Aberdeen University Ontology Reuse Stack

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Adult Learning Theory: Insights Relevant to the Appropriation of Ideas, Theories, Concepts and Models by Management Practitioners.

The core aim of the overall research project is to explore the appropriation of ideas, theories, concepts and models by individual management practitioners

Are North-South Technological Spillovers Substantial? : A Dynamic Panel Data Model Estimation

This paper argues that actual technological spillovers are not substantial in developing countries because of the absence of an absorptive capacity. We carry out a panel data analysis in an attempt to gain insight into the specific aspects that enable economies to benefit from the backlog of existing knowledge. Our findings indicate that low productivity effects of human capital coupled with weak or virtually inexistent systems of innovation are at the root of the observed ambiguity with regard to the spillovers gains that are expected to play a significant role in sparking growth.absorptive capacity, spillovers, developing countries, systems of innovation

Weak gravitational lensing: reducing the contamination by intrinsic alignments

Intrinsic alignments of galaxies can mimic to an extent the effects of shear caused by weak gravitational lensing. Previous studies have shown that for shallow surveys with median redshifts z_m = 0.1, the intrinsic alignment dominates the lensing signal. For deep surveys with z_m = 1, intrinsic alignments are believed to be a significant contaminant of the lensing signal, preventing high-precision measurements of the matter power spectrum. In this paper we show how distance information, either spectroscopic or photometric redshifts, can be used to down-weight nearby pairs in an optimised way, to reduce the errors in the shear signal arising from intrinsic alignments. Provided a conservatively large intrinsic alignment is assumed, the optimised weights will essentially remove all traces of contamination. For the Sloan spectroscopic galaxy sample, residual shot noise continues to render it unsuitable for weak lensing studies. However, a dramatic improvement for the slightly deeper Sloan photometric survey is found, whereby the intrinsic contribution, at angular scales greater than 1 arcminute, is reduced from about 80 times the lensing signal to a 10% effect. For deeper surveys such as the COMBO-17 survey with z_m = 0.6, the optimisation reduces the error from a largely systematic 220% error at small angular scales to a much smaller and largely statistical error of only 17% of the expected lensing signal. We therefore propose that future weak lensing surveys be accompanied by the acquisition of photometric redshifts, in order to remove fully the unknown intrinsic alignment errors from weak lensing detections.Comment: 10 pages, 6 figures, MNRAS accepted. Minor changes to match accepted version. RCS and ODT predictions are modifie

Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach

We examine counterfactual explanations for explaining the decisions made by model-based AI systems. The counterfactual approach we consider defines an explanation as a set of the system's data inputs that causally drives the decision (i.e., changing the inputs in the set changes the decision) and is irreducible (i.e., changing any subset of the inputs does not change the decision). We (1) demonstrate how this framework may be used to provide explanations for decisions made by general, data-driven AI systems that may incorporate features with arbitrary data types and multiple predictive models, and (2) propose a heuristic procedure to find the most useful explanations depending on the context. We then contrast counterfactual explanations with methods that explain model predictions by weighting features according to their importance (e.g., SHAP, LIME) and present two fundamental reasons why we should carefully consider whether importance-weight explanations are well-suited to explain system decisions. Specifically, we show that (i) features that have a large importance weight for a model prediction may not affect the corresponding decision, and (ii) importance weights are insufficient to communicate whether and how features influence decisions. We demonstrate this with several concise examples and three detailed case studies that compare the counterfactual approach with SHAP to illustrate various conditions under which counterfactual explanations explain data-driven decisions better than importance weights

The WiggleZ Dark Energy Survey: the selection function and z=0.6 galaxy power spectrum

We report one of the most accurate measurements of the three-dimensional large-scale galaxy power spectrum achieved to date, using 56,159 redshifts of bright emission-line galaxies at effective redshift z=0.6 from the WiggleZ Dark Energy Survey at the Anglo-Australian Telescope. We describe in detail how we construct the survey selection function allowing for the varying target completeness and redshift completeness. We measure the total power with an accuracy of approximately 5% in wavenumber bands of dk=0.01 h/Mpc. A model power spectrum including non-linear corrections, combined with a linear galaxy bias factor and a simple model for redshift-space distortions, provides a good fit to our data for scales k < 0.4 h/Mpc. The large-scale shape of the power spectrum is consistent with the best-fitting matter and baryon densities determined by observations of the Cosmic Microwave Background radiation. By splitting the power spectrum measurement as a function of tangential and radial wavenumbers we delineate the characteristic imprint of peculiar velocities. We use these to determine the growth rate of structure as a function of redshift in the range 0.4 < z < 0.8, including a data point at z=0.78 with an accuracy of 20%. Our growth rate measurements are a close match to the self-consistent prediction of the LCDM model. The WiggleZ Survey data will allow a wide range of investigations into the cosmological model, cosmic expansion and growth history, topology of cosmic structure, and Gaussianity of the initial conditions. Our calculation of the survey selection function will be released at a future date via our website wigglez.swin.edu.au.Comment: 21 pages, 22 figures, accepted for publication in MNRA

Customer-engineer relationship management for converged ICT service companies

Thanks to the advent of converged communications services (often referred to as ‘triple play’), the next generation Service Engineer will need radically different skills, processes and tools from today’s counterpart. Why? in order to meet the challenges of installing and maintaining services based on multi-vendor software and hardware components in an IP-based network environment. The converged services environment is likely to be ‘smart’ and support flexible and dynamic interoperability between appliances and computing devices. These radical changes in the working environment will inevitably force managers to rethink the role of Service Engineers in relation to customer relationship management. This paper aims to identify requirements for an information system to support converged communications service engineers with regard to customer-engineer relationship management. Furthermore, an architecture for such a system is proposed and how it meets these requirements is discussed

Information Aggregation with Costly Information and Random Ordering: Experimental Evidence

The cost of information is an often ignored factor in economic situations although the information acquisition behavior of the decision makers has a crucial influence on the outcome. In this experiment, we study an information aggregation process in which participants decide in a random sequence. Participants observe predecessors decisions and can acquire additional private information at a fixed price. We analyze participants information acquisition behavior and updating procedures. About one half of the individuals act rationally, whereas the other participants systematically overestimate the private signal value. This leads to excessive signal acquisitions and reduced conformity.