43,115 research outputs found

    A survey of machine learning techniques applied to self organizing cellular networks

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    In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

    Innovation processes and industrial districts

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    In this survey, we examine the operations of innovation processes within industrial districts by exploring the ways in which differentiation, specialization, and integration affect the generation, diffusion, and use of new knowledge in such districts. We begin with an analysis of the importance of the division of labour and then investigate the effects of social embeddedness on innovation. We also consider the effect of forms of organization within industrial districts at various stages of product and process life, and we examine the negative aspects of embeddedness for innovation. We conclude with a discussion of the possible consequences of new information and communications technologies on innovation in industrial districts

    Knowledge Integration and Diffusion: Measures and Mapping of Diversity and Coherence

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    I present a framework based on the concepts of diversity and coherence for the analysis of knowledge integration and diffusion. Visualisations that help understand insights gained are also introduced. The key novelty offered by this framework compared to previous approaches is the inclusion of cognitive distance (or proximity) between the categories that characterise the body of knowledge under study. I briefly discuss the different methods to map the cognitive dimension

    New Prospects for Organizational Democracy? How the Joint Pursuit of Social and Financial Goals Challenges Traditional Organizational Designs

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    Some interesting exceptions notwithstanding, the traditional logic of economic efficiency has long favored hierarchical forms of organization and disfavored democracy in business. What does the balance of arguments look like, however, when values besides efficient revenue production are brought into the picture? The question is not hypothetical: In recent years, an ever increasing number of corporations have developed and adopted socially responsible behaviors, thereby hybridizing aspects of corporate businesses and social organizations. We argue that the joint pursuit of financial and social objectives warrants significant rethinking of organizational democracy’s merits compared both to hierarchy and to non-democratic alternatives to hierarchy. In making this argument, we draw on an extensive literature review to document the relative lack of substantive discussion of organizational democracy since 1960. And we draw lessons from political theory, suggesting that the success of political democracy in integrating diverse values offers some grounds for asserting parallel virtues in the business case

    Complex Systems Science: Dreams of Universality, Reality of Interdisciplinarity

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    Using a large database (~ 215 000 records) of relevant articles, we empirically study the "complex systems" field and its claims to find universal principles applying to systems in general. The study of references shared by the papers allows us to obtain a global point of view on the structure of this highly interdisciplinary field. We show that its overall coherence does not arise from a universal theory but instead from computational techniques and fruitful adaptations of the idea of self-organization to specific systems. We also find that communication between different disciplines goes through specific "trading zones", ie sub-communities that create an interface around specific tools (a DNA microchip) or concepts (a network).Comment: Journal of the American Society for Information Science and Technology (2012) 10.1002/asi.2264
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