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Found 9759 publications. Showing page 96 of 391:

Publication  
Year  
Category

Radiative forcing by black carbon in the Arctic.

Quinn, P.K.; Stohl, A.; Baklanov, A.; Flanner, M.G.; Herber, A.; Kupiainen, K.; Law, K.S.; Schmale, J.; Sharma, S.; Vestreng, V.; von Salzen, K.

2014

QUILT: Measurement and model results for the arctic winter stratosphere 2001/2002.

Arlander, D.W.; Tørnkvist, K.K.; Roozendael, M. Van, Hendrick, F.; Wittrock, F.; Richter, A.; Goutail, F.; Lefevre, F.; Pfeilsticker, K.; Wagner, T.; Chipperfield, M.; Roscoe, H.K.; Denis, L.; Gil, M.; Puentedura, O.; Landgraf, J.; Laat, J. de, Ravegnani, F.; Petritoli, A.; Johnston, P.V.; Kreher, K.

2002

Query-driven Qualitative Constraint Acquisition

Belaid, Mohamed-Bachir; Belmecheri, Nassim; Gotlieb, Arnaud; Lazaar, Nadjib; Spieker, Helge

Many planning, scheduling or multi-dimensional packing problems involve the design of subtle logical combinations of temporal or spatial constraints. Recently, we introduced GEQCA-I, which stands for Generic Qualitative Constraint Acquisition, as a new active constraint acquisition method for learning qualitative constraints using qualitative queries. In this paper, we revise and extend GEQCA-I to GEQCA-II with a new type of query, universal query, for qualitative constraint acquisition, with a deeper query-driven acquisition algorithm. Our extended experimental evaluation shows the efficiency and usefulness of the concept of universal query in learning randomly-generated qualitative networks, including both temporal networks based on Allen’s algebra and spatial networks based on region connection calculus. We also show the effectiveness of GEQCA-II in learning the qualitative part of real scheduling problems.

2024

Quantitative imaging of volcanic plumes - results, needs, and future trends.

Platt, U.; Lübcke, P.; Kuhn, J.; Bobrowski, N.; Prata, F.; Burton, M.; Kern, C.

2015

Quantitative analysis of the 16-17 September 2013 resuspended ash event in Iceland.

Kylling, A.; Beckett, F.; Sigurdardottir, G.M.; von Loewis, S.; Witham, C.

2015

Quantitative Analysis of Microplastics including Tire Wear Particles in Northern Atlantic Air with Pyrolysis-GC/MS

Gossmann, Isabel; Herzke, Dorte; Held, Andreas; Schulz, Janina; Nikiforov, Vladimir; Georgi, Christoph; Evangeliou, Nikolaos; Eckhardt, Sabine; Gerdts, Gunnar; Wurl, Oliver; Scholz-Böttcher, Barbara

2023

Quantifying wet scavenging processes in aircraft observations of nitric acid and cloud condensation nuclei.

Garrett, T.J.; Avey, L.; Palmer, P.I.; Stohl, A.; Neuman, J.A.; Brock, C.A.; Ryerson, T.B.; Holloway, J.S.

2006

Quantifying the source/receptor link for the IAGOS-MOZAIC observation database.

Auby, A.; Sauvage, B.; Thouret, V.; Boulanger, D.; Eckhardt, S.; Darras, S.; Turquety, S.

2013

Quantifying the Impact of the Covid-19 Lockdown Measures on Nitrogen Dioxide Levels throughout Europe

Solberg, Sverre; Walker, Sam-Erik; Schneider, Philipp; Guerreiro, Cristina

MDPI

2021

Quantifying subnational CO2 emissions by assimilating regional measurements in a global high-resolution inverse model

Nayagam, Lorna Raja; Maksyutov, Shamil; Oda, Tomohiro; Janardanan, Rajesh; Yoshida, Yukio; Trisolino, Pamela; Zeng, Jiye; Kaiser, Johannes; Matsunaga, Tsuneo

2024

Quantifying methane emissions from the Arctic Ocean seabed to the atmosphere.

Platt, S.; Pisso, I.; Schmidbauer, N.; Hermansen, O.; Silyakova, A.; Ferré, B.; Vadakkepuliyambatta, S.; Myhre, G.; Mienert, J.; Stohl, A.; Myhre, C.L.

2016

Quantifying effect of traffic measures using individual exposure modeling. NILU F

Clench-Aas, J.; Bartonova, A.; Klæboe, R.; Kolbenstvedt, M.

1999

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