7,458 research outputs found
CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties
The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels. This article presents an overview of the CONTREX European project, its main innovative technology (extension of a model based design approach, functional and extra-functional analysis with executable models and run-time management) and the final results of three industrial use-cases from different domain (avionics, automotive and telecommunication).The work leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2011 under grant agreement no. 611146
CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties
The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. The paper presents the CONTREX European project and its preliminary results. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels
CHORUS Deliverable 3.3: Vision Document - Intermediate version
The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action).
This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events.
The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search.
A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009
Dynamic Approach to Competitive Intelligence: Case Studies of Large-Scale Swiss Telecom Firms
The research aim is to understand how the competitive intelligence (CI) process in large-scale Swiss
telecom companies contributes to management decision-making. Studying CI activities of the Swiss
large-scale telecom firms (Swisscom, Sunrise, Orange/Salt, Cablecom) in a dynamic European
context offers useful insight into the critical challenges that service firms now face when developing
intelligence in disruptive market contexts where aggressive competitive behaviour is evident.
In considering CI theory, this study has reviewed perspectives drawn from research on the CI
process, studies on knowledge management and work on systems thinking. In extending the
predominant modular view of CI to include elements of systems thinking, this study has added to our
academic understanding of CI at firm level. An Integrative CI Activities framework was developed
that enables a more holistic perspective of CI to be adopted, taking account of operational,
organisational and strategic perspectives. A diagram representing the range of CI analysis
methodologies has also been generated, that differentiates between internal/external orientation and
static/dynamic forms of CI analysis. Such frameworks can be used by CI researchers in other market
contexts.
The methodology for this study drew on a pragmatist philosophy, using a case study strategy that
adopted mixed methods in data collection, including semi-structured depth interviews with top CI
Analysts in each firm. Findings have shown differences in the scope of CI Activities that link to
stages of CI development (developing, developed) and variation between headquarters-centred and
firm-centred approaches to CI planning and implementation. The adoption of query based, flexible
analysis approaches in firm-centred settings differ from more structured CI analysis techniques in
headquarters-based firms. Evidence from this study suggests that networked communication, strong
feedback mechanisms and the adoption of more flexible CI analyst roles link to more effective CI
processes and to greater potential for direct CI contribution to decision-making.
Key contributions emerge through the three lenses of analysis adopted (operational, organisational
and strategic); in terms of operational CI processes, the study identifies a complex integrated system
at work in firms that implement CI effectively. In studying the link between organisational structure
and CI analysis, the study has mapped organisational support patterns and how they shape the CI
process at firm level. With respect to the strategic lens, following a detailed worked study of
predictive analysis in one case firm, findings have identified adaptiveness in CI design as essential to
address disruptive market change. Managerial consideration include a need for a) greater flexibility in
CI implementation at firm level to adapt to turbulent markets, b) acknowledgement of the importance
of the CI analyst role further and c) more dynamic CI content to be generated by CI analysts
AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems
The evolution towards 6G architecture promises a transformative shift in
communication networks, with artificial intelligence (AI) playing a pivotal
role. This paper delves deep into the seamless integration of Large Language
Models (LLMs) and Generalized Pretrained Transformers (GPT) within 6G systems.
Their ability to grasp intent, strategize, and execute intricate commands will
be pivotal in redefining network functionalities and interactions. Central to
this is the AI Interconnect framework, intricately woven to facilitate
AI-centric operations within the network. Building on the continuously evolving
current state-of-the-art, we present a new architectural perspective for the
upcoming generation of mobile networks. Here, LLMs and GPTs will
collaboratively take center stage alongside traditional pre-generative AI and
machine learning (ML) algorithms. This union promises a novel confluence of the
old and new, melding tried-and-tested methods with transformative AI
technologies. Along with providing a conceptual overview of this evolution, we
delve into the nuances of practical applications arising from such an
integration. Through this paper, we envisage a symbiotic integration where AI
becomes the cornerstone of the next-generation communication paradigm, offering
insights into the structural and functional facets of an AI-native 6G network
A SLR on Customer Dropout Prediction
Dropout prediction is a problem that is being addressed with machine learning algorithms;
thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict
the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as
which features should be selected and how to measure accuracy while considering whether the features are
appropriate according to the business context in which they are employed. To solve these questions, the
goal of this paper is to develop a systematic literature review to evaluate the development of existing studies
and to predict the dropout rate in contractual settings using machine learning to identify current trends and
research opportunities. The results of this study identify trends in the use of machine learning algorithms
in different business areas and in the adoption of machine learning algorithms, including which metrics are
being adopted and what features are being applied. Finally, some research opportunities and gaps that could
be explored in future research are presented.info:eu-repo/semantics/publishedVersio
A SLR on Customer Dropout Prediction
Dropout prediction is a problem that is being addressed with machine learning algorithms;
thus, appropriate approaches to address the dropout rate are needed. The selection of an algorithm to predict
the dropout rate is only one problem to be addressed. Other aspects should also be considered, such as
which features should be selected and how to measure accuracy while considering whether the features are
appropriate according to the business context in which they are employed. To solve these questions, the
goal of this paper is to develop a systematic literature review to evaluate the development of existing studies
and to predict the dropout rate in contractual settings using machine learning to identify current trends and
research opportunities. The results of this study identify trends in the use of machine learning algorithms
in different business areas and in the adoption of machine learning algorithms, including which metrics are
being adopted and what features are being applied. Finally, some research opportunities and gaps that could
be explored in future research are presented.info:eu-repo/semantics/publishedVersio
- …