889 resultados para Digital Forensics, Forensic Computing, Forensic Science
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This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.
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The conclusions reached while considering various aspects of the implemented strategy in the identification procedures in the wake of the tsunami disaster of December 26, 2004 are outlined. The lessons to be learned are discussed.
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This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (Csingle bondH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.
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PURPOSE: To investigate the dual-energy CT behavior of cocaine and heroin and of typical adulterants, and to evaluate the elemental composition of pure cocaine and heroin compared with cocaine and heroin in bodypacks. METHODS: Pure heroin and pure synthetic cocaine samples, eight different adulterants, and in each case ten different bodypacks containing cocaine or heroin, were imaged at 80, 100, 120, and 140 kVp in a dual source CT system at two different degrees of compression. Two radiologists, blinded to the samples, measured the attenuation. The dual-energy index (DEI) was calculated. We performed atomic mass spectrometry for the elemental analysis of pure cocaine, pure heroin, and heroin and cocaine in bodypacks, and 140 kVp in a dual-source CT system. RESULTS: Inter- and intra-observer agreement for attenuation measurements was good (r = 0.61-0.72; p < 0.01). The cocaine bodypacks had a positive DEI of 0.029, while the pure drugs and the heroin bodypacks had a negative DEI (-0.051 to -0.027). Levamisole was the only substance which expressed a positive DEI of 0.011, while the remaining adulterants had negative DEIs ranging between -0.015 and -0.215. Atomic mass spectrometry revealed a concentration of tin in the cocaine bodypack that was 67 times higher than in the pure synthetic cocaine sample. CONCLUSIONS: The different DEIs of bodypacks containing cocaine and heroin allow them to be distinguished with dual-energy CT. Although the material properties of pure cocaine, pure heroin, or common drug extenders do not explain the differences in DEI, tin contamination during illicit natural cocaine production may be a possible explanation.
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In Switzerland, a two-tier system based on impairment by any psychoactive substances which affect the capacity to drive safely and zero tolerance for certain illicit drugs came into force on 1 January 2005. According to the new legislation, the offender is sanctioned if Delta(9)-tetrahydrocannabinol THC is >or=1.5ng/ml or amphetamine, methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyethylamphetamine (MDEA), cocaine, free morphine are >or=15ng/ml in whole blood (confidence interval+/-30%). For all other psychoactive substances, impairment must be proven in applying the so-called "three pillars expertise". At the same time the legal blood alcohol concentration (BAC) limit for driving was lowered from 0.80 to 0.50g/kg. The purpose of this study was to analyze the prevalence of drugs in the first year after the introduction of the revision of the Swiss Traffic Law in the population of drivers suspected of driving under the influence of drugs (DUID). A database was developed to collect the data from all DUID cases submitted by the police or the Justice to the eight Swiss authorized laboratories between January and December 2005. Data collected were anonymous and included the age, gender, date and time of the event, the type of vehicle, the circumstances, the sampling time and the results of all the performed toxicological analyses. The focus was explicitly on DUID; cases of drivers who were suspected to be under the influence of ethanol only were not considered. The final study population included 4794 DUID offenders (4243 males, 543 females). The mean age of all drivers was 31+/-12 years (range 14-92 years). One or more psychoactive drugs were detected in 89% of all analyzed blood samples. In 11% (N=530) of the samples, neither alcohol nor drugs were present. The most frequently encountered drugs in whole blood were cannabinoids (48% of total number of cases), ethanol (35%), cocaine (25%), opiates (10%), amphetamines (7%), benzodiazepines (6%) and methadone (5%). Other medicinal drugs such as antidepressants and benzodiazepine-like were detected less frequently. Poly-drug use was prevalent but it may be underestimated because the laboratories do not always analyze all drugs in a blood sample. This first Swiss study points out that DUID is a serious problem on the roads in Switzerland. Further investigations will show if this situation has changed in the following years.
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Pearson correlation coefficients were applied for the objective comparison of 30 black gel pen inks analysed by laser desorption ionization mass spectrometry (LDI-MS). The mass spectra were obtained for ink lines directly on paper using positive and negative ion modes at several laser intensities. This methodology has the advantage of taking into account the reproducibility of the results as well as the variability between spectra of different pens. A differentiation threshold could thus be selected in order to avoid the risk of false differentiation. Combining results from positive and negative mode yielded a discriminating power up to 85%, which was better than the one obtained previously with other optical comparison methodologies. The technique also allowed discriminating between pens from the same brand.
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Several ink dating methods based on solvents analysis using gas chromatography/mass spectrometry (GC/MS) were proposed in the last decades. These methods follow the drying of solvents from ballpoint pen inks on paper and seem very promising. However, several questions arose over the last few years among questioned documents examiners regarding the transparency and reproducibility of the proposed techniques. These questions should be carefully studied for accurate and ethical application of this methodology in casework. Inspired by a real investigation involving ink dating, the present paper discusses this particular issue throughout four main topics: aging processes, dating methods, validation procedures and data interpretation. This work presents a wide picture of the ink dating field, warns about potential shortcomings and also proposes some solutions to avoid reporting errors in court.
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Tolperisone (Mydocalm) is a centrally acting muscle relaxant with few sedative side effects that is used for the treatment of chronic pain conditions. We describe three cases of suicidal tolperisone poisoning in three healthy young subjects in the years 2006, 2008 and 2009. In all cases, macroscopic and microscopic autopsy findings did not reveal the cause of death. Systematic toxicological analysis (STA) including immunological tests, screening for volatile substances and blood, urine and gastric content screening by GC-MS and HPLC-DAD demonstrated the presence of tolperisone in all cases. In addition to tolperisone, only the analgesics paracetamol (acetaminophen), ibuprofen and naproxen could be detected. The blood ethanol concentrations were all lower than 0.10 g/kg. Tolperisone was extracted by liquid-liquid extraction using n-chlorobutane as the extraction solvent. The quantification was performed by GC-NPD analysis of blood, urine and gastric content. Tolperisone concentrations of 7.0 mg/l, 14 mg/l and 19 mg/l were found in the blood of the deceased. In the absence of other autopsy findings, the deaths in these three cases were finally explained as a result of lethal tolperisone ingestion. To the best of our knowledge, these three cases are the first reported cases of suicidal tolperisone poisonings.
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The aim of this research was to evaluate how fingerprint analysts would incorporate information from newly developed tools into their decision making processes. Specifically, we assessed effects using the following: (1) a quality tool to aid in the assessment of the clarity of the friction ridge details, (2) a statistical tool to provide likelihood ratios representing the strength of the corresponding features between compared fingerprints, and (3) consensus information from a group of trained fingerprint experts. The measured variables for the effect on examiner performance were the accuracy and reproducibility of the conclusions against the ground truth (including the impact on error rates) and the analyst accuracy and variation for feature selection and comparison.¦The results showed that participants using the consensus information from other fingerprint experts demonstrated more consistency and accuracy in minutiae selection. They also demonstrated higher accuracy, sensitivity, and specificity in the decisions reported. The quality tool also affected minutiae selection (which, in turn, had limited influence on the reported decisions); the statistical tool did not appear to influence the reported decisions.
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The development of statistical models for forensic fingerprint identification purposes has been the subject of increasing research attention in recent years. This can be partly seen as a response to a number of commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. In addition, key forensic identification bodies such as ENFSI [1] and IAI [2] have recently endorsed and acknowledged the potential benefits of using statistical models as an important tool in support of the fingerprint identification process within the ACE-V framework. In this paper, we introduce a new Likelihood Ratio (LR) model based on Support Vector Machines (SVMs) trained with features discovered via morphometric and spatial analyses of corresponding minutiae configurations for both match and close non-match populations often found in AFIS candidate lists. Computed LR values are derived from a probabilistic framework based on SVMs that discover the intrinsic spatial differences of match and close non-match populations. Lastly, experimentation performed on a set of over 120,000 publicly available fingerprint images (mostly sourced from the National Institute of Standards and Technology (NIST) datasets) and a distortion set of approximately 40,000 images, is presented, illustrating that the proposed LR model is reliably guiding towards the right proposition in the identification assessment of match and close non-match populations. Results further indicate that the proposed model is a promising tool for fingerprint practitioners to use for analysing the spatial consistency of corresponding minutiae configurations.
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Under the influence of intelligence-led policing models, crime analysis methods have known of important developments in recent years. Applications have been proposed in several fields of forensic science to exploit and manage various types of material evidence in a systematic and more efficient way. However, nothing has been suggested so far in the field of false identity documents.This study seeks to fill this gap by proposing a simple and general method for profiling false identity documents which aims to establish links based on their visual forensic characteristics. A sample of more than 200 false identity documents including French stolen blank passports, counterfeited driving licenses from Iraq and falsified Bulgarian driving licenses was gathered from nine Swiss police departments and integrated into an ad hoc developed database called ProfID. Links detected automatically and systematically through this database were exploited and analyzed to produce strategic and tactical intelligence useful to the fight against identity document fraud.The profiling and intelligence process established for these three types of false identity documents has confirmed its efficiency, more than 30% of documents being linked. Identity document fraud appears as a structured and interregional criminality, against which material and forensic links detected between false identity documents might serve as a tool for investigation.
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Determining the time since deposition of fingermarks may prove necessary to assess their relevance to criminal investigations. The crucial factor is the initial composition of fingermarks, because it represents the starting point of any aging model. This study mainly aimed to characterize the initial composition of fingerprints, which show a high variability between donors (inter-variability), but also to investigate the variations among fingerprints from the same donor (intra-variability). Solutions to reduce this initial variability using squalene and cholesterol as target compounds are proposed and should be further investigated. The influence of substrates was also evaluated, and the initial composition was observed to be larger on porous surface than nonporous surfaces. Preliminary aging of fingerprints over 30 days was finally studied on a porous and a nonporous substrate to evaluate the potential for dating of fingermarks. Squalene was observed to decrease in a faster rate on a nonporous substrate.
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Deciding whether two fingerprint marks originate from the same source requires examination and comparison of their features. Many cognitive factors play a major role in such information processing. In this paper we examined the consistency (both between- and within-experts) in the analysis of latent marks, and whether the presence of a 'target' comparison print affects this analysis. Our findings showed that the context of a comparison print affected analysis of the latent mark, possibly influencing allocation of attention, visual search, and threshold for determining a 'signal'. We also found that even without the context of the comparison print there was still a lack of consistency in analysing latent marks. Not only was this reflected by inconsistency between different experts, but the same experts at different times were inconsistent with their own analysis. However, the characterization of these inconsistencies depends on the standard and definition of what constitutes inconsistent. Furthermore, these effects were not uniform; the lack of consistency varied across fingerprints and experts. We propose solutions to mediate variability in the analysis of friction ridge skin.
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Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.
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Since the first anti-doping tests in the 1960s, the analytical aspects of the testing remain challenging. The evolution of the analytical process in doping control is discussed in this paper with a particular emphasis on separation techniques, such as gas chromatography and liquid chromatography. These approaches are improving in parallel with the requirements of increasing sensitivity and selectivity for detecting prohibited substances in biological samples from athletes. Moreover, fast analyses are mandatory to deal with the growing number of doping control samples and the short response time required during particular sport events. Recent developments in mass spectrometry and the expansion of accurate mass determination has improved anti-doping strategies with the possibility of using elemental composition and isotope patterns for structural identification. These techniques must be able to distinguish equivocally between negative and suspicious samples with no false-negative or false-positive results. Therefore, high degree of reliability must be reached for the identification of major metabolites corresponding to suspected analytes. Along with current trends in pharmaceutical industry the analysis of proteins and peptides remains an important issue in doping control. Sophisticated analytical tools are still mandatory to improve their distinction from endogenous analogs. Finally, indirect approaches will be discussed in the context of anti-doping, in which recent advances are aimed to examine the biological response of a doping agent in a holistic way.