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Huang et al. [71], Kikuchi et al. [51], Wu and Zhao [72], Liu et al. [69], Cerroni, and Callegati [74], Xu et al. [52], Deshpande and Keahey [82] proposed a performance aware models whereas Deshpande et al. [75] highlight the eviction time issue, Zhang et al. [81] highlight memory and storage transfer over WAN network issue.
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Here, we present the R package camb: Chemically Aware Model Builder, which aims to address the current lack of an R framework comprising the four steps mentioned above.
The objective of the research presented in this paper is to derive a Quality of Service aware model of ubiquitous learning services based on typical learning schemes.
Towards building a systematic methodology of algorithm design for applications of networked sensor systems, we formally define two link-wise communication models, the Collision Free Model (CFM) and the Collision Aware Model (CAM).
Adopting the adaptive agent model, an AMDA paradigm, we put forward a security–aware model-driven mechanism by using an extension of the role-based access control (RBAC) model.
The Requirements and Design Modelling Plug-in provides developers with tools to aid in is based on the energy aware modelling of an application, while the Code Optimiser Plug-in provides offline functionality to profiler an application's energy consumption during development.
They provide maximum-likelihood based learning method to learn influence parameters in these topic-aware models.
They provide learning methods to learn influence parameters in the topic-aware models from real-world data.
The content-aware models use one set of coefficients per content (see rows "H DD B to E and "SD" A to E in Tables 4 and 5).
We provide empirical results based on simulations for comparing HMM-As with symmetric and other asymmetry-aware models, showing that modeling more general asymmetries can be very effective.
By definition, the content-blind models use the same set of coefficients for all contents while the content-aware models have one set of coefficients per content (see Tables 4 and 5).
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