1,721,004 research outputs found
A scanning LiDAR for long range detection and tracking of UAVs
No full textL'utilisation abusive de drones civils est une préoccupation croissante depuis ces dernières années. En réponse, de multiples systèmes basés sur des technologies optiques, électroniques et même acoustiques ont été développés pour la détection et la poursuite de ces drones. Cela représente néanmoins un challenge en raison de leur faible taille et de leur grande diversité de formes et de trajectoire. Afin de répondre à ce besoin pour des distances allant jusqu'au kilomètre, nous avons recherché, développé et optimisé un système LiDAR (light detection and ranging) à balayage. Dans notre système, la mesure de distance est réalisée via le principe du temps de vol, et l'imagerie est effectuée en scannant séquentiellement la scène en utilisant un système de miroir galvanométrique à deux axes. Nous avons profité de la polyvalence du système de balayage pour développer plusieurs modes de fonctionnement. Un mode de détection classique réalise l'image de la scène à l'aide d'un balayage ligne par ligne de type grand champ. Le mode de suivi est basé sur un motif local entourant la cible, qui est mis à jour à une très haute cadence afin de maintenir la cible dans les limites de ce motif. Nous avons réalisé une étude d'optimisation, théorique et numérique, des nombreux paramètres impliqués dans le balayage LiDAR afin d'atteindre des performances suffisantes en termes de portée maximale, de résolution et de fréquence de localisation. L'optimisation des modèles pour les modes de détection et de poursuite a été le principal focus, en utilisant la probabilité de détection cible comme fonction à maximiser. La taille, la vitesse et la réflectivité de la cible ont également été incluses dans la probabilité de détection, donnant un aperçu complet des performances du système. Sur la plateforme LiDAR, chaque composant a été caractérisé afin d'enrichir et de valider nos modèles. Cette plateforme a été testée durant plusieurs semaines d'essais, au cours desquelles nous avons réalisé la détection et la poursuite de divers types de drones. S'en est suivi un processus d'intégration pré-industrielle des chaînes optiques, électroniques et algorithmiques.Misuse of civil drones, or UAVs (unmanned aerial vehicles) has been a rising concern in the past few years. As a response, multiple systems including optics, electronics and even acoustics technologies have been developed for detection and tracking. Unfortunately, UAVs represent a challenging target to detect and track due to their small, decimetric size and large variability of shapes and behaviors. In this PhD, we developed and optimized a LiDAR (light detection and ranging) system to tackle this issue to distances up to a kilometer. In our system, range is acquired using the time of flight principle, and imagery done by sequentially scanning the scene with a dual-axis galvanometer. We took advantage of the scanning versatility to develop several operating modes. A standard detection mode captures the image of the scene using a raster-scan of large _eld of view. Tracking mode is based on a local pattern surrounding the target, which is updated at a very high rate to keep the target within its boundaries. Efforts were put into a theoretical and numerical optimization study of the numerous parameters involved in our scanning LiDAR, so as to reach su_cient performances in term of maximal range, localization resolution and rate. Pattern optimization for both detection and tracking mode was a primary focus, using the target probability of detection as the function to maximize. Target size, speed and re_ectivity was also introduced in the probability of detection, giving a complete overview of the system performance. On our LiDAR platform, developed from the ground up, each component was characterized to enrich and validate our models. This prototype was tested for UAVs detection and tracking during several weeks of trials. Following this success, a pre-industrial integration process was launched and supervised by the candidate
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Οnbοard/οffbοard extended perceptiοn fοr autοnοmοus navigatiοn
No full textAvec l'arrivée de la navigation autonome, la perception de l'environnement dans lequel évoluent les véhicules est une tâche primordiale. Pour répondre à cette problématique, les véhicules se sont dotés de plus en plus de capteurs pour percevoir leur environnement. Plus récemment, nous pouvons observer l'apparition d'approches coopératives afin d'outrepasser les limitations des capteurs embarqués.Dans cette thèse, nous faisons un état de l'art des méthodes de perceptions coopératives dans le contexte automobile. Nous y discutons des architectures fréquemment utilisées et des défis qu'elles entraînent. Nous étudions aussi les méthodes de localisation, de détection et suivis ainsi que les méthodes de cartographies coopératives avant de lister les projets et les scénarii dans lesquels la perception coopérative est utilisée aujourd'hui.En réponse à cet état de l'art, nous avons mis au point une nouvelle architecture coopérative fusionnant les approches Véhicules-Véhicules et Véhicule-Infrastructure actuelles et basée sur l'utilisation de données issues des véhicules et des infrastructures. Cette approche nous permet dans un premier temps de générer des grilles d'occupation des objets dynamiques d'une scène en utilisant uniquement des données limitées issues des caméras. Nous ajoutons ensuite à cette approche un aspect sémantique permettant la création de grilles sémantiques. Afin de fusionner les données issues des différents points de vues, nous avons testé deux méthodes : l'une basée sur la théorie bayésienne et l'autre sur la théorie de Dempster-Shafer.Les résultats sont obtenus à partir de jeux de données de notre conception et montrent des résultats inatteignables par les méthodes de l'état de l'art aujourd'hui ainsi qu'une supériorité de la méthode basée sur la théorie de Dempster-Shafer.With the emergence of autonomous navigation, the perception of the environment in which vehicles evolve is a primordial task. To address this issue, vehicles have increasingly been equipped with sensors to perceive their environment. Recently, we can observe the emergence of cooperative approaches to overcome the limitations of onboard sensors.In this thesis, we present a state-of-the-art of cooperative perception methods in the automotive context. We discuss the frequently used architectures and the challenges they entail. We also study localization, detection and tracking methods as well as cooperative mapping methods before listing the projects and scenarios in which cooperative perception is used today.As a response to this state-of-the-art, we have developed a new cooperative architecture merging the current Vehicle-Vehicle and Vehicle-Infrastructure approaches based on the use of data from vehicles and infrastructures. This approach allows us to generate dynamic object occupancy grids of a scene using only limited camera data. We then add to this approach a semantic aspect allowing the creation of semantic grids. To merge the data from the different points of view, we evaluated two methods: one based on the Bayesian theory and the other on the Dempster-Shafer theory.The results are obtained from datasets of our own design and show results unattainable by state-of-the-art methods today as well as a superiority of the method based on the Dempster-Shafer theory
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
- …
