Algorithms Applied to Global Optimisation – Visual Evaluation

Evaluation and assessment of various search and optimisation algorithms is subject of large research efforts. Particular interest of this study is global optimisation and presented approach is based on observation and visual evaluation of Real-Coded Genetic Algorithm, Particle Swarm Optimisation, Differential Evolution and Free Search, which are briefly described and used for experiments. 3D graphical views, generated by visualisation tool VOTASA, illustrate essential aspects of global search process such as divergence, convergence, dependence on initialisation and utilisation of accidental events. Discussion on potential benefits of visual analysis, supported with numerical results, which could be used for comparative assessment of other methods and directions for further research conclude presented study

Physical instrumental vetoes for gravitational-wave burst triggers

We present a robust strategy to \emph{veto} certain classes of instrumental glitches that appear at the output of interferometric gravitational-wave (GW) detectors.This veto method is `physical' in the sense that, in order to veto a burst trigger, we make use of our knowledge of the coupling of different detector subsystems to the main detector output. The main idea behind this method is that the noise in an instrumental channel X can be \emph{transferred} to the detector output (channel H) using the \emph{transfer function} from X to H, provided the noise coupling is \emph{linear} and the transfer function is \emph{unique}. If a non-stationarity in channel H is causally related to one in channel X, the two have to be consistent with the transfer function. We formulate two methods for testing the consistency between the burst triggers in channel X and channel H. One method makes use of the \emph{null-stream} constructed from channel H and the \emph{transferred} channel X, and the second involves cross-correlating the two. We demonstrate the efficiency of the veto by `injecting' instrumental glitches in the hardware of the GEO 600 detector. The \emph{veto safety} is demonstrated by performing GW-like hardware injections. We also show an example application of this method using 5 days of data from the fifth science run of GEO 600. The method is found to have very high veto efficiency with a very low accidental veto rate.Comment: Minor changes, To appear in Phys. Rev.

An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development

In this paper, we investigate model-driven engineering, reporting on an exploratory case-study conducted at a large automotive company. The study consisted of interviews with 20 engineers and managers working in different roles. We found that, in the context of a large organization, contextual forces dominate the cognitive issues of using model-driven technology. The four forces we identified that are likely independent of the particular abstractions chosen as the basis of software development are the need for diffing in software product lines, the needs for problem-specific languages and types, the need for live modeling in exploratory activities, and the need for point-to-point traceability between artifacts. We also identified triggers of accidental complexity, which we refer to as points of friction introduced by languages and tools. Examples of the friction points identified are insufficient support for model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe

Who Should Bear the Risk When Self-Driving Vehicles Crash?

The moral importance of liability to harm has so far been ignored in the lively debate about what self-driving vehicles should be programmed to do when an accident is inevitable. But liability matters a great deal to just distribution of risk of harm. While morality sometimes requires simply minimizing relevant harms, this is not so when one party is liable to harm in virtue of voluntarily engaging in activity that foreseeably creates a risky situation, while having reasonable alternatives. On plausible assumptions, merely choosing to use a self-driving vehicle typically gives rise to a degree of liability, so that such vehicles should be programmed to shift the risk from bystanders to users, other things being equal. Insofar vehicles cannot be programmed to take all the factors affecting liability into account, there is a pro tanto moral reason not to introduce them, or restrict their use