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Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

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Dataset of coded handwriting features for use in statistical modelling.

Anna Agius¹, Marie Morelato¹, Sébastien Moret¹

¹University of Technology Sydney, Centre for Forensic Science, PO Box 123, Broadway 2007, Australia.

|January 12, 2018

Summary

Handwriting analysis can help identify a writer's country of origin. This study provides data on writer, spatial, and construction characteristics for English Australian and Vietnamese writers to enable further research.

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Area of Science:

Forensic science
Graphology
Biometrics

Background:

Forensic intelligence relies on identifying individuals through unique characteristics.
Handwriting analysis is a key forensic discipline for writer identification.
Determining a writer's country of origin from handwriting can aid investigations.

Purpose of the Study:

To present data on handwriting characteristics for statistical analysis.
To investigate the relationship between handwriting features and writer nationality.
To assess the potential for differentiating between English Australian and Vietnamese writers based on handwriting.

Main Methods:

Data collection of writer, spatial, and construction characteristics from 37 English Australian and 37 Vietnamese writers.
Coding of characteristics using Microsoft Excel 2013.
Focus on seven specific characters: 'g', 'h', 'th', 'M', '0', '7', and '9' for construction analysis.

Main Results:

The study provides a coded dataset of handwriting characteristics.
This data enables statistical modeling to explore nationality-based handwriting variations.
The dataset facilitates research into differentiating writers by origin.

Conclusions:

The presented data supports further research into handwriting-based nationality inference.
Mathematical techniques can be employed to characterize handwriting features for forensic intelligence.
This work contributes to the field of writer identification and forensic analysis.