gregory; Hayes, Michael; Ó Mathúna, S. Cian Tobin, Ena Evaluation of temperature distribution in cold rooms is an important consideration in the design of food storage solutions. Two common approaches used in both industry and academia to address this question are the deployment of wireless sensors, and modelling with Computational Fluid Dynamics (CFD). However, for a realworld evaluation of temperature distribution in a cold room, both approaches have their limitations. For wireless sensors, it is economically unfeasible to carry out large-scale deployment (to obtain a high resolution of temperature distribution); while with CFD modelling, it is usually not accurate enough to get a reliable result. In this paper, we propose a model-based framework which combines the wireless sensors technique with CFD modelling technique together to achieve a satisfactory trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms. A case study is presented to demonstrate the usability of the framework.

2011-09-01T00:00:00Z Ma, Ji Murphy, David Ó Mathúna, S. Cian Hayes, Michael Provan, Gregory http://hdl.handle.net/10468/569 2013-03-08T03:01:06Z 2011-09-01T00:00:00Z

Model and visualise the relationship between energy consumption and temperature distribution in cold rooms Ma, Ji; Murphy, David; Ó Mathúna, S. Cian; Hayes, Michael; Provan, Gregory Carr, Hamish; Grimstead, Ian In the area of food and pharmacy cold storage, temperature distribution is considered as a key factor. Inappropriate distribution of temperature during the cooling process in cold rooms will cause the deterioration of the quality of products and therefore shorten their life-span. In practice, in order to maintain the distribution of temperature at an appropriate level, large amount of electrical energy has to be consumed to cool down the volume of space, based on the reading of a single temperature sensor placed in every cold room. However, it is not clear and visible that what is the change of energy consumption and temperature distribution over time. It lacks of effective tools to visualise such a phenomenon. In this poster, we initially present a solution which combines a visualisation tool with a Computational Fluid Dynamics (CFD) model together to enable users to explore such phenomenon.

2011-09-01T00:00:00Z