scholarly journals Variability reduction through optimal combination of wind/wave resources – An Irish case study

Energy ◽  
2010 ◽  
Vol 35 (1) ◽  
pp. 314-325 ◽  
Author(s):  
Francesco Fusco ◽  
Gary Nolan ◽  
John V. Ringwood
2021 ◽  
pp. 110720
Author(s):  
D.M. Rakshit ◽  
DM Gowda ◽  
Anthony James Robinson ◽  
Aimee Byrne
Keyword(s):  

2021 ◽  
Vol 13 (7) ◽  
pp. 1367
Author(s):  
Yuanzhi Cai ◽  
Hong Huang ◽  
Kaiyang Wang ◽  
Cheng Zhang ◽  
Lei Fan ◽  
...  

Over the last decade, a 3D reconstruction technique has been developed to present the latest as-is information for various objects and build the city information models. Meanwhile, deep learning based approaches are employed to add semantic information to the models. Studies have proved that the accuracy of the model could be improved by combining multiple data channels (e.g., XYZ, Intensity, D, and RGB). Nevertheless, the redundant data channels in large-scale datasets may cause high computation cost and time during data processing. Few researchers have addressed the question of which combination of channels is optimal in terms of overall accuracy (OA) and mean intersection over union (mIoU). Therefore, a framework is proposed to explore an efficient data fusion approach for semantic segmentation by selecting an optimal combination of data channels. In the framework, a total of 13 channel combinations are investigated to pre-process data and the encoder-to-decoder structure is utilized for network permutations. A case study is carried out to investigate the efficiency of the proposed approach by adopting a city-level benchmark dataset and applying nine networks. It is found that the combination of IRGB channels provide the best OA performance, while IRGBD channels provide the best mIoU performance.


2019 ◽  
Vol 52 (25) ◽  
pp. 415-420 ◽  
Author(s):  
Orlagh Costello ◽  
Mary Doyle Kent ◽  
Peter Kopacek
Keyword(s):  

2020 ◽  
Vol 6 (4) ◽  
pp. 115
Author(s):  
Marta Macias Aragonés ◽  
Gloria de la Viña Nieto ◽  
María Nieto Fajardo ◽  
David Páez Rodríguez ◽  
James Gaffey ◽  
...  

Regional bioeconomy development is directly linked to the availability and access to bioresources. Therefore, it is necessary to trigger opportunities for information and communications technologies (ICTs), the Internet of things (IoT) and Industry 4.0 solutions to increase the efficiency of high potential value biomass supply chains, improving this way the accessibility of bioresources. This study aims to present the results achieved through the development of Digital Innovation Hubs (DIHs) as a tool able to boost biomass valorisation, reshaping regional bioeconomy. The objective was to shape these DIHs and assess how stakeholders could be engaged and benefit from such initiatives. This has been attained through the design and implementation of DIHs in two case-study regions, Andalusia (Spain) and south-east Ireland (Ireland). The approaches and results for stakeholders’ engagement, barrier mitigation, DIH structure and activities are presented. So far, more than 100 stakeholders have been engaged, more than 50 business opportunities have been promoted and a set of support services and events have been carried out. Main lessons learned are (1) about the relevance of understanding the needs of stakeholders, (2) impact is bigger when relevant regional industries (rather than academia/technology providers) discuss the technologies they have integrated and how these have improved efficiency or added value to their processes, and (3) about the importance of the communication plan and a well-formed DIH service definition.


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