Territorialización de la inseguridad ciudadana en Bogotá: La Calle del Bronx

La tesis devela la connotación sistemática y multicausal de lo que a través de la investigación se denomina como "Procesos de Territorialización de la Inseguridad Ciudadana". Mediante un estudio de caso, se pone en evidencia la apropiación y captura sostenida en el tiempo de fenómenos como la inseguridad y la criminalidad, sobre determinadas zonas o barrios urbanos que por sus características socioeconómicas, políticas, geográficas, culturales, laborales y de mercado de quienes los habitan o frecuentan, se consideran como sectores "críticos y/o vulnerables".

Delitos de posición y delitos con elementos de autoría meramente tipificadores: nuevas bases para una distinción necesaria.

El presente trabajo tiene por objeto dar respuesta a tres de las principales cuestiones concernientes a la teoría general de los delitos especiales. En primer lugar, se trata de conocer en qué consiste esta categoría delictiva. Esto es, abundar en el concepto de delito especial. En segunda instancia, resulta obligado saber cuál es el fundamento material de la restricción del círculo de posibles autores que caracteriza a los delitos especiales. Y, por último, es preciso preguntarse si el extraneus que participa en un delito especial debe responder penalmente, y, en caso afirmativo, si debe hacerlo con la misma pena que el intraneus o bien con una pena atenuada. Todo ello se desarrollará con especial atención al actual art. 65.3 CP, el precepto que nació con la vocación de dar respuesta, al menos en parte, a las cuestiones que han sido formuladas, y que tanta controversia viene generando en la doctrina española prácticamente desde el momento en que entró en vigor.

Um estudo sobre a vitimização para a cidade de São Paulo

A study about the victimization in the city of São Paulo. This paper applies the crime economics theory to Brazilian data. Following Becker (1968), Hinderlang et al. (1978) and Cohen et al. (1981), we tested the microeconomic factors that influence crime and victimization. For this end, the two waves of research of victimization of the Instituto Futuro Brasil, 2003 and 2008, were used in an effort to identify the determinants of victimization and police notification, using probit model. The main results suggest the factors which impact significantly the probability of victimization are the demographic characteristics, economic conditions and personal habits. The models of "life style" and "opportunity" seem to have good performance.

L’écosystème des crimes de bars de danse érotique québécois

Il existe des associations entre les bars de danse érotique et les activités illicites, dans les écrits journalistiques et scientifiques. Nous avons vérifié ces associations en menant une description des crimes et déviances associés aux bars de danse érotique. Puis, nous avons tenté d’expliquer l’organisation et la structure de ces crimes, en nous appuyant sur l’approche du crime organisant et la théorie de l’écosystème du crime, de Felson (2006). Des entretiens semi-dirigés ont été conduits avec dix femmes danseuses, une femme shooter girl, un propriétaire, un portier et deux clients. Une analyse thématique à deux niveaux a montré que les délits se rapportent aux stupéfiants, à la prostitution, au proxénétisme, aux déviances, et à divers actes de violence. Des distinctions importantes, quant au contrôle selon les établissements sont notées. La structure et l’organisation des crimes peuvent s’expliquer par une logique propre aux relations symbiotiques et interdépendantes, tel que le suggère la théorie de l’écosystème du crime de Felson. Ainsi, la structure des délits peut prendre une forme mutualiste ou parasitaire. L’interrelation propre au neutralisme explique l’organisation générale de ces délits. Le milieu criminogène de la danse érotique offre de multiples opportunités, qui seront saisies par les acteurs motivés, en vue de réaliser un bénéfice personnel. Deux constats étonnants : les données suggèrent que l’implication des organisations criminelles est relativement limitée; et les conséquences occasionnées par les activités du milieu présentent un caractère inquiétant, particulièrement pour les femmes. Des efforts en matière de prévention situationnelle seraient appropriés pour réduire les opportunités.

Les éléments entourant le passage à l'acte sous forme de co-délinquance au Québec

Les premières études recensées ayant traité de la co-délinquance ont plus de cent ans. Comme il s’agit d’un sujet qui a de l’histoire, il y a eu une grande évolution dans la façon d’aborder la question et dans les méthodologies employées. Mais, ce n’est que depuis quelques années que la co-délinquance est étudiée par l’entremise de données d’arrestations policières et c’est ce type de données qui sera utilisé pour répondre à l’objectif principal, celui-ci étant la détermination des conditions expliquant le recours ou non à la co-délinquance pour commettre une infraction criminelle. De plus, pour répondre à notre objectif de recherche, nous avons opté pour une théorie structurante du crime, approche qui n’avait jamais été utilisé auparavant dans les études sur la co-délinquance. Comme méthodologie, nous avons utilisé un échantillon composé de 9 103 participations criminelles, de 8 243 événements distincts et de 3 356 individus et plusieurs prédicteurs ont été analysés afin de déterminer lesquels expliquent le mieux la co-délinquance. L’âge, le genre, les antécédents criminels, l’urbanité et le type de crimes sont toutes des variables qui ont été considérées. L’urbanité représente une nouveauté dans ce type de recherche, puisque nous avons recensé que très peu d’études ayant abordées la question. Alors, que pour le type de crime, nous l’avons détaillé, comme aucune étude sur la co-délinquance ne l’a fait auparavant (23 catégories d’infractions). Ce détail nous permet donc de bien cibler l’impact de chaque délit sur le recours à la co-délinquance. Le résultat émergeant des analyses de régression logistique est que le recours à la co-délinquance s’explique principalement par le type de crime commis, certains actes criminels sont plus propices à la co-délinquance que d’autres. Nous constatons également que les autres variables analysées ont très peu ou pas d’impact sur le recours à la co-délinquance, que ce soit l’âge, le genre, les antécédents criminels ou même l’urbanité.

Systemological Knowledge-based Technology for Solving Complete Ill-structured Problems

Original method and technology of systemological «Unit-Function-Object» analysis for solving complete ill-structured problems is proposed. The given visual grapho-analytical UFO technology for the fist time combines capabilities and advantages of the system and object approaches and can be used for business reengineering and for information systems design. UFO- technology procedures are formalized by pattern-theory methods and developed by embedding systemological conceptual classification models into the system-object analysis and software tools. Technology is based on natural classification and helps to investigate deep semantic regularities of subject domain and to take proper account of system-classes essential properties the most objectively. Systemological knowledge models are based on method which for the first time synthesizes system and classification analysis. It allows creating CASE-toolkit of a new generation for organizational modelling for companies’ sustainable development and competitive advantages providing.

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Institutions, Anomie, and Violent Crime: Clarifying and Elaborating Institutional-Anomie Theory

A limited but accumulating body of research and theoretical commentary offers support for core claims of the “institutional-anomie theory” of crime (IAT) and points to areas needing further development. In this paper, which focuses on violent crime, we clarify the concept of social institutions, elaborate the cultural component of IAT, derive implications for individual behavior, summarize empirical applications, and propose directions for future research. Drawing on Talcott Parsons, we distinguish the “subjective” and “objective” dimensions of institutional dynamics and discuss their interrelationship. We elaborate on the theory’s cultural component with reference to Durkheim’s distinction between “moral” and “egoistic” individualism and propose that a version of the egoistic type characterizes societies in which the economy dominates the institutional structure, anomie is rampant, and levels of violent crime are high. We also offer a heuristic model of IAT that integrates macro- and individual levels of analysis. Finally, we discuss briefly issues for the further theoretical elaboration of this macro-social perspective on violent crime. Specifically, we call attention to the important tasks of explaining the emergence of economic dominance in the institutional balance of power and of formulating an institutional account for distinctive punishment practices, such as the advent of mass incarceration in the United States.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

Information-theory analysis of skewed coding for suppression of pattern-dependent errors in digital communications

We present information-theory analysis of the tradeoff between bit-error rate improvement and the data-rate loss using skewed channel coding to suppress pattern-dependent errors in digital communications. Without loss of generality, we apply developed general theory to the particular example of a high-speed fiber communication system with a strong patterning effect. © 2007 IEEE.

Resource use pattern analysis for predicting resource availability in opportunistic grids

This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

Career development and systems theory: Connecting theory and practice

The Systems Theory Framework was developed to produce a metatheoretical framework through which the contribution of all theories to our understanding of career behaviour could be recognised. In addition it emphasises the individual as the site for the integration of theory and practice. Its utility has become more broadly acknowledged through its application to a range of cultural groups and settings, qualitative assessment processes, career counselling, and multicultural career counselling. For these reasons, the STF is a very valuable addition to the field of career theory. In viewing the field of career theory as a system, open to changes and developments from within itself and through constantly interrelating with other systems, the STF and this book is adding to the pattern of knowledge and relationships within the career field. The contents of this book will be integrated within the field as representative of a shift in understanding existing relationships within and between theories. In the same way, each reader will integrate the contents of the book within their existing views about the current state of career theory and within their current theory-practice relationship. This book should be required reading for anyone involved in career theory. It is also highly suitable as a text for an advanced career counselling or theory course.