scholarly journals Trade‐off between cost and accuracy in large‐scale surface water dynamic modeling

2017 ◽  
Vol 53 (6) ◽  
pp. 4942-4955 ◽  
Author(s):  
Augusto Getirana ◽  
Christa Peters‐Lidard ◽  
Matthew Rodell ◽  
Paul D. Bates
Keyword(s):  
Surface Water ◽  
Dynamic Modeling ◽  
Large Scale ◽  
Trade Off ◽  
Scale Surface

Managing the impacts of mining on Ghana’s water resources from a legal perspective

2018 ◽  
Vol 1 (3) ◽  
pp. 156-165 ◽  
Author(s):  
Nasirudeen Abdul Fatawu
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Environmental Protection Agency ◽  
Large Scale ◽  
Small Scale ◽  
Mining Activities ◽  
Protection Agency ◽  
Environmental Laws ◽  
Mining Areas ◽  
Legal Perspective

Recent floods in Ghana are largely blamed on mining activities. Not only are lives lost through these floods, farms andproperties are destroyed as a result. Water resources are diverted, polluted and impounded upon by both large-scale minersand small-scale miners. Although these activities are largely blamed on behavioural attitudes that need to be changed, thereare legal dimensions that should be addressed as well. Coincidentally, a great proportion of the water resources of Ghana arewithin these mining areas thus the continual pollution of these surface water sources is a serious threat to the environmentand the development of the country as a whole. The environmental laws need to be oriented properly with adequate sanctionsto tackle the impacts mining has on water resources. The Environmental Impact Assessment (EIA) procedure needs to bestreamlined and undertaken by the Environmental Protection Agency (EPA) and not the company itself.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

Control-oriented low-speed dynamic modeling and trade-off analysis of air-breathing aerospace vehicles

2019 ◽  
Vol 20 (12) ◽  
pp. 893-907
Author(s):  
Hai-dong Shen ◽  
Rui Cao ◽  
Yan-bin Liu ◽  
Fei-teng Jin ◽  
Yu-ping Lu
Keyword(s):  
Dynamic Modeling ◽  
Aerospace Vehicles ◽  
Trade Off ◽  
Air Breathing ◽  
Low Speed

Large-scale preparation of a 3D patchy surface with dissimilar dendritic amphiphiles

Soft Matter ◽  
2018 ◽  
Vol 14 (6) ◽  
pp. 1043-1049 ◽  
Author(s):  
Yanyan Feng ◽  
Yujia Wan ◽  
Ming Jin ◽  
Decheng Wan
Keyword(s):  
Large Scale ◽  
Large Scale Preparation ◽  
Porous Monolith ◽  
Scale Preparation ◽  
Surface Decoration ◽  
Scale Surface

We show here the first example of the large-scale surface decoration of a macroscopic and porous monolith with dissimilar micropatches.

scholarly journals Modeling of Thermal Effects in Semiconductor Structures

VLSI Design ◽  
1998 ◽  
Vol 8 (1-4) ◽  
pp. 53-58
Author(s):  
Christopher M. Snowden
Keyword(s):  
Thermal Effects ◽  
Large Scale ◽  
High Electron Mobility Transistors ◽  
Thermal Modelling ◽  
High Electron ◽  
Temperature Model ◽  
Active Devices ◽  
Electron Mobility Transistors ◽  
Fully Coupled ◽  
Scale Surface

A fully coupled electro-thermal hydrodynamic model is described which is suitable for modelling active devices. The model is applied to the non-isothermal simulation of pseudomorphic high electron mobility transistors (pHEMTs). A large-scale surface temperature model is described which allows thermal modelling of semiconductor devices and monolithic circuits. An example of the application of thermal modelling to monolithic circuit characterization is given.

Sign in / Sign up

Export Citation Format

Share Document