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2 Foundations of Computing and Decision Sciences

2 2023

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Towards automated recommendations for drunk driving penalties in Poland - a case study analysis in selected court

Kiejnich-Kruk Karolina, Twardawa Mateusz, Formanowicz Piotr

Foundations of Computing and Decision Sciences

2023

Vol. 48, No. 4

425--451

Depending on the legal system, judges may have varying degrees of discretion in determining the type and extent of sentence that can be imposed for a particular offence. Nevertheless, it appears that even in systems traditionally considered discretionary, accepted patterns play a significant role in determining penalties, and judges utilize merely a limited spectrum of potential penalties in repetitive cases. Confirmation of the predictability of sentencing in certain categories of cases facilitates the possibility of automation. Utilising a computer program to assist judges in sentencing proposals based on input is feasible. This program can reflect the standard practice of sentencing penalties and punitive measures in a particular category of cases or rectify it, depending on the adopted sentencing policy. The objective of the article is to present findings from research that investigated whether a specific relation shapes the dimension of penalties and penal measures for cases concerning driving under the influence of alcohol in Poland, in the context of possible automation of the sentencing process. Another aim of this study is to provide an example of a straightforward mathematical recommendation model that tries to reflect both the discovered correlations in the data and the presumed intentions of legislators.

A DNA Algorithm for Calculating the Maximum Flow of a Network

Sackmann Andrea, Brown Kristelle, Formanowicz Piotr, Morgan Kevin, Kalsheker Noor, Garibaldi Jon M., Blażewicz Jacek

Foundations of Computing and Decision Sciences

2023

Vol. 48, No. 4

483--506

DNA computing is a highly interdisciplinary field which combines molecular operations with theoretical algorithm design. A number of algorithms have been demonstrated in DNA computing, but to date network flow problems have not been studied. We aim to provide an approach to calculate the value of the maximum flow in networks by encoding the mathematical problem in DNA molecules and by using molecular biology techniques to manipulate the DNA. We present results which demonstrate that the algorithm works for an example network problem. This paper presents the first application of DNA computing to network-flow problems. The presented algorithm has a linear time complexity where the calculation itself is done in a constant number of steps.