An Abstraction-Driven Approach for Complex Model-Based Software Development

2010 ◽  
Author(s):  
K O Chow
Keyword(s):  
Software Development ◽  
Complex Model ◽  
Model Based

scholarly journals Phosphate Adsorption on γ-Alumina: A Surface Complex Model Based on Surface Characterization and Zeta Potential Measurements

2021 ◽  
Author(s):  
Teddy Roy ◽  
Dorothea Wisser ◽  
Mickaël Rivallan ◽  
Manuel Corral Valero ◽  
Thibaut Corre ◽  
...  
Keyword(s):  
Zeta Potential ◽  
Surface Characterization ◽  
Complex Model ◽  
Phosphate Adsorption ◽  
Surface Complex ◽  
Model Based

Future Automotive Embedded Systems Enabled by Efficient Model-Based Software Development

2021 ◽  
Author(s):  
Juergen Schaefer ◽  
Herbert Christlbauer ◽  
Alexander Schreiber ◽  
Graham Reith ◽  
Mischa Jonker ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Software Development ◽  
Model Based

Integrating model checking and model based testing for industrial software development

2019 ◽  
Vol 104 ◽  
pp. 88-102 ◽  
Author(s):  
Emília Villani ◽  
Rodrigo Pastl Pontes ◽  
Guilherme Kisselofl Coracini ◽  
Ana Maria Ambrósio
Keyword(s):  
Model Checking ◽  
Software Development ◽  
Model Based ◽  
Model Based Testing ◽  
Industrial Software

Continual Human Value Analysis in Software Development: A Goal Model Based Approach

2020 ◽  
Author(s):  
Harsha Perera ◽  
Gunter Mussbacher ◽  
Waqar Hussain ◽  
Rifat Ara Shams ◽  
Arif Nurwidyantoro ◽  
...  
Keyword(s):  
Software Development ◽  
Goal Model ◽  
Value Analysis ◽  
Model Based ◽  
Human Value

scholarly journals Analysis of Four Years of Global XCO2 Anomalies as Seen by Orbiting Carbon Observatory-2

2019 ◽  
Vol 11 (7) ◽  
pp. 850 ◽  
Author(s):  
Janne Hakkarainen ◽  
Iolanda Ialongo ◽  
Shamil Maksyutov ◽  
David Crisp
Keyword(s):  
South Africa ◽  
Biomass Burning ◽  
Fossil Fuel ◽  
Global Scale ◽  
Complex Model ◽  
Fuel Combustion ◽  
Local Concentration ◽  
Fossil Fuel Combustion ◽  
Tropical Regions ◽  
Model Based

NASA’s carbon dioxide mission, Orbiting Carbon Observatory-2, began operating in September 2014. In this paper, we analyze four years (2015–2018) of global (60°S–60°N) XCO2 anomalies and their annual variations and seasonal patterns. We show that the anomaly patterns in the column-averaged CO2 dry air mole fraction, XCO2, are robust and consistent from year-to-year. We evaluate the method by comparing the anomalies to fluxes from anthropogenic, biospheric, and biomass burning and to model-simulated local concentration enhancements. We find that, despite the simplicity of the method, the anomalies describe the spatio-temporal variability of XCO2 (including anthropogenic emissions and seasonal variability related to vegetation and biomass burning) consistently with more complex model-based approaches. We see, for example, that positive anomalies correspond to fossil fuel combustion over the major industrial areas (e.g., China, eastern USA, central Europe, India, and the Highveld region in South Africa), shown as large positive XCO2 enhancements in the model simulations. We also find corresponding positive anomalies and fluxes over biomass burning areas during different fire seasons. On the other hand, the largest negative anomalies correspond to the growing season in the northern middle latitudes, characterized by negative XCO2 enhancements from simulations and high solar-induced chlorophyll fluorescence (SIF) values (indicating the occurrence of photosynthesis). The largest discrepancies between the anomaly patterns and the model-based results are observed in the tropical regions, where OCO-2 shows persistent positive anomalies over every season of every year included in this study. Finally, we demonstrate how XCO2 anomalies enable the detection of anthropogenic signatures for several local scale case studies, both in the Northern and Southern Hemisphere. In particular, we analyze the XCO2 anomalies collocated with the recent TROPOspheric Monitoring Instrument NO2 observations (used as indicator of anthropogenic fossil fuel combustion) over the Highveld region in South Africa. The results highlight the capability of satellite-based observations to monitor natural and man-made CO2 signatures on global scale.

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