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Extended Generativity Theory on Digital Platforms [PDF]
The assumption that generativity engenders unbounded growth has acquired an almost taken-for-granted position in information systems and management literature. Against this premise, we examine the relationship between generativity and user base growth in
Daniel Fürstenau +2 more
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Generativity, sustainable development and green consumer behaviour [PDF]
Conserving the planet for the next generation has come to be an essential component of sustainable development, with “future generations” being the term most frequently included when citing definitions of sustainable development.
Chris Shiel +2 more
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Explicit Generalization as Generalization of Semantic Generalization
2015 3rd International Conference on Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligence, 2015The semantic generalization was proposed. This generalization makes it possible for a kind of class to have attributes by considering the semantics of the attributes of the subclasses even if there is no common attribute in the subclasses. The attributes generalized can be specified by users rather than automatically decided.
Teruhisa Hochin, Hiroki Nomiya
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Generalized Beta-Generated Distributions [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Carol Alexander +3 more
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The nature, prevalence and correlates of generativity among men in middle career
Multiple methods were used to explore the character, contexts, and correlates of generativity among 41 men aged 45-55. Generativity in the role of worker was unrelated to generativity in men's roles as father, citizen and 'leisurite'.
Clark, Michael, Arnold, John
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Measuring Generativity in Older Adults
Erikson already emphasized the importance of remaining generative in old age. Current instruments designed to measure generativity, however, were developed to be used with middle-aged adults.
Angela Schoklitsch, Urs Baumann
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A Generalization of the Least General Generalization
1994Abstract In this chapter, we present a polynomial time algorithm, called a k-minimal multiple generalization (k-mmg) algorithm, where k ≥ 1, and its application to inductive learning problems. The algorithm is a natural extension of the least general generalization algorithm developed by Plotkin and Reynolds.
Hiroki Arimura +3 more
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ACM SIGMETRICS Performance Evaluation Review, 2020
Large-scale systems are everywhere, and deciding how to dispatch an arriving job to one of the many available servers is crucial to obtaining low response time. One common scalable dispatching paradigm is the "power of d," in which the dispatcher queries d servers at random and assigns the job to a server based only on the state of the queried servers.
Jazeem Abdul Jaleel +3 more
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Large-scale systems are everywhere, and deciding how to dispatch an arriving job to one of the many available servers is crucial to obtaining low response time. One common scalable dispatching paradigm is the "power of d," in which the dispatcher queries d servers at random and assigns the job to a server based only on the state of the queried servers.
Jazeem Abdul Jaleel +3 more
openaire +1 more source

