scholarly journals Dynamic reconfiguration of frequency-specific cortical coactivation patterns during psychedelic and anesthetized states induced by ketamine

NeuroImage ◽  
2022 ◽  
pp. 118891
Author(s):  
Duan Li ◽  
Phillip E. Vlisides ◽  
George A. Mashour
MIS Quarterly ◽  
2014 ◽  
Vol 38 (3) ◽  
pp. 831-848 ◽  
Author(s):  
Melissa Mazmanian ◽  
◽  
Marisa Cohn ◽  
Paul Dourish ◽  
◽  
...  

2008 ◽  
Author(s):  
Joseph Loyall ◽  
Praveen Sharma ◽  
Matthew Gillen ◽  
Jianming Ye ◽  
Richard Shantz

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 830
Author(s):  
Filipe F. C. Silva ◽  
Pedro M. S. Carvalho ◽  
Luís A. F. M. Ferreira

The dissemination of low-carbon technologies, such as urban photovoltaic distributed generation, imposes new challenges to the operation of distribution grids. Distributed generation may introduce significant net-load asymmetries between feeders in the course of the day, resulting in higher losses. The dynamic reconfiguration of the grid could mitigate daily losses and be used to minimize or defer the need for network reinforcement. Yet, dynamic reconfiguration has to be carried out in near real-time in order to make use of the most updated load and generation forecast, this way maximizing operational benefits. Given the need to quickly find and update reconfiguration decisions, the computational complexity of the underlying optimal scheduling problem is studied in this paper. The problem is formulated and the impact of sub-optimal solutions is illustrated using a real medium-voltage distribution grid operated under a heavy generation scenario. The complexity of the scheduling problem is discussed to conclude that its optimal solution is infeasible in practical terms if relying upon classical computing. Quantum computing is finally proposed as a way to handle this kind of problem in the future.


Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1139
Author(s):  
Mykola Beshley ◽  
Natalia Kryvinska ◽  
Halyna Beshley ◽  
Oleg Yaremko ◽  
Julia Pyrih

A virtual router model with a static and dynamic resource reconfiguration for future internet networking was developed. This technique allows us to create efficient virtual devices with optimal parameters (queue length, queue overflow management discipline, number of serving devices, mode of serving devices) to ensure the required level of quality of service (QoS). An analytical model of a network device with virtual routers is proposed. By means of the mentioned mathematical representation, it is possible to determine the main parameters of the virtual queue system, which are based on the first in, first out (FIFO) algorithm, in order to analyze the efficiency of network resources utilization, as well as to determine the parameters of QoS flows, for a given intensity of packets arrival at the input interface of the network element. In order to research the guaranteed level of QoS in future telecommunications networks, a simulation model of a packet router with resource virtualization was developed. This model will allow designers to choose the optimal parameters of network equipment for the organization of virtual routers, which, in contrast to the existing principle of service, will provide the necessary quality of service provision to end users in the future network. It is shown that the use of standard static network device virtualization technology is not able to fully provide a guaranteed level of QoS to all present flows in the network by the criterion of minimum delay. An approach for dynamic reconfiguration of network device resources for virtual routers has been proposed, which allows more flexible resource management at certain points in time depending on the input load. Based on the results of the study, it is shown that the dynamic virtualization of the network device provides a guaranteed level of QoS for all transmitted flows. Thus, the obtained results confirm the feasibility of using dynamic reconfiguration of network device resources to improve the quality of service for end users.


2011 ◽  
Vol 40 (7) ◽  
pp. 502-508
Author(s):  
V. A. Shaltyrev ◽  
K. A. Shaltyrev ◽  
I. I. Shagurin

Sign in / Sign up

Export Citation Format

Share Document