A framework for forensic face recognition based on recognition performance calibrated for the quality of image pairs

Recently, it has been shown that performance of a face recognition system depends on the quality of both face images participating in the recognition process: the reference and the test image. In the context of forensic face recognition, this observation has two implications: a) the quality of the trace (extracted from CCTV footage) constrains the performance achievable using a particular face recognition system; b) the quality of the suspect reference set (to which the trace is matched against) can be judiciously chosen to approach optimal recognition performance under such a constraint. Motivated by these recent findings, we propose a framework for forensic face recognition that is based on calibrating the recognition performance for the quality of pairs of images. The application of this framework to several mock-up forensic cases, created entirely from the MultiPIE dataset, shows that optimal recognition performance, under such a constraint, can be achieved by matching the quality (pose, illumination, and, imaging device) of the reference set to that of the trace. This improvement in recognition performance helps reduce the rate of misleading interpretation of the evidence

Machine Learning for Observables: Reactant to Product State Distributions for Atom-Diatom Collisions

Machine learning-based models to predict product state distributions from a distribution of reactant conditions for atom-diatom collisions are presented and quantitatively tested. The models are based on function-, kernel- and grid-based representations of the reactant and product state distributions. While all three methods predict final state distributions from explicit quasi-classical trajectory simulations with R$^2$ > 0.998, the grid-based approach performs best. Although a function-based approach is found to be more than two times better in computational performance, the kernel- and grid-based approaches are preferred in terms of prediction accuracy, practicability and generality. The function-based approach also suffers from lacking a general set of model functions. Applications of the grid-based approach to nonequilibrium, multi-temperature initial state distributions are presented, a situation common to energy distributions in hypersonic flows. The role of such models in Direct Simulation Monte Carlo and computational fluid dynamics simulations is also discussed

Higher order multipole moments for molecular dynamics simulations

In conventional force fields, the electrostatic potential is represented by atom-centred point charges. This choice is in principle arbitrary, but technically convenient. Point charges can be understood as the first term of multipole expansions, which converge with an increasing number of terms towards the accurate representation of the molecular potential given by the electron density distribution. The use of multipole expansions can therefore improve the force field accuracy. Technically, the implementation of atomic multipoles is more involved than the use of point charges. Important points to consider are the orientation of the multipole moments during the trajectory, conformational dependence of the atomic moments and stability of the simulations which are discussed her

Ligand and interfacial dynamics in a homodimeric hemoglobin

The structural dynamics of dimeric hemoglobin (HbI) from Scapharca inaequivalvis in different ligand-binding states is studied from atomistic simulations on the μs time scale. The intermediates are between the fully ligand-bound (R) and ligand-free (T) states. Tertiary structural changes, such as rotation of the side chain of Phe97, breaking of the Lys96-heme salt bridge, and the Fe-Fe separation, are characterized and the water dynamics along the R-T transition is analyzed. All these properties for the intermediates are bracketed by those determined experimentally for the fully ligand-bound and ligand-free proteins, respectively. The dynamics of the two monomers is asymmetric on the 100 ns timescale. Several spontaneous rotations of the Phe97 side chain are observed which suggest a typical time scale of 50-100 ns for this process. Ligand migration pathways include regions between the B/G and C/G helices and, if observed, take place in the 100 ns time scale

Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions

This paper is a postprint of a paper submitted to and accepted for publication in IET Biometrics and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital LibraryThis article presents a method for computing Likelihood Ratios (LR) from multimodal score distributions produced by an Automated Fingerprint Identification System (AFIS) feature extraction and comparison algorithm. The AFIS algorithm used to compare fingermarks and fingerprints was primarily developed for forensic investigation rather than for forensic evaluation. The computation of the scores is speed-optimized and performed on three different stages, each of which outputs discriminating scores of different magnitudes together forming a multimodal score distribution. It is worthy mentioning that each fingermark to fingerprint comparison performed by the AFIS algorithm results in one single similarity score (e.g. one score per comparison). The multimodal nature of the similarity scores can be typical for other biometric systems and the method proposed in this work can be applied in similar cases, where the multimodal nature in similarity scores is observed. In this work we address some of the problems related to modelling such distributions and propose solutions to issues like data sparsity, dataset shift and over-fitting. The issues mentioned affect the methods traditionally used in the situation when a multimodal nature in the similarity scores is observed (a Kernel Density Functions (KDF) was used to illustrate these issues in our case). Furthermore, the method proposed produces interpretable results in the situations when the similarity scores are sparse and traditional approaches lead to erroneous LRs of huge magnitudesThe research was conducted in scope of the BBfor2 – Marie Curie Initial Training Network (FP7-PEOPLE-ITN-2008 under the Grant Agreement 238803) at the Netherlands Forensic Institute in cooperation with the ATVS Biometric Recognition Group at the Universidad Autonoma de Madrid and the National Police Services Agency of the Netherland

Dense breast on screening mammography: utility and futility of additional ultrasound.

High breast density decreases the sensitivity of mammography. Regardless of masking effect, it is also a stronger predictor for breast cancer than most other risk factors, including family history. Up to 50% of women have dense breast (categories C+D). The relative risk is 2.1 to 2.3 in women with extremely dense breast (category d). There is little consensus on the potential need of additional measures. Breast Ultrasound (US) may be proposed as an adjunctive test, as it is non-invasive and non-irradiating. Since 2012, our program for breast cancer screening propose to realise an additional US to the women with category d breasts. An evaluation of the data of the first year showed that less 50% of the women act upon the recommendation. In spite of the low compliance supplementary cancers were found. Since, no more evaluation was performed. The aim of this study was: To evaluate the effect of the recommendation in term of additional cancer's identification, additional biopsies and additional investigations. To identify the reasons of non compliance

Measuring coherence of computer-assisted likelihood ratio methods

This is the author’s version of a work that was accepted for publication in Forensic Science International. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Forensic Science International, 249 (2015): 123 – 132 DOI:10.1016/j.forsciint.2015.01.033Measuring the performance of forensic evaluation methods that compute likelihood ratios (LRs) is relevant for both the development and the validation of such methods. A framework of performance characteristics categorized as primary and secondary is introduced in this study to help achieve such development and validation. Ground-truth labelled fingerprint data is used to assess the performance of an example likelihood ratio method in terms of those performance characteristics. Discrimination, calibration, and especially the coherence of this LR method are assessed as a function of the quantity and quality of the trace fingerprint data. Assessment of the coherence revealed a weakness of the comparison algorithm in the computer-assisted likelihood ratio method used.This research was conducted in the scope of the BBfor2 – European Commission Marie Curie Initial Training Network (FP7-PEOPLE-ITN-2008 under Grant Agreement 238803) at the Netherlands Forensic Institute, and in collaboration with the ATVS Biometric Recognition Group at the Universidad Autonoma de Madrid and the National Police Services Agency of the Netherlands

CT enteroclysis: technique and clinical applications

CT enteroclysis (CTE) has been gradually evolving with technical developments of spiral and multidetector row CT technology. It has nowadays become a well-defined imaging modality for the evaluation of various small bowel disorders. Volume challenge of 2L of enteral contrast agent administrated to the small bowel via a nasojejunal catheter ensures luminal distension, the prerequisite for the detection of mural abnormalities, also facilitating the accurate visualization of intraluminal lesions. CT acquisition is centered on small bowel loops, reconstructed in thin axial slices and completed by multiplanar views. Image analysis is essentially done in cine-mode on work-stations. CTE is of particular diagnostic value in intermediate or advanced stages of Cohn's disease, including the depiction of extraintestinal complications. It has become the imaging modality of choice for the localization and characterization of small bowel tumors. The cause and degree of low-grade small bowel obstruction is more readily analyzed with the technique of CTE than conventional CT. Limitations of CTE concern the assessment of pure intestinal motility disorders, superficial mucosal lesions and arteriovenous malformations of the small bowel, which are not consistently visualized. CTE should be selectively used to answer specific questions of the small bowel. It essentially contributes to the diagnostic quality of modern small bowel imaging, and therefore deserves an established, well-defined place among the other available technique