probabilistic modelling
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2022 ◽  
Vol 189 ◽  
pp. 107108
Author(s):  
Lauri Jaamala ◽  
Kristo Mela ◽  
Jussi Laurila ◽  
Milla Rinne ◽  
Pasi Peura

2021 ◽  
Author(s):  
◽  
Valerie Chan

<p>We consider probabilistic modelling for accomplishing record linkage across two large scale publicly available data sources: New Zealand Births Deaths and Marriages (BDM), and Māori Land Online (MLO). We undertake this project in the context of te ao Māori, integrating mātauranga Māori principles into the work. We present several methods for record linkage and several novel ways to reject false linkages.</p>


2021 ◽  
Author(s):  
◽  
Valerie Chan

<p>We consider probabilistic modelling for accomplishing record linkage across two large scale publicly available data sources: New Zealand Births Deaths and Marriages (BDM), and Māori Land Online (MLO). We undertake this project in the context of te ao Māori, integrating mātauranga Māori principles into the work. We present several methods for record linkage and several novel ways to reject false linkages.</p>


2021 ◽  
pp. 100206
Author(s):  
Nicoleta Spînu ◽  
Mark T.D. Cronin ◽  
Junpeng Lao ◽  
Anna Bal-Price ◽  
Ivana Campia ◽  
...  

2021 ◽  
Vol 5 ◽  
pp. 14
Author(s):  
Tommi Mäklin ◽  
Teemu Kallonen ◽  
Sophia David ◽  
Christine J. Boinett ◽  
Ben Pascoe ◽  
...  

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.


Author(s):  
Kangfeng Ye ◽  
Ana Cavalcanti ◽  
Simon Foster ◽  
Alvaro Miyazawa ◽  
Jim Woodcock

AbstractRoboChart is a timed domain-specific language for robotics, distinctive in its support for automated verification by model checking and theorem proving. Since uncertainty is an essential part of robotic systems, we present here an extension to RoboChart to model uncertainty using probabilism. The extension enriches RoboChart state machines with probability through a new construct: probabilistic junctions as the source of transitions with a probability value. RoboChart has an accompanying tool, called RoboTool, for modelling and verification of functional and real-time behaviour. We present here also an automatic technique, implemented in RoboTool, to transform a RoboChart model into a PRISM model for verification. We have extended the property language of RoboTool so that probabilistic properties expressed in temporal logic can be written using controlled natural language.


Author(s):  
Oleksiy Larin ◽  
Kseniia Potopalska ◽  
Oleksandr Polivanov ◽  
Sergii Nazarenko ◽  
Andrii Kalynovskyi

2021 ◽  
pp. 110679
Author(s):  
Rodney Feliciano ◽  
Géraldine Boué ◽  
Fahad Mohssin ◽  
Mohammed Mustafa Hussaini ◽  
Jeanne-Marie Membré

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