Evaluation of Setup Procedures on Mobile Devices Based on Users’ Initial Experience

Users’ initial perceptions of their competence are key motivational factors for further use. However, initial tasks on a mobile operating system (OS) require setup procedures, which are currently largely inconsistent, do not provide users with clear, visible and immediate feedback on their actions, and require significant adjustment time for first-time users. This paper reports on a study with ten users, carried out to better understand how both prior experience and initial interaction with two touchscreen mobile interfaces (Apple iOS and Google Android) affected setup task performance and motivation. The results show that the reactions to setup on mobile interfaces appear to be partially dependent on which device was experienced first. Initial experience with lower-complexity devices improves performance on higher-complexity devices, but not vice versa. Based on these results, the paper proposes six guidelines for designers to design more intuitive and motivating user interfaces (UI) for setup procedures. The preliminary results indicate that these guidelines can contribute to the design of more inclusive mobile platforms and further work to validate these findings is proposed.

Annealing behaviors of long-wavelength InAs/GaAs quantum dots with different growth procedures by metalorganic chemical vapor deposition

The effects of annealing on the optical properties of InAs/GaAs quantum dots (QDs) grown under different conditions by metalorganic chemical vapor deposition (MOCVD) are studied. A lower QD growth rate leads to an earlier and faster decrease of QD photoluminescence (PL) intensity with increasing annealing temperature. which is proposed to be related to the increased QD two-dimensional (2D)-three-dimensional (3D) transition critical layer thickness at low QD growth rate. High-quality GaAs cap layers grown at high temperature and a low deposition rate are shown to decrease the blueshift of the QDs' emission wavelength significantly during in-situ I h annealing experiments, which is important for the fabrication of long-wavelength InAs/GaAs QD lasers by MOCVD technique. (C) 2009 Elsevier B.V. All rights reserved.

Justified Generalization: Acquiring Procedures from Examples

This thesis describes an implemented system called NODDY for acquiring procedures from examples presented by a teacher. Acquiring procedures form examples involves several different generalization tasks. Generalization is an underconstrained task, and the main issue of machine learning is how to deal with this underconstraint. The thesis presents two principles for constraining generalization on which NODDY is based. The first principle is to exploit domain based constraints. NODDY demonstrated how such constraints can be used both to reduce the space of possible generalizations to manageable size, and how to generate negative examples out of positive examples to further constrain the generalization. The second principle is to avoid spurious generalizations by requiring justification before adopting a generalization. NODDY demonstrates several different ways of justifying a generalization and proposes a way of ordering and searching a space of candidate generalizations based on how much evidence would be required to justify each generalization. Acquiring procedures also involves three types of constructive generalizations: inferring loops (a kind of group), inferring complex relations and state variables, and inferring predicates. NODDY demonstrates three constructive generalization methods for these kinds of generalization.

Theatre/Archaeology: Disciplinary Dialogues

Pearson, Mike, Shanks, Michael, Theatre/Archaeology (London: Routledge, 2001), pp.xviii+215 RAE2008

OpenBU: Institutional Repository Procedures Manual

(adapted from the DSpace Procedures Manual developed by Kalamazoo College Digital Archive)

Regularized iterative and non-iterative procedures for object restoration from experimental data

A regularized algorithm for the recovery of band-limited signals from noisy data is described. The regularization is characterized by a single parameter. Iterative and non-iterative implementations of the algorithm are shown to have useful properties, the former offering the advantage of flexibility and the latter a potential for rapid data processing. Comparative results, using experimental data obtained in laser anemometry studies with a photon correlator, are presented both with and without regularization. © 1983 Taylor & Francis Ltd.

Regularized iterative and noniterative procedures for object restoration in the presence of noise :an error analysis

An analysis is carried out, using the prolate spheroidal wave functions, of certain regularized iterative and noniterative methods previously proposed for the achievement of object restoration (or, equivalently, spectral extrapolation) from noisy image data. The ill-posedness inherent in the problem is treated by means of a regularization parameter, and the analysis shows explicitly how the deleterious effects of the noise are then contained. The error in the object estimate is also assessed, and it is shown that the optimal choice for the regularization parameter depends on the signal-to-noise ratio. Numerical examples are used to demonstrate the performance of both unregularized and regularized procedures and also to show how, in the unregularized case, artefacts can be generated from pure noise. Finally, the relative error in the estimate is calculated as a function of the degree of superresolution demanded for reconstruction problems characterized by low space–bandwidth products.

Discretisation procedures for multi-physics phenomena

Procedures are described for solving the equations governing a multi-physics process. Finite volume techniques are used to discretise, using the same unstructured mesh, the equations of fluid flow, heat transfer with solidification, and solid deformation. These discretised equations are then solved in an integrated manner. The computational mechanics environment, PHYSICA, which facilitates the building of multi-physics models, is described. Comparisons between model predictions and experimental data are presented for the casting of metal components.