Resilience Assignment Framework using System Dynamics and Fuzzy Logic.

This paper is concerned with the development of a conceptual framework that measures the resilience of the transport network under climate change related events. However, the conceptual framework could be adapted and quantified to suit each disruption’s unique impacts. The proposed resilience framework evaluates the changes in transport network performance in multi-stage processes; pre, during and after the disruption. The framework will be of use to decision makers in understanding the dynamic nature of resilience under various events. Furthermore, it could be used as an evaluation tool to gauge transport network performance and highlight weaknesses in the network. In this paper, the system dynamics approach and fuzzy logic theory are integrated and employed to study three characteristics of network resilience. The proposed methodology has been selected to overcome two dominant problems in transport modelling, namely complexity and uncertainty. The system dynamics approach is intended to overcome the double counting effect of extreme events on various resilience characteristics because of its ability to model the feedback process and time delay. On the other hand, fuzzy logic is used to model the relationships among different variables that are difficult to express in numerical form such as redundancy and mobility

CAST – City analysis simulation tool: an integrated model of land use, population, transport and economics

The paper reports on research into city modelling based on principles of Science of Complexity. It focuses on integration of major processes in cities, such as economics, land use, transport and population movement. This is achieved using an extended Cellular Automata model, which allows cells to form networks, and operate on individual financial budgets. There are 22 cell types with individual processes in them. The formation of networks is based on supply and demand mechanisms for products, skills, accommodation, and services. Demand for transport is obtained as an emergent property of the system resulting from the network connectivity and relevant economic mechanisms. Population movement is a consequence of mechanisms in the housing and skill markets. Income and expenditure of cells are self-regulated through market mechanisms and changing patterns of land use are a consequence of collective interaction of all mechanisms in the model, which are integrated through emergence

Using the Internet to improve university education: Problem-oriented web-based learning and the MUNICS environment

Up to this point, university education has largely remained unaffected by the developments of novel approaches to web-based learning. The paper presents a principled approach to the design of problem-oriented, web-based learning at the university level. The principles include providing authentic contexts with multimedia, supporting collaborative knowledge construction, making thinking visible with dynamic visualisation, quick access to content resources via Information and Communication Technologies (ICT), and flexible support by tele-tutoring. These principles are used in the Munich Net-based Learning In Computer Science (MUNICS) learning environment, which is designed to support students of computer science to apply their factual knowledge from the lectures to complex real-world problems. For example, students can model the knowledge management in an educational organisation with a graphical simulation tool. Some more general findings from a formative evaluation study with the MUNICS prototype are reported and discussed. E.g., the students' ignorance of the additional content resources is discussed in the light of the well-known finding of insufficient use of help systems in software applicationsBislang wurden neuere Ansätze zum web-basierten Lernen in nur geringem Maße zur Verbesserung des Universitätsstudiums genutzt. Es werden theoretisch begründete Prinzipien für die Gestaltung problemorientierter, web-basierter Lernumgebungen an der Universität formuliert. Zu diesen Prinzipien gehören die Nutzung von Multimedia-Technologien für die Realisierung authentischer Problemkontexte, die Unterstützung der gemeinsamen Wissenskonstruktion, die dynamische Visualisierung, der schnelle Zugang zu weiterführenden Wissensressourcen mit Hilfe von Informations- und Kommunikationstechnologien sowie die flexible Unterstützung durch Teletutoring. Diese Prinzipien wurden bei der Gestaltung der MUNICS Lernumgebung umgesetzt. MUNICS soll Studierende der Informatik bei der Wissensanwendung im Kontext komplexer praktischer Problemstellungen unterstützen. So können die Studierenden u.a. das Wissensmanagement in einer Bildungsorganisation mit Hilfe eines graphischen Simulationswerkzeugs modellieren. Es werden Ergebnisse einer formativen Evaluationsstudie berichtet und diskutiert. Beispielsweise wird die in der Studie festgestellte Ignoranz der Studierenden gegenüber den weiterführenden Wissensressourcen vor dem Hintergrund des häufig berichteten Befunds der unzureichenden Nutzung von Hilfesystemen beleuchte

Structural constraints in complex networks

We present a link rewiring mechanism to produce surrogates of a network where both the degree distribution and the rich--club connectivity are preserved. We consider three real networks, the AS--Internet, the protein interaction and the scientific collaboration. We show that for a given degree distribution, the rich--club connectivity is sensitive to the degree--degree correlation, and on the other hand the degree--degree correlation is constrained by the rich--club connectivity. In particular, in the case of the Internet, the assortative coefficient is always negative and a minor change in its value can reverse the network's rich--club structure completely; while fixing the degree distribution and the rich--club connectivity restricts the assortative coefficient to such a narrow range, that a reasonable model of the Internet can be produced by considering mainly the degree distribution and the rich--club connectivity. We also comment on the suitability of using the maximal random network as a null model to assess the rich--club connectivity in real networks.Comment: To appear in New Journal of Physics (www.njp.org