A modified flood severity assessment for enhanced decision support: application to the Boscastle flash flood of 2004

A modified flash flood severity assessment is presented, based on scoring a set of factors according to their potential for generating extreme catchment-scale flooding. Improvements are made to the index through incorporation of parameter uncertainties, managing data absence, and clearer graphical communication. The motive for proposing these changes is to better inform flood managers during the development of a flash flood that may require an emergency response. This modified decision-support system is demonstrated for the Boscastle flood of 2004 and other historical floods in the United Kingdom. For Boscastle, the extreme nature of the flood is underestimated, which is likely to be due to the lack of sophistication in weighting flood parameters. However, the proposed amendments are able to rapidly reflect the reliability of a catchment severity rating, which may further enhance this technique as a decision-support tool alongside radar observations of localized storms

Fuzzy-based Propagation of Prior Knowledge to Improve Large-Scale Image Analysis Pipelines

Many automatically analyzable scientific questions are well-posed and offer a variety of information about the expected outcome a priori. Although often being neglected, this prior knowledge can be systematically exploited to make automated analysis operations sensitive to a desired phenomenon or to evaluate extracted content with respect to this prior knowledge. For instance, the performance of processing operators can be greatly enhanced by a more focused detection strategy and the direct information about the ambiguity inherent in the extracted data. We present a new concept for the estimation and propagation of uncertainty involved in image analysis operators. This allows using simple processing operators that are suitable for analyzing large-scale 3D+t microscopy images without compromising the result quality. On the foundation of fuzzy set theory, we transform available prior knowledge into a mathematical representation and extensively use it enhance the result quality of various processing operators. All presented concepts are illustrated on a typical bioimage analysis pipeline comprised of seed point detection, segmentation, multiview fusion and tracking. Furthermore, the functionality of the proposed approach is validated on a comprehensive simulated 3D+t benchmark data set that mimics embryonic development and on large-scale light-sheet microscopy data of a zebrafish embryo. The general concept introduced in this contribution represents a new approach to efficiently exploit prior knowledge to improve the result quality of image analysis pipelines. Especially, the automated analysis of terabyte-scale microscopy data will benefit from sophisticated and efficient algorithms that enable a quantitative and fast readout. The generality of the concept, however, makes it also applicable to practically any other field with processing strategies that are arranged as linear pipelines.Comment: 39 pages, 12 figure

Flight techniques for the measurement of stability derivatives and aircraft response

A method of obtaining aircraft frequency-response from transient response data by Fourier analysis is currently being investigated. This report describes progress that has been made between the commencement of the contract (1st December, 1964) and the time of writing (October, 1965). The dynamic response characteristics of a Hawker Siddeley Dore' aircraft are being determined from flight measurements using the Fourier method of analysis. At present attention is centred on the longitudinal response as the short-period mode of the aircraft is well damped and should be defined by a simple transfer function. The aircraft transient responses to various pilot-applied control inputs are recorded and the Fourier analysis of these transients is being carried out on a Ferranti Pegasus digital computer. Three development flights have been completed to date, and some preliminary results have been obtained, although the detailed analysis of the flight data is awaiting the incorporation of the instrumentation calibration into the computer programme. This last procedure will speed up the analysis of future data

A Model for Analysing the Collective Dynamic Behaviour and Characterising the Exploitation of Population-Based Algorithms

Several previous studies have focused on modelling and analysing the collective dynamic behaviour of population-based algorithms. However, an empirical approach for identifying and characterising such a behaviour is surprisingly lacking. In this paper, we present a new model to capture this collective behaviour, and to extract and quantify features associated with it. The proposed model studies the topological distribution of an algorithm's activity from both a genotypic and a phenotypic perspective, and represents population dynamics using multiple levels of abstraction. The model can have different instantiations. Here it has been implemented using a modified version of self-organising maps. These are used to represent and track the population motion in the fitness landscape as the algorithm operates on solving a problem. Based on this model, we developed a set of features that characterise the population's collective dynamic behaviour. By analysing them and revealing their dependency on fitness distributions, we were then able to define an indicator of the exploitation behaviour of an algorithm. This is an entropy-based measure that assesses the dependency on fitness distributions of different features of population dynamics. To test the proposed measures, evolutionary algorithms with different crossover operators, selection pressure levels and population handling techniques have been examined, which lead populations to exhibit a wide range of exploitation-exploration behaviours. </jats:p

Application of automatic vehicle location in law enforcement: An introductory planning guide

A set of planning guidelines for the application of automatic vehicle location (AVL) to law enforcement is presented. Some essential characteristics and applications of AVL are outlined; systems in the operational or planning phases are discussed. Requirements analysis, system concept design, implementation planning, and performance and cost modeling are described and demonstrated with numerous examples. A detailed description of a typical law enforcement AVL system, and a list of vendor sources are given in appendixes