1,720,985 research outputs found
Assessment of the environmental impact of applications in federated clouds
Full text linkWhile in recent work the energy efficiency of cloud platforms has been emphasized and many approaches have been proposed to reduce the energy consumption in data centres, the evaluation of the environmental impact of applications running in cloud environments is still a research issue, as well as possible techniques to lower their environmental footprint. In the paper the approach taken in the ECO2Clouds project towards assessment of environmental impact of applications and the evaluation of its potential reduction based on adaptive services is illustrated and discussed, including in the discussion the evaluation of alternative possible uses of eco-metrics towards reducing the environmental impact of applications
Adaptive Computing for Agents and Dynamic Collaborative Environments
No full textThe "Adaptive Computing (and Agents) for Enhanced Collaboration" (ACEC) track currently enjoys its 11th year. ACEC focuses on the dynamic collaboration that occurs between networked systems as realized by agent-based or adaptive solutions or services. The purpose of this track is to bring together research in the fields of software agents and daptive computing, more broadly, as they relate to the challenges associated with efficient, effective collaboration. This report briefly discusses the content of the papers presented in the track by respective authors and collective knowledge derived from the underlying state-of-the-art
Adaptive Computing (and Agents) for Enhanced Collaboration (ACEC 2020)
No full textThe 18th edition of the 'Adaptive Computing (and Agents) for Enhanced Collaboration' (ACEC) track at WETICE 2020 focuses mostly on the area of adaptive agent-based techniques for the enterprise. The aim of the track is to bring together researches and practitioners from the fields of software agents and adaptive computing to present results and discuss innovative ideas. This report outlines the content of the papers accepted for presentation at the track
Adaptive computing and agent approaches for enhanced collaboration
No full textIn the 10th edition, the former "Agent-based Computing for Enterprise Collaboration (ACEC)" track has enhanced its offering at WETICE 2012 into the new title "Adaptive Computing (and Agents) for Enhanced Collaboration". This year, ACEC continues its focus on the areas of agent-based services and agent-based solutions for dynamic collaborations, but extends also to adaptive, nonagent based domains or collaboration beyond enterprise settings. The purpose of this track is to bring together research in the fields of software agents and adaptive computing, more broadly, as they relate to the challenges associated efficient, effective collaboration. This report briefly discusses the content of the papers presented in the track by respective authors. © 2012 IEEE
Adaptive Computing (and Agents) for Enhanced Collaboration (ACEC 2021)
No full textThe 19th edition of the 'Adaptive Computing (and Agents) for Enhanced Collaboration' (ACEC) track at WETICE 2021 targets the relevant topic of adaptation in relation to tools, methods and techniques for the enterprise. The aim of the track is to bring together researches and practitioners, working on agentbased software systems and/or adaptive computing, to present results and discuss innovative ideas. This report outlines the content of the papers accepted for presentation at the track
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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