Trade-off between minimum number of wireless sensors and the accuracy of temperature profile in cold rooms: a model-based framework

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.

Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

Non-product related environmental process and production methods (NPR-PPMs): a view from international trade law and international environmental governance

The primary aim of this thesis is to analyse legal and governance issues in the use of Environmental NPR-PPMs, particularly those aiming to promote sustainable practices or to protect natural resources. NPR-PPMs have traditionally been thought of as being incompatible with the rules of the World Trade Organization (WTO). However, the issue remains untouched by WTO adjudicatory bodies. One can suggest that WTO adjudicatory bodies may want to leave this issue to the Members, but the analysis of the case law also seems to indicate that the question of legality of NPR-PPMs has not been brought ‘as such’ in dispute settlement. This thesis advances the argument that despite the fact that the legal status of NPR-PPMs remains unsettled, during the last decades adjudicatory bodies have been scrutinising environmental measures based on NPR-PPMs just as another expression of the regulatory autonomy of the Members. Though NPR-PPMs are regulatory choices associated with a wide range of environmental concerns, trade disputes giving rise to questions related to the legality of process-based measures have been mainly associated with the protection of marine wildlife (i.e., fishing techniques threatening or affecting animal species). This thesis argues that environmental objectives articulated as NPR-PPMs can indeed qualify as legitimate objectives both under the GATT and the TBT Agreement. However, an important challenge for the their compatibility with WTO law relate to aspects associated with arbitrary or unjustifiable discrimination. In the assessment of discrimination procedural issues play an important role. This thesis also elucidates other important dimensions to the issue from the perspective of global governance. One of the arguments advanced in this thesis is that a comprehensive analysis of environmental NPR-PPMs should consider not only their role in what is regarded as trade barriers (governmental and market-driven), but also their significance in global objectives such as the transition towards a green economy and sustainable patterns of consumption and production.