Asynchronous Interaction Framework for Verilog Simulation Virtualization on Node.js

Author(s):  
Daeun Heo ◽  
Daejin Park
Author(s):  
Jiajun Tang ◽  
Jin Xia ◽  
Xinzhi Mu ◽  
Bo Pang ◽  
Cewu Lu

2020 ◽  
Vol 68 ◽  
pp. 817-850
Author(s):  
Wojciech Jamroga ◽  
Wojciech Penczek ◽  
Teofil Sidoruk ◽  
Piotr Dembiński ◽  
Antoni Mazurkiewicz

We propose a general semantics for strategic abilities of agents in asynchronous systems, with and without perfect information. Based on the semantics, we show some general complexity results for verification of strategic abilities in asynchronous interaction. More importantly, we develop a methodology for partial order reduction in verification of agents with imperfect information. We show that the reduction preserves an important subset of strategic properties, with as well as without the fairness assumption. We also demonstrate the effectiveness of the reduction on a number of benchmarks. Interestingly, the reduction does not work for strategic abilities under perfect information.


Author(s):  
Alexandros Chavdoulas ◽  
Maria Pavlis Korres ◽  
Piera Leftheriotou

Designers, developers, and educators in an online course, where the risk of learners feeling isolated is of greater concern, should consider including learning activities that engage students with content and with each other in order to promote multiple ways of interaction and communication between learners and higher learners' engagement in the course. Interaction could be developed both in synchronous and asynchronous mode, in a direct or/and indirect (vicarious) way within the e-learning process. This chapter focuses on the development of asynchronous interaction between learners in a MOOC on personal development, provided in 2016 via a popular educational platform and how interaction affected the learning outcomes. The ways that learners asynchronously interact with each other through forum and peer review are identified and research proved that learners interact in a direct and indirect way and that the development of interaction returns multiple benefits to the learning process and outcome.


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