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Pregled bibliografske jedinice broj: 1180483

Inter-laboratory workflow for forensic applications: Classification of car glass fragments


Kaspi, Omer; Israelsohn-Azulay, Osnat; Yigal, Zidon; Rosengarten, Hila; Krmpotić, Matea; Gouasmia, Sabrina; Bogdanović Radović, Iva; Jalkanen, Pasi; Liski, Anna; Mizohata, Kenichiro et al.
Inter-laboratory workflow for forensic applications: Classification of car glass fragments // Forensic science international, 333 (2022), 111216, 9 doi:10.1016/j.forsciint.2022.111216 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1180483 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Inter-laboratory workflow for forensic applications: Classification of car glass fragments

Autori
Kaspi, Omer ; Israelsohn-Azulay, Osnat ; Yigal, Zidon ; Rosengarten, Hila ; Krmpotić, Matea ; Gouasmia, Sabrina ; Bogdanović Radović, Iva ; Jalkanen, Pasi ; Liski, Anna ; Mizohata, Kenichiro ; Räisänen, Jyrki ; Girshevitz, Olga ; Senderowitz, Hanoch

Izvornik
Forensic science international (0379-0738) 333 (2022); 111216, 9

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
PIXE ; car window glass fragments ; Machine Learning ; Forensics

Sažetak
The International Atomic Energy Agency (IAEA) has coordinated a research project titled ”Enhancing Nuclear Analytical Techniques to Meet the Needs of Forensics Sciences” (CRP F11021) with the aim of empowering accelerator and reactor based techniques for applications in forensic sciences. One of the key topics of this project was the analysis and classification of forensic glass specimens using Ion Beam Analysis (IBA) techniques and in particular, Particle Induced X-ray Emission (PIXE). To this end, glass fragments from car windows from different car models and manufacturers provided by the Israeli police force were subjected to PIXE measurements at three laboratories to determine their elemental compositions and possible glass corrosion. Major and trace elements were measured and given as an input to machine learning (ML) algorithms in order to develop classification models to determine the origin of the glass samples. First, we have developed ML models based on the results obtained at each lab. These models successfully classified glass fragments into different car models with an accuracy >80% on external test sets. Next, we demonstrated that following an appropriate pre-processing step, results from different labs could be combined into a single unified database for the derivation of a classification model. This model demonstrates good performances that matches or surpasses the performances of models derived from the individual labs. This finding paves the way towards establishing an international database that is composed of measurements from various PIXE labs. We believe that using this methodology of combining various sources of measurements will improve models’ performances and generality and will make the models accessible to law enforcement agencies around the world.

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Kemija



POVEZANOST RADA


Ustanove:
Institut "Ruđer Bošković", Zagreb

Poveznice na cjeloviti tekst rada:

doi www.sciencedirect.com doi.org

Citiraj ovu publikaciju:

Kaspi, Omer; Israelsohn-Azulay, Osnat; Yigal, Zidon; Rosengarten, Hila; Krmpotić, Matea; Gouasmia, Sabrina; Bogdanović Radović, Iva; Jalkanen, Pasi; Liski, Anna; Mizohata, Kenichiro et al.
Inter-laboratory workflow for forensic applications: Classification of car glass fragments // Forensic science international, 333 (2022), 111216, 9 doi:10.1016/j.forsciint.2022.111216 (međunarodna recenzija, članak, znanstveni)
Kaspi, O., Israelsohn-Azulay, O., Yigal, Z., Rosengarten, H., Krmpotić, M., Gouasmia, S., Bogdanović Radović, I., Jalkanen, P., Liski, A. & Mizohata, K. (2022) Inter-laboratory workflow for forensic applications: Classification of car glass fragments. Forensic science international, 333, 111216, 9 doi:10.1016/j.forsciint.2022.111216.
@article{article, author = {Kaspi, Omer and Israelsohn-Azulay, Osnat and Yigal, Zidon and Rosengarten, Hila and Krmpoti\'{c}, Matea and Gouasmia, Sabrina and Bogdanovi\'{c} Radovi\'{c}, Iva and Jalkanen, Pasi and Liski, Anna and Mizohata, Kenichiro and R\"{a}is\"{a}nen, Jyrki and Girshevitz, Olga and Senderowitz, Hanoch}, year = {2022}, pages = {9}, DOI = {10.1016/j.forsciint.2022.111216}, chapter = {111216}, keywords = {PIXE, car window glass fragments, Machine Learning, Forensics}, journal = {Forensic science international}, doi = {10.1016/j.forsciint.2022.111216}, volume = {333}, issn = {0379-0738}, title = {Inter-laboratory workflow for forensic applications: Classification of car glass fragments}, keyword = {PIXE, car window glass fragments, Machine Learning, Forensics}, chapternumber = {111216} }
@article{article, author = {Kaspi, Omer and Israelsohn-Azulay, Osnat and Yigal, Zidon and Rosengarten, Hila and Krmpoti\'{c}, Matea and Gouasmia, Sabrina and Bogdanovi\'{c} Radovi\'{c}, Iva and Jalkanen, Pasi and Liski, Anna and Mizohata, Kenichiro and R\"{a}is\"{a}nen, Jyrki and Girshevitz, Olga and Senderowitz, Hanoch}, year = {2022}, pages = {9}, DOI = {10.1016/j.forsciint.2022.111216}, chapter = {111216}, keywords = {PIXE, car window glass fragments, Machine Learning, Forensics}, journal = {Forensic science international}, doi = {10.1016/j.forsciint.2022.111216}, volume = {333}, issn = {0379-0738}, title = {Inter-laboratory workflow for forensic applications: Classification of car glass fragments}, keyword = {PIXE, car window glass fragments, Machine Learning, Forensics}, chapternumber = {111216} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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