18,315 research outputs found

    Intelligent protocol adaptation for enhanced medical e-collaboration

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    Copyright @ 2003 AAAIDistributed multimedia e-health applications have a set specific requirements which must be taken into account effective use is to be made of the limited resources provided by public telecommunication networks. Moreover, there an architectural gap between the provision of network-level Quality of Service (QoS) and user requirements of e-health applications. In this paper, we address the problem bridging this gap from a multi-attribute decision-making perspective in the context of a remote collaborative environment for back pain treatment. We propose intelligent mechanism that integrates user- related requirements with the more technical characterisation Quality of Service. We show how our framework is capable of suggesting appropriately tailored transmission protocols, by incorporating user requirements in the remote delivery e-health solutions

    CBR and MBR techniques: review for an application in the emergencies domain

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    The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

    A gap in competencies or in capabilities?: the role of regional universities in developing scientific and technological skills in Campania

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    A gap in competencies or in capabilities?: the role of regional universities in developing scientific and technological skills in Campania The paper assesses the role of universities in resolving the STEM (Science, Technology, Engineering and Mathematics) skills gap in the Campania region of Southern Italy. The results are shown to hinge on a doubled supply/demand model, involving a first upstream stage (logically if not chronologically) of derived demands for and supplies of STEM-based skill development within universities, and a second downstream stage of the usage of these skills in industrial firms. The main objective of this work is to re-examine the role of conventional ‘knowledge capital’ arguments for the role of universities in development processes in catching-up regions of the EU – i.e. human capital and R&D capital, or what will be identified here as ‘competencies’ – as against what we refer to as ‘capabilities’ arguments, reflected here in better ways in which universities might adapt to the actual needs of industry for highly skilled workers and research outcomes. The results suggest that the STEM skills gap is not clearly a deficiency just in capabilities, but more so in the links between capabilities and competencies. Moreover, the STEM universities are trying to feed the interaction with industry, however it is still left mostly to the personal relationships of the professors or their administrative counterparts, e.g. head of the T&T office, and/or to placement. Key words: Derived demand and supply, STEM subjects, Mezzogiorno region, skills gap, competencies and capabilities.

    Iterative preprocessing of event logs

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    Agents for educational games and simulations

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    This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

    Intelligent systems in manufacturing: current developments and future prospects

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    Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

    On the role of pre and post-processing in environmental data mining

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    The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed
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