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

Energy behaviour change model validation

This dataset includes psychological data (environmental values, success expectancy, perceived barriers for pro-environmental behaviour, general energy literacy) and electricity consumption data for 20 households in Exeter, UK. This dataset was created within the ENLITEN project funded by EPSRC (grant number EP/K002724/1)The conceptual model described in the paper, “A Cognitive Agent-Based Model for Energy Behaviour Change Interventions” (Mogles, N., Padget, J., Gabe-Thomas, E., Walker, I., Lee, J.) was implemented in the MATLAB environment. The file containing the code for running model simulations is called energy_beh_change_model.m and it was run using MATLAB version MATLAB_R2014b

Transdisciplinarity Within the Academic Engineering Literature

Despite increased discourse around transdisciplinary (TD) research, there is a perception it has received less attention within engineering. This is significant if, as generally accepted, TD increases the societal value of research. This paper benchmarks TD engineering research against the broader TD literature, addressing the question: How do the characteristics of the academic engineering TD literature compare to the TD academic literature in general? We analyse the chronology, journals, and text of papers referencing TD within their abstract and compare this to papers that fall within the engineering subject area. The conclusions find that TD research is limited generally, and within engineering specifically. Historically, TD research focuses on sustainability challenges, a persistent trend within the general literature. Within engineering research, the focus of TD is wider and addresses operational and “grand challenge” problems. TD remains poorly defined and future work should focus on clarifying meaning within the engineering discipline

Comparing Modelling Approaches in Aviation Safety Tibor BOSSE a a

Abstract. Within open socio-technical systems, the quality of the system as a whole crucially depends on the joint performance and interaction of the individual agents involved. A domain where the study of this regulation is particularly complex is the domain of Air Traffic Management (ATM). The current paper compares four of the more influential modelling approaches within ATM, namely Event Trees, FRAM, STAMP, and the agent-based approach LEADSTO. This is done by applying the four approaches to a case study on retrospective modelling of a runway incursion incident that occurred in 1995. Based on this comparison, the pros and cons of the different approaches are discussed

Intelligent Mobile Support for Therapy Adherence and Behavior Change

Mobile applications have proven to be a promising tool to support people in adhering to their health goals. Although coaching and reminder apps abound, few of them are based on established theories of behavior change. In the present work, a behavior change support system is presented that uses a computational model based on multiple psychological theories of behavior change. The system determines the user’s reason for non-adherence using a mobile phone app and an online lifestyle diary. The user automatically receives generated messages with persuasive, tailored content. The system was designed to support chronic patients with type 2 diabetes, HIV, and cardiovascular disease, but can be applied to many health and lifestyle domains. The main focus of this work is the development of the model and the underlying reasoning method. Furthermore, the implementation of the system and some preliminary results of its functioning will be discussed

An ambient intelligent system for improving therapy adherence of chronic patients

The amount of chronic diseases is increasing in Western societies due to the ageing of the population. The costs of constant personal supervising of chronic patients aimed at the improvement of therapy adherence are particularly high. Moreover, chronic disease therapy imposes a burden on everyday life of chronic patients and their psychological well-being as it requires strict regimen and self-control. In this context Ambient Intelligence techniques have an explicit potential in both reducing the medical costs in the health care sector and improving the well-being of chronic patients. Our approach is to adopt Ambient Persuasion technology to increase the therapy adherence of chronic patients. It will be realized by means of an adaptive agent-based system which uses cognitive models of patient's behaviour