Home Energy Simulation for Non-Intrusive Load Monitoring Applications

Author(s):  
Krishnan Srinivasarengan ◽  
Y. G. Goutam ◽  
M. Girish Chandra
2021 ◽  
Vol 18 ◽  
pp. 100145
Author(s):  
Giovanni Bucci ◽  
Fabrizio Ciancetta ◽  
Edoardo Fiorucci ◽  
Simone Mari ◽  
Andrea Fioravanti

Author(s):  
Yongchao Yu ◽  
Aravind K. Mikkilineni ◽  
Stephen M. Killough ◽  
Teja Kuruganti ◽  
Pooran C. Joshi ◽  
...  

Measurement ◽  
2016 ◽  
Vol 89 ◽  
pp. 197-203 ◽  
Author(s):  
Shervin Tashakori ◽  
Amin Baghalian ◽  
Muhammet Unal ◽  
Hadi Fekrmandi ◽  
volkan y şenyürek ◽  
...  

2010 ◽  
Vol 1 ◽  
pp. 64-68
Author(s):  
Volker Kreidler ◽  
Holger Daum
Keyword(s):  

2019 ◽  
Author(s):  
Xiaohui Wang ◽  
Zhaoxi Sun

<p>Correct calculation of the variation of free energy upon base flipping is crucial in understanding the dynamics of DNA systems. The free energy landscape along the flipping pathway gives the thermodynamic stability and the flexibility of base-paired states. Although numerous free energy simulations are performed in the base flipping cases, no theoretically rigorous nonequilibrium techniques are devised and employed to investigate the thermodynamics of base flipping. In the current work, we report a general nonequilibrium stratification scheme for efficient calculation of the free energy landscape of base flipping in DNA duplex. We carefully monitor the convergence behavior of the equilibrium sampling based free energy simulation and the nonequilibrium stratification and determine the empirical length of time blocks required for converged sampling. Comparison between the performances of equilibrium umbrella sampling and nonequilibrium stratification is given. The results show that nonequilibrium free energy simulation is able to give similar accuracy and efficiency compared with the equilibrium enhanced sampling technique in the base flipping cases. We further test a convergence criterion we previously proposed and it comes out that the convergence behavior determined by this criterion agrees with those given by the time-invariant behavior of PMF and the nonlinear dependence of standard deviation on the sample size. </p>


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