Dynamiques d’intimidation contre la force publique : enjeux pour les policiers et les agents correctionnels

Une des caractéristiques fondamentales des policiers et des agents correctionnels est le recours légitime à la coercition pour imposer leur autorité. Cette force publique doit donc, en théorie, avoir le dessus sur toute forme de force privée. Dans l’étude des phénomènes de violence, cette caractéristique rend leur victimisation singulière. À ce jour, les formes d’influence, de pressions indues et d’intimidation vécus par les agents de la force publique demeurent relativement peu étudiées. Les objectifs de cette thèse sont d’améliorer notre compréhension des dynamiques d’intimidation, de soulever les différents enjeux pour la force publique et de proposer une théorie de l’intimidation criminelle. La force publique étant, avant toute chose, une émanation de l’État, nous avons commencé par analyser la problématique de l’intimidation criminelle de manière plus globale. En testant la théorie de l’action de sécurité (Cusson, 2010), nous avons constaté qu’une force publique intimidée et corrompue entraîne une perte de légitimité et une inefficacité du système judiciaire dans sa lutte contre la criminalité. Nous avons ensuite adopté une perspective interactionniste pour comprendre les dynamiques d’intimidation au quotidien. Nous nous sommes demandés quels étaient les éléments qui rendaient une intimidation crédible et grave pour les policiers. En identifiant leur monde d’objets (Blumer, 1986), nous avons constaté que les actes d’intimidation qui survenaient en dehors du cadre professionnel étaient jugés plus graves par les policiers et que l’appartenance de l’intimidateur à une organisation criminelle entraînait une augmentation de la gravité de la menace. Ensuite, nous nous sommes interrogés sur la notion d’identité sociale des agents correctionnels victimes d’intimidation (Tedeschi et Felson, 1994). Nous avons constaté que les intimidations mineures mais répétées avaient tendance à modifier les pratiques professionnelles des surveillants. Une analyse intégrée de ces perspectives met en lumière l’existence de deux formes d’intimidation : une intimidation réactive et peu sévère en nature et une intimidation planifiée et grave. Elle soulève également trois enjeux pour la force publique : son aspect symbolique, la transformation de son action et sa légitimité. En intégrant ces enjeux, une théorie de l’intimidation criminelle est proposée. En dernier lieu, des solutions préventives et répressives sont avancées pour lutter contre ce phénomène.

Salient Features of the North Indian Ocean Associated with the Indian summer Monsoon

This study deals with the salient features of the north Indian ocean associated with the summer monsoon. The focus is given on the Arabian sea mini warm pool, which is a part of the Indian ocean. It primarily study the certain aspects of the atmosphere and ocean variability in the north Indian ocean. The attempt were made to understand various aspects of time –scale variability of major features occurring in the Indian summer monsoon. The result from the thesis can be utilized as an input for model studies for prediction of monsoon, understanding ocean dynamics, radar tracking and ranging etc.

Salient Features of the North Indian Ocean Associated with the Indian summer Monsoon

This study deals with the salient features of the north Indian ocean associated with the summer monsoon. The focus is given on the Arabian sea mini warm pool, which is a part of the Indian ocean. It primarily study the certain aspects of the atmosphere and ocean variability in the north Indian ocean. The attempt were made to understand various aspects of time –scale variability of major features occurring in the Indian summer monsoon. The result from the thesis can be utilized as an input for model studies for prediction of monsoon, understanding ocean dynamics, radar tracking and ranging etc.

"Strictly models and objects first" - Unterrichtskonzept und -methodik für objektorientierte Modellierung im Informatikunterricht

Objektorientierte Modellierung (OOM) im Unterricht ist immer noch ein breit diskutiertes Thema - in der Didaktik akzeptiert und gewünscht, von der Praxis oft als unnötiger Overhead oder als schlicht zu komplex empfunden. Ich werde in dieser Arbeit zeigen, wie ein Unterrichtskonzept aufgebaut sein kann, das die lerntheoretischen Vorteile der OOM nutzt und dabei die berichteten Schwierigkeiten größtenteils vermeidet. Ausgehend von den in der Literatur dokumentierten Konzepten zur OOM und ihren Kritikpunkten habe ich ein Unterrichtskonzept entwickelt, das aus Erkenntnissen der Lernpsychologie, allgemeiner Didaktik, Fachdidaktik und auch der Softwaretechnik Unterrichtsmethoden herleitet, um den berichteten Schwierigkeiten wie z.B. dem "Lernen auf Vorrat" zu begegnen. Mein Konzept folgt vier Leitideen: models first, strictly objects first, Nachvollziehbarkeit und Ausführbarkeit. Die strikte Umsetzung dieser Ideen führte zu einem Unterrichtskonzept, das einerseits von Beginn an das Ziel der Modellierung berücksichtigt und oft von der dynamischen Sicht des Problems ausgeht. Da es weitgehend auf der grafischen Modellierungsebene verbleibt, werden viele Probleme eines Programmierkurses vermieden und dennoch entstehen als Ergebnis der Modellierung ausführbare Programme.

Generating Compliant Motion of Objects with an Articulated Hand

The flexibility of the robot is the key to its success as a viable aid to production. Flexibility of a robot can be explained in two directions. The first is to increase the physical generality of the robot such that it can be easily reconfigured to handle a wide variety of tasks. The second direction is to increase the ability of the robot to interact with its environment such that tasks can still be successfully completed in the presence of uncertainties. The use of articulated hands are capable of adapting to a wide variety of grasp shapes, hence reducing the need for special tooling. The availability of low mass, high bandwidth points close to the manipulated object also offers significant improvements I the control of fine motions. This thesis provides a framework for using articulated hands to perform local manipulation of objects. N particular, it addresses the issues in effecting compliant motions of objects in Cartesian space. The Stanford/JPL hand is used as an example to illustrate a number of concepts. The examples provide a unified methodology for controlling articulated hands grasping with point contacts. We also present a high-level hand programming system based on the methodologies developed in this thesis. Compliant motion of grasped objects and dexterous manipulations can be easily described in the LISP-based hand programming language.

Computer Analysis of Visual Properties of Curved Objects

A method is presented for the visual analysis of objects by computer. It is particularly well suited for opaque objects with smoothly curved surfaces. The method extracts information about the object's surface properties, including measures of its specularity, texture, and regularity. It also aids in determining the object's shape. The application of this method to a simple recognition task ??e recognition of fruit ?? discussed. The results on a more complex smoothly curved object, a human face, are also considered.

Learning Commonsense Categorical Knowledge in a Thread Memory System

If we are to understand how we can build machines capable of broad purpose learning and reasoning, we must first aim to build systems that can represent, acquire, and reason about the kinds of commonsense knowledge that we humans have about the world. This endeavor suggests steps such as identifying the kinds of knowledge people commonly have about the world, constructing suitable knowledge representations, and exploring the mechanisms that people use to make judgments about the everyday world. In this work, I contribute to these goals by proposing an architecture for a system that can learn commonsense knowledge about the properties and behavior of objects in the world. The architecture described here augments previous machine learning systems in four ways: (1) it relies on a seven dimensional notion of context, built from information recently given to the system, to learn and reason about objects' properties; (2) it has multiple methods that it can use to reason about objects, so that when one method fails, it can fall back on others; (3) it illustrates the usefulness of reasoning about objects by thinking about their similarity to other, better known objects, and by inferring properties of objects from the categories that they belong to; and (4) it represents an attempt to build an autonomous learner and reasoner, that sets its own goals for learning about the world and deduces new facts by reflecting on its acquired knowledge. This thesis describes this architecture, as well as a first implementation, that can learn from sentences such as ``A blue bird flew to the tree'' and ``The small bird flew to the cage'' that birds can fly. One of the main contributions of this work lies in suggesting a further set of salient ideas about how we can build broader purpose commonsense artificial learners and reasoners.

How are Three-Deminsional Objects Represented in the Brain?

We discuss a variety of object recognition experiments in which human subjects were presented with realistically rendered images of computer-generated three-dimensional objects, with tight control over stimulus shape, surface properties, illumination, and viewpoint, as well as subjects' prior exposure to the stimulus objects. In all experiments recognition performance was: (1) consistently viewpoint dependent; (2) only partially aided by binocular stereo and other depth information, (3) specific to viewpoints that were familiar; (4) systematically disrupted by rotation in depth more than by deforming the two-dimensional images of the stimuli. These results are consistent with recently advanced computational theories of recognition based on view interpolation.

Component based recognition of objects in an office environment

We present a component-based approach for recognizing objects under large pose changes. From a set of training images of a given object we extract a large number of components which are clustered based on the similarity of their image features and their locations within the object image. The cluster centers build an initial set of component templates from which we select a subset for the final recognizer. In experiments we evaluate different sizes and types of components and three standard techniques for component selection. The component classifiers are finally compared to global classifiers on a database of four objects.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Embedding objects into Matlab/Simulink for process supervision

This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

CETL's Re-Usable Learning Objects

Completed, available and free to use Learning Objects listed by subject area

Lecture 3 - Objects Ahoy

Variables - Objects and Primitives, Quick look at scope