Results 141 to 150 of about 10,123,899 (424)

Ground-source heat pumps and underground thermal energy storage: energy for the future [PDF]

open access: yes, 2008
We need energy for space heating—but in most cases not where or when energy sources are available. Energy storage, which helps match energy supply and demand, has been practised for centuries, also in Norway.
Banks, D.   +4 more
core  

Thermal energy storage [PDF]

open access: yes
The general scope of study on thermal energy storage development includes: (1) survey and review possible concepts for storing thermal energy; (2) evaluate the potentials of the surveyed concepts for practical applications in the low and high ...
Grodzka, P. G., Picklesimer, E. A.
core   +1 more source

Note on the pumped storage potential of the Onslow-Manorburn depression, New Zealand [PDF]

open access: yes, 2005
The Onslow-Manorburn depression in the South Island of New Zealand has possibility for development as the upper reservoir of the world's largest pumped storage scheme, as measured by an energy storage capacity of 10,200 GWh of realisable potential energy.
Bardsley, W. Earl
core   +1 more source

Evaluation of the effect of metal stents on dose perturbation in the carbon beam irradiation field

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Propose Carbon ion therapy is indicated for cases in which stents have been inserted, such as bile ducts, but the effect of metal stents on carbon ion therapy is unclear. In this study, the dose perturbation of carbon ion therapy caused by metallic bile duct stents was evaluated by dosimetry. Materials and methods Five different types of metal
Yuya Miyasaka   +8 more
wiley   +1 more source

Storage Sizing and Placement through Operational and Uncertainty-Aware Simulations

open access: yes, 2013
As the penetration level of transmission-scale time-intermittent renewable generation resources increases, control of flexible resources will become important to mitigating the fluctuations due to these new renewable resources.
Backhaus, Scott   +2 more
core   +1 more source

A comparative analysis of deep learning architectures with data augmentation and multichannel input for locoregional breast cancer radiotherapy

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Studies on deep learning dose prediction increasingly focus on 3D models with multiple input channels and data augmentation, which increases the training time and thus also the environmental burden and hampers the ease of re‐training. Here we compare 2D and 3D U‐Net models with clinical accepted plans to evaluate the appropriateness of
Rosalie Klarenberg   +2 more
wiley   +1 more source

Scalable Planning for Energy Storage in Energy and Reserve Markets [PDF]

open access: yesarXiv, 2016
Energy storage can facilitate the integration of renewable energy resources by providing arbitrage and ancillary services. Jointly optimizing energy and ancillary services in a centralized electricity market reduces the system's operating cost and enhances the profitability of energy storage systems.
arxiv  

An extension to the OVH concept for knowledge‐based dose volume histogram prediction in lung tumor volumetric‐modulated arc therapy

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Volumetric‐modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs‐at‐risk (OARs). Particularly in the case of lung tumors, deciding whether it is possible or worth spending more time on further improvements of a treatment
Johann Brand   +4 more
wiley   +1 more source

Recursive Binary Neural Network Learning Model with 2.28b/Weight Storage Requirement [PDF]

open access: yesarXiv, 2017
This paper presents a storage-efficient learning model titled Recursive Binary Neural Networks for sensing devices having a limited amount of on-chip data storage such as < 100's kilo-Bytes. The main idea of the proposed model is to recursively recycle data storage of synaptic weights (parameters) during training.
arxiv  

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