A cognitive model-based approach for autonomic fault management in OpenFlow networks

2013 ◽  
Vol 23 (6) ◽  
pp. 383-401 ◽  
Author(s):  
Sungsu Kim ◽  
Joon-Myung Kang ◽  
Sin-seok Seo ◽  
James Won-Ki Hong
2008 ◽  
pp. 199-218 ◽  
Author(s):  
Sasanka Prabhala ◽  
Subhashini Ganapathy ◽  
S. Narayanan ◽  
Jennie J. Gallimore ◽  
Raymond R. Hill

With increased interest in the overall employment of pilotless vehicles functioning in the ground, air, and marine domains for both defense and commercial applications, the need for high-fidelity simulation models for testing and validating the operational concepts associated with these systems is very high. This chapter presents a model-based approach that we adopted for investigating the critical issues in the command and control of remotely operated vehicles (ROVs) through an interactive model-based architecture. The domain of ROVs is highly dynamic and complex in nature. Hence, a proper understanding of the simulation tools, underlying system algorithms, and user needs is critical to realize advanced simulation system concepts. Our resulting simulation architecture integrates proven design concepts such as the model-view-controller paradigm, distributed computing, Web-based simulations, cognitive model-based high-fidelity interfaces and object-based modeling methods.


2019 ◽  
Vol 29 (5) ◽  
pp. 640-656 ◽  
Author(s):  
Mark Povich

Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function. In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function. In this article, I show how Model-Based Cognitive Neuroscience (MBCN) epitomizes the integrative mechanistic perspective and concentrates the most revolutionary elements of the cognitive neuroscience revolution. I also show how the prominent subset account of functional realization supports the integrative mechanistic perspective I take on MBCN and use it to clarify the intralevel and interlevel components of integration.


2012 ◽  
Vol 39 (5) ◽  
pp. 4972-4977 ◽  
Author(s):  
Jiyun Li ◽  
Yilei Li

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