985 resultados para Crime analysis


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Includes bibliographical references.

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Jaccard has been the choice similarity metric in ecology and forensic psychology for comparison of sites or offences, by species or behaviour. This paper applies a more powerful hierarchical measure - taxonomic similarity (s), recently developed in marine ecology - to the task of behaviourally linking serial crime. Forensic case linkage attempts to identify behaviourally similar offences committed by the same unknown perpetrator (called linked offences). s considers progressively higher-level taxa, such that two sites show some similarity even without shared species. We apply this index by analysing 55 specific offence behaviours classified hierarchically. The behaviours are taken from 16 sexual offences by seven juveniles where each offender committed two or more offences. We demonstrate that both Jaccard and s show linked offences to be significantly more similar than unlinked offences. With up to 20% of the specific behaviours removed in simulations, s is equally or more effective at distinguishing linked offences than where Jaccard uses a full data set. Moreover, s retains significant difference between linked and unlinked pairs, with up to 50% of the specific behaviours removed. As police decision-making often depends upon incomplete data, s has clear advantages and its application may extend to other crime types. Copyright © 2007 John Wiley & Sons, Ltd.

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A growing body of scientific literature recurrently indicates that crime and forensic intelligence influence how crime scene investigators make decisions in their practices. This study scrutinises further this intelligence-led crime scene examination view. It analyses results obtained from two questionnaires. Data have been collected from nine chiefs of Intelligence Units (IUs) and 73 Crime Scene Examiners (CSEs) working in forensic science units (FSUs) in the French speaking part of Switzerland (six cantonal police agencies). Four salient elements emerged: (1) the actual existence of communication channels between IUs and FSUs across the police agencies under consideration; (2) most CSEs take into account crime intelligence disseminated; (3) a differentiated, but significant use by CSEs in their daily practice of this kind of intelligence; (4) a probable deep influence of this kind of intelligence on the most concerned CSEs, specially in the selection of the type of material/trace to detect, collect, analyse and exploit. These results contribute to decipher the subtle dialectic articulating crime intelligence and crime scene investigation, and to express further the polymorph role of CSEs, beyond their most recognised input to the justice system. Indeed, they appear to be central, but implicit, stakeholders in intelligence-led style of policing.

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"June 1984."

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Since 2008, Intelligence units of six states of the western part of Switzerland have been sharing a common database for the analysis of high volume crimes. On a daily basis, events reported to the police are analysed, filtered and classified to detect crime repetitions and interpret the crime environment. Several forensic outcomes are integrated in the system such as matches of traces with persons, and links between scenes detected by the comparison of forensic case data. Systematic procedures have been settled to integrate links assumed mainly through DNA profiles, shoemarks patterns and images. A statistical outlook on a retrospective dataset of series from 2009 to 2011 of the database informs for instance on the number of repetition detected or confirmed and increased by forensic case data. Time needed to obtain forensic intelligence in regard with the type of marks treated, is seen as a critical issue. Furthermore, the underlying integration process of forensic intelligence into the crime intelligence database raised several difficulties in regards of the acquisition of data and the models used in the forensic databases. Solutions found and adopted operational procedures are described and discussed. This process form the basis to many other researches aimed at developing forensic intelligence models.

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Whether for investigative or intelligence aims, crime analysts often face up the necessity to analyse the spatiotemporal distribution of crimes or traces left by suspects. This article presents a visualisation methodology supporting recurrent practical analytical tasks such as the detection of crime series or the analysis of traces left by digital devices like mobile phone or GPS devices. The proposed approach has led to the development of a dedicated tool that has proven its effectiveness in real inquiries and intelligence practices. It supports a more fluent visual analysis of the collected data and may provide critical clues to support police operations as exemplified by the presented case studies.

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Forensic science is generally defined as the application of science to address questions related to the law. Too often, this view restricts the contribution of science to one single process which eventually aims at bringing individuals to court while minimising risk of miscarriage of justice. In order to go beyond this paradigm, we propose to refocus the attention towards traces themselves, as remnants of a criminal activity, and their information content. We postulate that traces contribute effectively to a wide variety of other informational processes that support decision making inmany situations. In particular, they inform actors of new policing strategies who place the treatment of information and intelligence at the centre of their systems. This contribution of forensic science to these security oriented models is still not well identified and captured. In order to create the best condition for the development of forensic intelligence, we suggest a framework that connects forensic science to intelligence-led policing (part I). Crime scene attendance and processing can be envisaged within this view. This approach gives indications abouthowto structure knowledge used by crime scene examiners in their effective practice (part II).

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Deliberate fires appear to be borderless and timeless events creating a serious security problem. There have been many attempts to develop approaches to tackle this problem, but unfortunately acting effectively against deliberate fires has proven a complex challenge. This article reviews the current situation relating to deliberate fires: what do we know, how serious is the situation, how is it being dealt with, and what challenges are faced when developing a systematic and global methodology to tackle the issues? The repetitive nature of some types of deliberate fires will also be discussed. Finally, drawing on the reality of repetition within deliberate fires and encouraged by successes obtained in previous repetitive crimes (such as property crimes or drug trafficking), we will argue that the use of the intelligence process cycle as a framework to allow a follow-up and systematic analysis of fire events is a relevant approach. This is the first article of a series of three articles. This first part is introducing the context and discussing the background issues in order to provide a better underpinning knowledge to managers and policy makers planning on tackling this issue. The second part will present a methodology developed to detect and identify repetitive fire events from a set of data, and the third part will discuss the analyses of these data to produce intelligence.

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The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

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"Created date: September 14, 2001"--P. [4] of cover.

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Dissertação apresentada como requisito parcial para a obtenção do grau de Mestre em Estatística e Gestão de Informação

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Data mining can be defined as the extraction of previously unknown and potentially useful information from large datasets. The main principle is to devise computer programs that run through databases and automatically seek deterministic patterns. It is applied in different fields of application, e.g., remote sensing, biometry, speech recognition, but has seldom been applied to forensic case data. The intrinsic difficulty related to the use of such data lies in its heterogeneity, which comes from the many different sources of information. The aim of this study is to highlight potential uses of pattern recognition that would provide relevant results from a criminal intelligence point of view. The role of data mining within a global crime analysis methodology is to detect all types of structures in a dataset. Once filtered and interpreted, those structures can point to previously unseen criminal activities. The interpretation of patterns for intelligence purposes is the final stage of the process. It allows the researcher to validate the whole methodology and to refine each step if necessary. An application to cutting agents found in illicit drug seizures was performed. A combinatorial approach was done, using the presence and the absence of products. Methods coming from the graph theory field were used to extract patterns in data constituted by links between products and place and date of seizure. A data mining process completed using graphing techniques is called ``graph mining''. Patterns were detected that had to be interpreted and compared with preliminary knowledge to establish their relevancy. The illicit drug profiling process is actually an intelligence process that uses preliminary illicit drug classes to classify new samples. Methods proposed in this study could be used \textit{a priori} to compare structures from preliminary and post-detection patterns. This new knowledge of a repeated structure may provide valuable complementary information to profiling and become a source of intelligence.

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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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This report was developed to provide summary information to allow practitioners and juvenile justice system officials access to specific sections of Iowa’s Three Year Plan. It includes the “System Flow, “Crime Analysis”, and “Child in Needs of Assistance” sections of Iowa’s 2006 Juvenile Justice and Delinquency Prevention Act formula grant Three-Year Plan. The complete Three Year Plan serves as Iowa’s application for Juvenile Justice and Delinquency Prevention Act formula grant funding. The information included in this report overviews system processing for delinquent youth. It also provides data and analysis from key system decision pointsand services.

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La mesure traditionnelle de la criminalité (taux pour 100 000 habitants) pose problème dans l'analyse des variations de la criminalité dans le temps ou l'espace. Le problème est dû au fait que le taux de criminalité est essentiellement déterminé par des infractions moins graves et très fréquentes. La présente étude a permis de tester l’utilité du nouvel outil développé par Statistique Canada qui procure un index de « gravité de la criminalité » dans lequel chaque crime est pondéré par son score de gravité (basé sur les décisions sentencielles moyennes au Canada de 2002 à 2007 pour chaque forme de crime). Appliquées aux statistiques officielles du Québec de 1977 à 2008, nos analyses montrent que l’indice de gravité s’avère une mesure utile pour dresser un portrait plus juste des tendances des crimes violents d’une année à l’autre. Plus exactement, l’indice de gravité montre que le taux de crimes violents est demeuré stable de 1977 à 1992 contrairement à l'image fournie par le taux traditionnel qui montre plutôt une montée fulgurante durant cette période. L’indice de gravité peut également être utile à l’égard des crimes violents pour comparer plus adéquatement les territoires entre eux afin d’établir ceux qui présentent une criminalité plus grave. Cependant, à l’égard de la criminalité globale et des crimes sans violence, l’indice de gravité n’est d’aucune utilité et présente la même lecture de la criminalité que la mesure traditionnelle. Cela s’explique par le fait que ce sont toujours les mêmes infractions (les vols, les méfaits et les introductions par effraction) qui contribuent majoritairement à chacune des deux mesures de la criminalité.