minor changes to md and bib of JOSS paper (#107)

* oxford commas (style)

* update bib

paper/paper.bib

@@ -3,29 +3,23 @@ @INPROCEEDINGS{Hammer:2017
 	booktitle={2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC)},
 	title={Safety analysis paradigm for UAS: Development and use of a common architecture and fault tree model},
 	year={2017},
-	volume={},
-	number={},
 	pages={1-10},
 	doi={10.1109/DASC.2017.8102039}
 }
 @INPROCEEDINGS{Cour-Harbo:2020,
-	author={Cour-Harbo, Anders la},
+	author={la Cour-Harbo, Anders},
 	booktitle={2020 International Conference on Unmanned Aircraft Systems (ICUAS)}, 
 	title={Ground impact probability distribution for small unmanned aircraft in ballistic descent}, 
 	year={2020},
-	volume={},
-	number={},
 	pages={1442-1451},
 	doi={10.1109/ICUAS48674.2020.9213990}
 }
 
-@INBOOK{Ancel:2017,
+@INPROCEDINGS{Ancel:2017,
 	author = {Ersin Ancel and Francisco M. Capristan and John V. Foster and Ryan C. Condotta},
 	title = {Real-time Risk Assessment Framework for Unmanned Aircraft System (UAS) Traffic Management (UTM)},
 	booktitle = {17th AIAA Aviation Technology, Integration, and Operations Conference},
 	year = {2017},
-	chapter = {},
-	pages = {},
 	doi = {10.2514/6.2017-3273},
 	URL = {https://arc.aiaa.org/doi/abs/10.2514/6.2017-3273},
 	eprint = {https://arc.aiaa.org/doi/pdf/10.2514/6.2017-3273}

paper/paper.md

@@ -56,7 +56,7 @@ SEEDPOD Ground Risk is a Python application and package that enables the generat
 GPU-accelerated routines for the risk calculation as well as being, to the authors best knowledge, the first open-source
 probabilistic ground risk assessment tool. Numba is used for all calculation acceleration and enable the fallback to
 JIT-compiled CPU code where a compatible NVIDIA GPU is not detected. A common set of scientific and geospatial Python
-packages are used, such as NumPy, SciPy, Pandas and GeoPandas.
+packages are used, such as NumPy, SciPy, Pandas, and GeoPandas.
 
 The software is intended to allow for further development and testing of different constituent models as part of a
 holistic ground risk assessment process. This enables the exploration of individual model effects on the final ground
@@ -74,7 +74,7 @@ exposes much the same functionality as the API in a no-code environment.
 # Acknowledgements
 
 This work is funded by the Engineering and Physical Sciences Research Council as part of the E-Drone project under grant
-number EP/V002619/1. The authors would like to thank András Sóbester, James Scanlan and Mario Ferraro for their guidance
+number EP/V002619/1. The authors would like to thank András Sóbester, James Scanlan, and Mario Ferraro for their guidance
 and advice on theoretical aspects of the work.
 
 # References