A compact model for multiterminal bipolar devices used in smart power applications

1998 ◽  
Vol 45 (9) ◽  
pp. 2037-2046 ◽  
Author(s):  
N. Speciale ◽  
A. Leone ◽  
V. Graziano ◽  
G. Privitera
2004 ◽  
Vol 35 (7) ◽  
pp. 591-594 ◽  
Author(s):  
P.M. Igic ◽  
M.S. Towers ◽  
P.A. Mawby

2019 ◽  
pp. 123-128 ◽  
Author(s):  
Maksim V. Demchenko ◽  
Rostislav O. Ruchkin ◽  
Eugenia P. Simaeva

The article substantiates the expediency of improving the legal support for the introduction and use of energy-efficient lighting equipment, as well as smart networks (Smart Grid), taking into account the ongoing digitalization of the Russian economy and electric power industry. The goal of scientific research is formulated, which is to develop practical recommendations on optimization of the public relations legal regulation in the digital power engineering sector. The research methodology is represented by the interaction of the legal and sociological aspects of the scientific methods system. The current regulatory and legal basis for the transformation of digital electricity relations has been determined. The need to modernize the system of the new technologies introduction legal regulation for generation, storage, transmission of energy, intelligent networks, including a riskbased management model, is established. A set of standardsetting measures was proposed to transform the legal regulation of public relations in the field of energyefficient lighting equipment with the aim of creating and effectively operating a single digital environment, both at the Federal and regional levels. A priority is set for the development of “smart” power grids and highly efficient power equipment in the constituent entities of the Russian Federation through a set of legal, economic (financial), edu cational measures.


2010 ◽  
Vol E93-C (8) ◽  
pp. 1349-1358
Author(s):  
Kenta YAMADA ◽  
Toshiyuki SYO ◽  
Hisao YOSHIMURA ◽  
Masaru ITO ◽  
Tatsuya KUNIKIYO ◽  
...  
Keyword(s):  

2020 ◽  
Vol 2020 (14) ◽  
pp. 378-1-378-7
Author(s):  
Tyler Nuanes ◽  
Matt Elsey ◽  
Radek Grzeszczuk ◽  
John Paul Shen

We present a high-quality sky segmentation model for depth refinement and investigate residual architecture performance to inform optimally shrinking the network. We describe a model that runs in near real-time on mobile device, present a new, highquality dataset, and detail a unique weighing to trade off false positives and false negatives in binary classifiers. We show how the optimizations improve bokeh rendering by correcting stereo depth misprediction in sky regions. We detail techniques used to preserve edges, reject false positives, and ensure generalization to the diversity of sky scenes. Finally, we present a compact model and compare performance of four popular residual architectures (ShuffleNet, MobileNetV2, Resnet-101, and Resnet-34-like) at constant computational cost.


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