000			02754nam a2200277 4500
001			391185
090			_a391185
100			_a20121008d2012 y0pory50 ba
101			_aeng
200			_aApplication of machine learning to toolmarks _bRecurso eletrónico _estatistically based methods for impression pattern comparisons _fNicholas D. K. Petraco ... [et al.]
210			_aNew York _ced. do a. _d2012
215			_a1 CD-ROM _d12 cm
300			_aResearch report funded by the U.S. Department of Justice, Award nr. 2009-DN-BX-K041. Ficheiro de 7,37 MB em formato PDF (101 p.). Disponível também em: https://www.ncjrs.gov/pdffiles1/nij/grants/239048.pdf. Acedido a 08 de outubro de 2012.
330			_aExecutive summary. Final technical report. I. Introduction: 1. Statement of the problem. 2. Review of relevant literature. 2.1 Introduction to toolmarks and toolmark examination. 2.2 Individualization of toolmarks. 2.3 Materials for experimentation. 2.4 Two schools of thought. 2.5 Methods and techniques of toolmark examination. 2.6 Reliability of toolmark examination. 2.7 Court decisions. 2.8 Statistics and toolmarks. 3. Rationale for the research. II. Materials and Methods: 1. Materials. 2. Methods for toolmark impression data collection. 1.1 Generating reproducible toolmark impressions. 1.2 Confocal microscope. 3. Machine learning methods for toolmark comparison. 3.1 General striated toolmark surface preprocessing and feature vector construction. 3.2 The data matrix and principal component analysis. 3.3 Canonical variate analysis. 3.4 Support vector machines. 4. Methods for error rate estimation. 4.1 Resubstitution methods. 4.2 Conformal prediction theory. III. Results: 1. Toolmark impression data collection and database. 1.1 Cartridge case striation and impression pattern collection. 1.2 Striated toolmark pattern collection. 1.3 Database and web interface. 1.4 Surface visualization and measurement software. 1.5 Profile simulator software. 1.6 R software and statistical analysis scripts. 2. Statistical Analyses. 2.1 Glock 19 Cartridge Casings. 2.2 Screwdriver striation patterns. IV. Conclusions: 1. Discussion of findings. 2. Implications for policy and practice. 3. Implications for further research. V. References. VI. Dissemination of research findings.
606			_aMARCAÇÃO DE OBJECTOS _9343973
606			_aBALÍSTICA _9320585
606			_aBASE DE DADOS _9227272
606			_aARMA DE FOGO E MUNIÇÕES _9343053
710			_aAPPLICATION OF MACHINE LEARNING TO TOOLMARKS _9356877
955			_xOferta