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Eva Bruenisholz
Researcher at University of Lausanne
Publications - 7
Citations - 59
Eva Bruenisholz is an academic researcher from University of Lausanne. The author has contributed to research in topics: Poison control & Occupational safety and health. The author has an hindex of 5, co-authored 7 publications receiving 46 citations.
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Journal ArticleDOI
The Intelligent Use of Forensic Data: An Introduction to the Principles
Eva Bruenisholz,Sameer Prakash,Alastair Ross,Marie Morelato,Troy O’Malley,Michael Anthony Raymond,Olivier Ribaux,Claude Roux,Simon J. Walsh +8 more
TL;DR: The primary aim of this paper is to raise awareness on the principles and practice of forensic intelligence through the collation and integration of recently published findings and observations to provide introductory principles to personnel of various levels and disciplines involved in law enforcement.
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Dismantling the justice silos: Flowcharting the role and expertise of forensic science, forensic medicine and allied health in adult sexual assault investigations
TL;DR: The rationale for the flowchart is to produce a visual representation of a typical sexual assault investigative process highlighting where and who plays a role in order to minimise the risk of justice silos.
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Benchmarking forensic volume crime performance in Australia between 2011 and 2015.
TL;DR: The findings of the 2015 study are presented as well as comparative analyses between 2011 and 2015, which discuss the measures taken, whether legal, technological or organisational, that are likely contributors to the performance improvements.
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Repetitive deliberate fires: Development and validation of a methodology to detect series.
TL;DR: Results are very promising and lead the way to a systematic implementation of this methodology in an intelligence framework, whilst demonstrating the need and benefit of increasing the collection of forensic specific information to strengthen the value of links between cases.
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Deliberate fires: From data to intelligence.
TL;DR: This paper presents a two-fold procedure developed to produce intelligence on a dataset of fire events that were either deliberate or unknown in origin, and proposes the basis for the development of an integrated real-time intelligence process.