Research on Suicide Risk Spectrum of Prisoners Based on Fourier Transform

Sainan Gao () and Yang Shen ()
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Sainan Gao: Nanjing University of Aeronautics and Astronautics
Yang Shen: Nanjing University of Aeronautics and Astronautics

Chapter Chapter 15 in City, Society, and Digital Transformation, 2022, pp 191-202 from Springer

Abstract: Abstract Prisoner suicide risk prevention and control cannot be ignored, yet there is a lack of relevant quantitative studies to support risk management. We quantify the risk of prisoner suicide based on the Fourier transform, establish a relevant data model, and examine the impact of different frequencies of influencing factors on the overall risk of prisoner suicide through simulation. At the same time, we innovatively use Fourier transform to obtain the frequency spectrum of prisoner suicide risk data, and conduct frequency domain analysis. The simulation results show that negative events are the most influential factor on the overall prisoner suicide risk, and the frequency domain analysis provides the cyclical characteristics of suicide risk for different types of prisoners. We emphasize the importance of fairness in prison enforcement to reduce the occurrence of negative events and the need for periodic suicide screening and prevention based on the behavioral characteristics of prisoners.

Keywords: Prison suicide; Fourier transform; Simulation; Prison management (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-15644-1_15

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DOI: 10.1007/978-3-031-15644-1_15

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