Extended Isotope Programming Model for Pervasive Computing Environment

Junbin, Zhang; Qi, Yong; Hou, Di; Xi, Min

doi:10.1109/iccit.2008.181

Cited by 2 publications

(1 citation statement)

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“…The 18 O isotope is treated in many scientific articles by presenting its direct applications [9,[25][26][27]. In previous papers [28][29][30][31][32], some solutions for modeling and controlling the separation process for the 18 O isotope production are presented. By analyzing these solutions, in most of the cases, some simplified linearized models with lumped parameters are proposed for the processes associated to the separation columns, which operate independently (they are not included in the separation cascades).…”

Section: Introductionmentioning

confidence: 99%

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

et al. 2021

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In the paper, the comparison between the efficiency of using artificial intelligence methods and the efficiency of using classical methods in modelling the industrial processes is made, considering as a case study the separation process of the 18O isotope. Firstly, the behavior of the considered isotopic separation process is learned using neural networks. The comparison between the efficiency of these methods is highlighted by the simulations of the process model, using the mentioned modelling techniques. In this context, the final part of the paper presents the proposed model being simulated in different scenarios that can occur in practice, thus resulting in some interesting interpretations and conclusions. The paper proves the feasibility of using artificial intelligence methods for industrial processes modeling; the obtained models being intended for use in designing automatic control systems.

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Section: Introductionmentioning

confidence: 99%

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

et al. 2021

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Typed context awareness Ambient Calculus for pervasive applications

2015

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The idea of pervasive computing is that information processing will become part of everyday life, and will be available everywhere, making computing so natural to the point of being invisible in the ambient. An important concept that arises with pervasive computing is context awareness . Context is any information that can be used to characterize an entity. Based on contextual information, applications can dynamically adapt themselves to the environments in which they operate. The Calculus of Context-aware Ambients (CCA) is an untyped formal language used to describe mobile and context-aware pervasive applications. The CCA extends the Ambient Calculus by providing new features, such as context-guarded action and process abstraction, allowing to model contexts and context-aware computations. In this work, we define a type system for the CCA, called CCA T , with the focus in the communication between processes and in the correct use of process abstraction and contexts, extending previous works on the definition of type systems for mobile computing. Moreover, we prove that the proposed type system has the subject reduction property (or type preservation). We also model a hospital scenario using CCA T to demonstrate the use of the proposed type system.

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Extended Isotope Programming Model for Pervasive Computing Environment

Cited by 2 publications

References 16 publications

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

AI versus Classic Methods in Modelling Isotopic Separation Processes: Efficiency Comparison

Typed context awareness Ambient Calculus for pervasive applications

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