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1. Communication about value creation: understanding and articulating the resources and relationships used by a business – what the Framework refers to as "capitals" – that are critical to the creation of value over time.
Hybridization, in the context of evolutionary optimization framework, refers to developing new algorithms by synergistically combining the composite benefits of global exploration and local exploitation capabilities of different ancestor algorithms.
A cloud framework refers to the aggregation of components like development tools, middleware and database services, needed for cloud computing, which aids in developing, deploying and managing cloud based applications strenuously, consequently making it an efficacious paradigm for massive scaling of dynamically allocated resources and their complex computing.
The educational production function framework refers to the relationship between inputs and outputs for a given production technology.
The Sendai Framework refers to the term technology 19 times, whereas its predecessor, the Hyogo Framework for Action 2005 2015, mentioned the term three times (UNITAR 2015).
In this paper, the analysis framework refers to the whole system, from raw data gathering, data reformat, data analysis, all the way to knowledge representation.
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Integrating theories, we developed an integrative conceptual framework, referred to as the CAr USE (or CAUSE) framework of cognitive and emotional antecedents of car use.
We treat with the Minimal Cost Multicommodity Flow Problem (MCMFP) in the setting of fuzzy sets, by forming a coherent algorithmic framework referred to as a fuzzy MCMFP.
In this paper, we propose an access control framework, referred to as the Policy Machine (PM) that fundamentally changes the way policy is expressed and enforced.
In this article, we design a novel probabilistic cluster structure ensemble framework, referred to as Gaussian mixture model based cluster structure ensemble framework (GMMSE), to identify the most representative cluster structure from the dataset.
The objective of this study is to investigate the concept of VQ in the setting of fuzzy sets by forming a coherent algorithmic framework referred to as a fuzzy VQ (FVQ).
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