47 research outputs found

    Intelligent modeling of e-Government initiatives in Greece

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    Over the last two years Greece has employed agile ICT solutions to reduce the administrative burden in front-office G2B transactions. This research supplements historic analysis with fuzzy cognitive maps to offer a multi-dimensional coupling of eGovernment initiatives with digital maturity assessment capabilities and a strategy alignment evaluation framework. This “intelligent x-ray” confirms that front-office technology is important in reducing administrative burden. The digital bypass of bureaucracy seems to be an effective start for Greece. However, this strategy can only serve as a short-term tactical choice. The “intelligent x-ray” provides executive level quantification and traceable reasoning to show that excessive emphasis on front- office technology will soon fail to support a strong eGovernment maturity. Organizational efficiency, interoperability, regulatory simplifications, and change management must also act as important objectives. Only then will ICT deliver its full potential, and the eGovernment maturity will improve significantly even with moderate ICT investments

    Multi-agent knowledge integration mechanism using particle swarm optimization

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    This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.Unstructured group decision-making is burdened with several central difficulties: unifying the knowledge of multiple experts in an unbiased manner and computational inefficiencies. In addition, a proper means of storing such unified knowledge for later use has not yet been established. Storage difficulties stem from of the integration of the logic underlying multiple experts' decision-making processes and the structured quantification of the impact of each opinion on the final product. To address these difficulties, this paper proposes a novel approach called the multiple agent-based knowledge integration mechanism (MAKIM), in which a fuzzy cognitive map (FCM) is used as a knowledge representation and storage vehicle. In this approach, we use particle swarm optimization (PSO) to adjust causal relationships and causality coefficients from the perspective of global optimization. Once an optimized FCM is constructed an agent based model (ABM) is applied to the inference of the FCM to solve real world problem. The final aggregate knowledge is stored in FCM form and is used to produce proper inference results for other target problems. To test the validity of our approach, we applied MAKIM to a real-world group decision-making problem, an IT project risk assessment, and found MAKIM to be statistically robust.Ministry of Education, Science and Technology (Korea

    A Dynamic Task Distribution and Engine Allocation Strategy for Distributed Execution of Logic Programs

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    Abstract. Distributed execution of logic programs on heterogeneous processors requires e cient task distribution and engine synchronization to exploit the potential for performance. This paper presents a task-driven scheduling technique to distribute tasks to engines e ectively. It consists of a dynamic hierarchy of distributed scheduling components able to adapt to program characteristics and the platform con guration and to control the considerable communication costs while exploiting good degrees of parallelism. It also incorporates an abort & failure mechanism to reduce speculative work and keep engines as busy as possible. Several experimental results illustrate the performance of the model.
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