The AFIS comparison algorithm Motorola BIS Printrak

The AFIS comparison algorithm (Motorola BIS - Printrak 9.1) is used here as a black box, without the aim of scrutinizing its internal approach to compute scores. A detailed description of the algorithm inside the black box can be found in [2]. In recent work [9] it order CP-673451 is shown that the higher the amount of scores to train the models, the more adequate the plug-in method. In this example, the propositions for the computation of the LR are established at source level, and defined as follows: The determination of the relevant propositions in a specific case is mandatory. However, the hypotheses determined in this particular example are generic and not intended as a recommendation in the original article [1]. They are just given for the purpose of illustration. Each particular case will lead to a different set of propositions, and this should be considered in the scope of the validation process. The determination of the hypotheses is part of the scope of the validation procedure conducted, which should be incorporated to other requirements from each particular laboratory or institution.
Datasets used As recommended in the original article [1], different datasets are used for the development and validation stages. A “forensic” dataset, consisting of fingermarks from the real cases, was used in the validation stage. The LRs generated by the methods, are the values used to conduct the validation process, and are the data presented in this contribution.
Multimodal LR method and baseline KDF
Validation criteria The validation criteria are established with respect to the results of the performance characteristic of the baseline method, as mentioned in Table 4 below.
Validation report In this section, we present a validation report following the EN ISO/IEC 17025:2005 recommendations, where all the items in the validation matrix above are addressed (Table 4). The report is presented per performance characteristic in Subsections 8.1 to 8.6 below.
Validation decision The multimodal LR method developed for the forensic fingerprint evidence evaluation appears to be satisfying the validation criteria specified above, with a remark regarding the coherence. Summary across different performance characteristics is presented in Table 8 below.
Acknowledgements The research was conducted in scope of the BBfor2 – European Commission Marie Curie Initial Training Network (FP7-PEOPLE-ITN-2008 under Grant Agreement 238803) in cooperation with The Netherlands Forensic Institute and the ATVS Biometric Recognition Group at the Universidad Autonoma de Madrid.
Data A physical nature, period and image of collected ancient pottery samples are given in Table 1. The major and trace elemental concentration of ancient potteries are determined using the EDXRF technique and reported in Table 2. Factor loadings of major and trace elements of ancient potteries are given in Table 3 (STATISTICA (10.0 version) software). Fig. 1 shows the archeological excavation sites in the study area. Figs. 2 and 3 represent the factor analysis and Fig. 4 shows the clustering analysis of major and trace elements.
Experimental design, materials and methods
Acknowledgment We are sincerely thankful and grateful to Dr. K. K. Satpathy, Head, Environment and Safety Division, RSEG, EIRSG, Indira Gandhi Centre for Atomic Research (IGCAR), Kalpakkam, Tamil Nadu, India for giving us permission to make use of the EDXRF facility and also our deep gratitude and sincere thanks to Dr. M. V. R. Prasad, Head, EnSD, RSEG, IGCAR, Kalpakkam for his keen interest, support and constant encouragements in EDXRF measurements. Our sincere thanks to Mr. K.V. Kanagasabapathy, Scientific Officer, RSEG, IGCAR for his technical help in EDXRF analysis.
Data
Experimental design, materials and methods The data on real GDP were obtained from the World Bank׳s World Development Indicators (WDI) [2]. The data to construct fossil fuel consumption were extracted from the database of the U.S. Energy Information Administration (EIA) database [3]. Fossil fuel consumption was calculated as the sum of petroleum, coal and natural gas consumption. The EIA does not publish data on non-fossil fuels, so this was derived as total energy consumption (obtained from the database) less fossil fuel consumption.