Collaborative Planning in an Uncollaborative World

The purpose of this paper is to expose the concept of collaborative planning to the reality of planning, thereby assessing its efficacy for informing and explaining what planners 'really' do and can do. In this systematic appraisal, collaborative planning is disaggregated into four elements that can enlighten such conceptual frameworks: ontology, epistemology, ideology and methodology. These four lenses help delimit and clarify collaborative planning's strengths and weaknesses. The conceptual debate is related to an empirical investigation of planning processes, ranging from region-wide to local and from statutory to visionary in an arena where special care has been invested in participatory deliberation processes. The final analysis provides a systematic gauge of collaborative planning in light of the extensive empirical evidence, deploying the four conceptual dimensions introduced in part one. This exposes a range of problems not only with the concept itself but also regarding its affinity with the uncollaborative world within which it has to operate. The former shed light on those aspects where collaborative planning as a conceptual tool for practitioners needs to be renovated, while the latter highlight inconsistencies in a political framework that struggles to accommodate both global competitiveness and local democratic collaboration.

UKCP: A Collaborative network of cerebral palsy registers in the United Kingdom

Cerebral palsy (CP) is a relatively rare condition with enormous social and financial impact. Information about CP is not routinely collected in the United Kingdom. We have pooled non-identifiable data from the five currently active UK CP registers to form the UKCP database: birth years 1960–1997. This article describes the rationale behind this collaboration and the creation of the database. Data about 6910 children with CP are currently held. The mean annual prevalence rate was 2.0 per 1000 live births for birth years 1986–1996. Where type is known, 91 per cent have spastic CP. Where data are available, nearly one-third of children have severely impaired lower limb function, and nearly a quarter have severely impaired upper limb function. As well as describing the range and complexity of motor and associated impairments, the pooled data from the UKCP database provide a platform for studies of aetiology, long-term outcomes, participation and service needs. The UKCP database is an important national resource for the surveillance of CP and the study of its epidemiology in the United Kingdom.

Feasibility of online collaborative voltage stability control of power systems

This paper presents the results of feasibility study of a novel concept of power system on-line collaborative voltage stability control. The proposal of the on-line collaboration between power system controllers is to enhance their overall performance and efficiency to cope with the increasing operational uncertainty of modern power systems. In the paper, the framework of proposed on-line collaborative voltage stability control is firstly presented, which is based on the deployment of multi-agent systems and real-time communication for on-line collaborative control. Then two of the most important issues in implementing the proposed on-line collaborative voltage stability control are addressed: (1) Error-tolerant communication protocol for fast information exchange among multiple intelligent agents; (2) Deployment of multi-agent systems by using graph theory to implement power system post-emergency control. In the paper, the proposed on-line collaborative voltage stability control is tested in the example 10-machine 39-node New England power system. Results of feasibility study from simulation are given considering the low-probability power system cascading faults.

Knowledge-based risk assessment under uncertainty in engineering projects

In this paper we describe how an evidential-reasoner can be used as a component of risk assessment of engineering projects using a direct way of reasoning. Guan & Bell (1991) introduced this method by using the mass functions to express rule strengths. Mass functions are also used to express data strengths. The data and rule strengths are combined to get a mass distribution for each rule; i.e., the first half of our reasoning process. Then we combine the prior mass and the evidence from the different rules; i.e., the second half of the reasoning process. Finally, belief intervals are calculated to help in identifying the risks. We apply our evidential-reasoner on an engineering project and the results demonstrate the feasibility and applicability of this system in this environment.

Risk assessment of E-Commerce projects using evidential reasoning

The purpose of this study is to develop a decision making system to evaluate the risks in E-Commerce (EC) projects. Competitive software businesses have the critical task of assessing the risk in the software system development life cycle. This can be conducted on the basis of conventional probabilities, but limited appropriate information is available and so a complete set of probabilities is not available. In such problems, where the analysis is highly subjective and related to vague, incomplete, uncertain or inexact information, the Dempster-Shafer (DS) theory of evidence offers a potential advantage. We use a direct way of reasoning in a single step (i.e., extended DS theory) to develop a decision making system to evaluate the risk in EC projects. This consists of five stages 1) establishing knowledge base and setting rule strengths, 2) collecting evidence and data, 3) determining evidence and rule strength to a mass distribution for each rule; i.e., the first half of a single step reasoning process, 4) combining prior mass and different rules; i.e., the second half of the single step reasoning process, 5) finally, evaluating the belief interval for the best support decision of EC project. We test the system by using potential risk factors associated with EC development and the results indicate that the system is promising way of assisting an EC project manager in identifying potential risk factors and the corresponding project risks.