Systemic approaches to incident analysis in aviation: comparison of STAMP, Agent-Based Modelling and Institutions

The rapid development and increasing complexity of modern socio-technical systems suggest an urgent need for systemic safety analysis approaches because traditional linear models cannot cope with this complexity. In the aviation safety literature, among systemic accident and incident analysis methods, Systems Theoretic Accident Modelling and Processes (STAMP) and Agent-based modelling (ABM) are the most cited ones. STAMP is a qualitative analysis approach known for its thoroughness and comprehensiveness. Computational ABM approach is a formal quantitative method which proved to be suitable for modelling complex flexible systems. In addition, from a legal point of view, formal systemic institutional modelling potentially provides an interesting contribution to accident and incident analysis. The current work compares three systemic modelling approaches: STAMP, ABM and institutional modelling applied to a case study in an aviation domain

Merging Top-View Lidar Data With Street-View SFM Data To Enhance Urban Flood Simulation

Top-view data obtainedfrom LiDAR systemshas long been used as topographic-input data for urban flood modelling applications. This high-resolution input data has considerable potential to improve urban flood modelling predictions with more detail. However, the difficulty of employing top-view data is that it may create some missing urban features because this type ofdata cannot represent anyurban features,which are hiddenunderneath other objects. These hidden featuresmay play a substantial part in diverting floodwater flowing through,especially in complex urban areas. The recent advances in Photogrammetry and Computer Vision techniques offer an opportunity to create high-resolution topographic data. By using a consumer digital camera,2Ddigital photoscan betaken from different viewpoints. The so-called Structure from Motion (SfM) techniquecan usethese overlappingphotos and reconstruct theminto3D point-cloud data with a high level of accuracy and resolution,usinga cost effective approach. In this work, we create street-view SfM point-cloud data obtained from street viewpoints. We also introduce a new multi-view approach by merging top-view LiDAR data withstreet-view SfM data. This new multi-view data can be used as topographic input data for a coupled 1D-2D model. When applyingsuch newdata, the flood simulation results can highlight some flood propagations much better than using the traditional top-view LiDAR data. Therefore, it has the potential toenhance the multi-view approach into practicable flood-modelling applications for the present and future urbanizing areas

A Cellular Automata Model with Probability Infection and Spatial Dispersion

In this article, we have proposed an epidemic model by using probability cellular automata theory. The essential mathematical features are analyzed with the help of stability theory. We have given an alternative modelling approach for the spatiotemporal system which is more realistic and satisfactory from the practical point of view. A discrete and spatiotemporal approach are shown by using cellular automata theory. It is interesting to note that both size of the endemic equilibrium and density of the individual increase with the increasing of the neighborhood size and infection rate, but the infections decrease with the increasing of the recovery rate. The stability of the system around the positive interior equilibrium have been shown by using suitable Lyapunov function. Finally experimental data simulation for SARS disease in China and a brief discussion conclude the paper

Dynamic FOV visible light communications receiver for dense optical networks

This study explores how the field-of-view (FOV) of a visible light communications (VLCs) receiver can be manipulated to realise the best signal-to-noise ratio (SNR) while supporting device mobility and optimal access point (AP) selection. The authors propose a dynamic FOV receiver that changes its aperture according to receiver velocity, location, and device orientation. The D-FOV technique is evaluated through modelling, analysis, and experimentation in an indoor environment comprised of 15 VLC APs. The proposed approach is also realised as an algorithm that is studied through analysis and simulation. The results of the study indicate the efficacy of the approach including a 3X increase in predicted SNR over static FOV approaches based on measured received signal strength in the testbed. Additionally, the collected data reveal that D-FOV increases effectiveness in the presence of noise. Finally, the study describes the tradeoffs among the number of VLC sources, FOV, user device velocity, and SNR as a performance metric.Accepted manuscrip

Time and position distributions in large volume spherical scintillation detectors

Large spherical scintillation detectors are playing an increasingly important role in experimental neutrino physics studies. From the instrumental point of view the primary signal response of these set-ups is constituted by the time and amplitude of the anode pulses delivered by each individual phototube following a particle interaction in the scintillator. In this work, under some approximate assumptions, we derive a number of analytical formulas able to give a fairly accurate description of the most important timing features of these detectors, intended to complement the more complete Monte Carlo studies normally used for a full modelling approach. The paper is completed with a mathematical description of the event position distributions which can be inferred, through some inference algorithm, starting from the primary time measures of the photomultiplier tubes.Comment: 29 pages, 20 figures, accepted for publication on Nucl. Instr. and Meth.

Kinetic parameter estimation from TGA: Optimal design of TGA experiments

This work presents a general methodology to determine kinetic models of solid thermal decomposition with thermogravimetric analysis (TGA) instruments. The goal is to determine a simple and robust kinetic model for a given solid with the minimum of TGA experiments. From this last point of view, this work can be seen as an attempt to find the optimal design of TGA experiments for kinetic modelling. Two computation tools were developed. The first is a nonlinear parameter estimation procedure for identifying parameters in nonlinear dynamical models. The second tool computes the thermogravimetric experiment (here, the programmed temperature profile applied to the thermobalance) required in order to identify the best kinetic parameters, i.e. parameters with a higher statistical reliability. The combination of the two tools can be integrated in an iterative approach generally called sequential strategy. The application concerns the thermal degradation of cardboard in a Setaram TGA instrument and the results that are presented demonstrate the improvements in the kinetic parameter estimation process