Reasoning with sorted-pareto dominance and other qualitative and partially ordered preferences in soft constraints

In decision making problems where we need to choose a particular decision or alternative from a set of possible choices, we often have some preferences which determine if we prefer one decision over another. When these preferences give us an ordering on the decisions that is complete, then it is easy to choose the best or one of the best decisions. However it often occurs that the preferences relation is partially ordered, and we have no best decision. In this thesis, we look at what happens when we have such a partial order over a set of decisions, in particular when we have multiple orderings on a set of decisions, and we present a framework for qualitative decision making. We look at the different natural notions of optimal decision that occur in this framework, which gives us different optimality classes, and we examine the relationships between these classes. We then look in particular at a qualitative preference relation called Sorted-Pareto Dominance, which is an extension of Pareto Dominance, and we give a semantics for this relation as one that is compatible with any order-preserving mapping of an ordinal preference scale to a numerical one. We apply Sorted-Pareto dominance to a Soft Constraints setting, where we solve problems in which the soft constraints associate qualitative preferences to decisions in a decision problem. We also examine the Sorted-Pareto dominance relation in the context of our qualitative decision making framework, looking at the relevant optimality classes for the Sorted-Pareto case, which gives us classes of decisions that are necessarily optimal, and optimal for some choice of mapping of an ordinal scale to a quantitative one. We provide some empirical analysis of Sorted-Pareto constraints problems and examine the optimality classes that result.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.

Nanoporous InP: anodic formation and growth mechanism in aqueous electrolytes

Porous layers can be formed electrochemically on (100) oriented n-InP substrates in aqueous KOH. A nanoporous layer is obtained underneath a dense near-surface layer and the pores appear to propagate from holes through the near-surface layer. In the early stages of the anodization transmission electron microscopy (TEM) clearly shows individual porous domains that appear to have a square-based pyramidal shape. Each domain appears to develop from an individual surface pit which forms a channel through this near-surface layer. We suggest that the pyramidal structure arises as a result of preferential pore propagation along the <100> directions. AFM measurements show that the density of surface pits increases with time. Each of these pits acts as a source for a pyramidal porous domain. When the domains grow, the current density increases correspondingly. Eventually the domains meet, forming a continuous porous layer, the interface between the porous and bulk InP becomes relatively flat and its total effective surface area decreases resulting in a decrease in the current density. Current-time curves at constant potential exhibit a peak and porous layers are observed to form beneath the electrode surface. The density of pits formed on the surface increases with time and approaches a plateau value. Porous layers are also observed in highly doped InP but are not observed in wafers with doping densities below ~5 × 1017 cm-3. Numerical models of this process have been developed invoking a mechanism of directional selectivity of pore growth preferentially along the <100> lattice directions. Manipulation of the parameters controlling these curves shows that the fall-off in current is controlled by the rate of diffusion of electrolyte through the pore structure with the final decline in current being caused by the termination of growth at the pore tips through the formation of passivating films or some other irreversible modification of the pore tips.

National, inter-institutional, graduate modules – blended learning approaches for PhD education in Ireland

This paper is a case study that describes the design and delivery of national PhD lectures with 40 PhD candidates in Digital Arts and Humanities in Ireland simultaneously to four remote locations, in Trinity College Dublin, in University College Cork, in NUI Maynooth and NUI Galway. Blended learning approaches were utilized to augment traditional teaching practices combining: face-to-face engagement, video-conferencing to multiple sites, social media lecture delivery support – a live blog and micro blogging, shared, open student web presence online. Techniques for creating an effective, active learning environment were discerned via a range of learning options offered to students through student surveys after semester one. Students rejected the traditional lecture format, even through the novel delivery method via video link to a number of national academic institutions was employed. Students also rejected the use of a moderated forum as a means of creating engagement across the various institutions involved. Students preferred a mix of approaches for this online national engagement. The paper discusses successful methods used to promote interactive teaching and learning. These included Peer to peer learning, Workshop style delivery, Social media. The lecture became a national, synchronous workshop. The paper describes how allowing students to have a voice in the virtual classroom they become animated and engaged in an open culture of shared experience and scholarship, create networks beyond their institutions, and across disciplinary boundaries. We offer an analysis of our experiences to assist other educators in their course design, with a particular emphasis on social media engagement.

Chemical approaches for doping nanodevice architectures

Advanced doping technologies are key for the continued scaling of semiconductor devices and the maintenance of device performance beyond the 14 nm technology node. Due to limitations of conventional ion-beam implantation with thin body and 3D device geometries, techniques which allow precise control over dopant diffusion and concentration, in addition to excellent conformality on 3D device surfaces, are required. Spin-on doping has shown promise as a conventional technique for doping new materials, particularly through application with other dopant methods, but may not be suitable for conformal doping of nanostructures. Additionally, residues remain after most spin-on-doping processes which are often difficult to remove. In-situ doping of nanostructures is especially common for bottom-up grown nanostructures but problems associated with concentration gradients and morphology changes are commonly experienced. Monolayer doping (MLD) has been shown to satisfy the requirements for extended defect-free, conformal and controllable doping on many materials ranging from traditional silicon and germanium devices to emerging replacement materials such as III-V compounds but challenges still remain, especially with regard to metrology and surface chemistry at such small feature sizes. This article summarises and critically assesses developments over the last number of years regarding the application of gas and solution phase techniques to dope silicon-, germanium- and III-V-based materials and nanostructures to obtain shallow diffusion depths coupled with high carrier concentrations and abrupt junctions.