Exploring good practice knowledge transfer related to post tsunami housing re-construction in Sri Lanka

Sri Lanka was badly affected by the tsunami that occurred on 26th December 2004. The tsunami destroyed about two-thirds of the Sri Lankan coastline and affected more than 1,000,000 people. It does not only affected the lives of the community, but also had a devastating effect on their housing and livelihoods. The overall loss of 100,000 or more houses due to the tsunami proved to be a major challenge to the emergency response teams and disaster planners. Although several major disasters of varying magnitudes have occurred in the world, the body of knowledge related to post-disaster housing reconstruction and rehabilitation appears fragmented and poorly integrated. This paper attempts to fill this theoretical gap by focusing on the extent to which good practice knowledge transfer helps in overcoming this problem for more effective and efficient delivery of post-tsunami housing in Sri Lanka. The paper applied knowledge transfer principles within the context of the two housing reconstruction strategies employed in post-tsunami housing reconstruction in Sri Lanka; namely donor-driven housing and owner driven housing. The results of this study reveal that the knowledge transfer within this context cannot be simply copied and inserted from one context without any localisation. Therefore, the paper proposes a high-level abstraction of the core principles of community engagement through participatory techniques associated with appropriate capacity and capability building techniques that will enable the various stakeholders to create a new application to suit the appropriate context of the transfer destination (post-tsunami context in Sri Lanka)

Attentional capture by meaning: A multi-level modelling study

We present a computational study of attentional capture by meaning, based on Barnard et al's key-distractor attentional blink task. We highlight a sequence of models, from an abstract black-box to a structurally detailed white-box model. Each of these models reproduces the major findings from the key-distractor blink task. We argue that such multi-level modelling gives greater confidence in the theoretical position encapsulated by these models

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

Incident Analysis & Digital Forensics in SCADA and Industrial Control Systems

SCADA and industrial control systems have been traditionally isolated in physically protected environments. However, developments such as standardisation of data exchange protocols and increased use of IP, emerging wireless sensor networks and machine-to-machine communication mean that in the near future related threat vectors will require consideration too outside the scope of traditional SCADA security and incident response. In the light of the significance of SCADA for the resilience of critical infrastructures and the related targeted incidents against them (e.g. the development of stuxnet), cyber security and digital forensics emerge as priority areas. In this paper we focus on the latter, exploring the current capability of SCADA operators to analyse security incidents and develop situational awareness based on a robust digital evidence perspective. We look at the logging capabilities of a typical SCADA architecture and the analytical techniques and investigative tools that may help develop forensic readiness to the level of the current threat environment requirements. We also provide recommendations for data capture and retention