The ArgoNeuT Detector in the NuMI Low-Energy beam line at Fermilab

The ArgoNeuT liquid argon time projection chamber has collected thousands of neutrino and antineutrino events during an extended run period in the NuMI beam-line at Fermilab. This paper focuses on the main aspects of the detector layout and related technical features, including the cryogenic equipment, time projection chamber, read-out electronics, and off-line data treatment. The detector commissioning phase, physics run, and first neutrino event displays are also reported. The characterization of the main working parameters of the detector during data-taking, the ionization electron drift velocity and lifetime in liquid argon, as obtained from through-going muon data complete the present report.Comment: 43 pages, 27 figures, 5 tables - update referenc

A Bayesian Approach For Image-Based Underwater Target Tracking And Navigation [TC1800. A832 2007 f rb].

Operasi pemeriksaan dan pemantauan di dasar laut merupakan aktiviti penting untuk industri di luar persisiran pantai terutamanya bagi tujuan pembangunan dan pemasangan infrastruktur. Sejak kebelakangan ini, pemasangan struktur di dasar laut seperti saluran paip gas atau petroleum dan kabel telekomunikasi telah meningkat. Pemeriksaan rutin adalah sangat mustahak untuk mencegah kerosakan. Undersea inspections and surveys are important requirements for offshore industry and mining organisation for various infra-structures installations. During the last decade, the use of underwater structure installations, such as oil or gas pipeline and telecommunication cables has increased many folds

Object detection and tracking using a parts-based approach

One of the main goals of artificial intelligence is to allow computers to understand the world around them. As humans we extract a large amount of knowledge about the world from our visual perception, and the field of computer vision is determined to give computers access to this same wealth of knowledge. One of the fundamental steps in understanding the world is finding specific objects within our field of view, and the related task of following these objects as they move. In this thesis the Implicit Shape Model algorithm, a local feature-based object detection algorithm, is implemented and used to develop an appearance model and object tracking algorithm based on it. This algorithm is very robust to intraclass variation, and can successfully track objects when both occlusion and non-stationary backgrounds are present. The usefulness of the proposed appearance model is analyzed, and results of the algorithm on real video sequences are presented. Several enhancements to the method are also proposed, and performance in terms of recall and precision is analyzed

Stereo Vision Tracking of Multiple Objects in Complex Indoor Environments

This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot’s environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors’ proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found

Filamentous phages as building blocks for reconfigurable and hierarchical self-assembly

Filamentous bacteriophages such as fd-like viruses are monodisperse rod-like colloids that have well defined properties: diameter, length, rigidity, charge and chirality. Engineering those viruses leads to a library of colloidal rods which can be used as building blocks for reconfigurable and hierarchical self-assembly. Their condensation in aqueous solution \th{with additive polymers which act as depletants to induce} attraction between the rods leads to a myriad of fluid-like micronic structures ranging from isotropic/nematic droplets, colloid membranes, achiral membrane seeds, twisted ribbons, $\pi$-wall, pores, colloidal skyrmions, M\"obius anchors, scallop membranes to membrane rafts. Those structures and the way they shape shift not only shed light on the role of entropy, chiral frustration and topology in soft matter but it also mimics many structures encountered in different fields of science. On one hand, filamentous phages being an experimental realization of colloidal hard rods, their condensation mediated by depletion interactions constitutes a blueprint for self-assembly of rod-like particles and provides fundamental foundation for bio- or material oriented applications. On the other hand, the chiral properties of the viruses restrict the generalities of some results but vastly broaden the self-assembly possibilities

PixelTrack: A Fast Adaptive Algorithm for Tracking Non-rigid Objects

International audienceIn this paper, we present a novel algorithm for fast tracking of generic objects in videos. The algorithm uses two components: a detector that makes use of the generalised Hough transform with pixel-based descriptors, and a probabilistic segmentation method based on global models for foreground and background. These components are used for tracking in a combined way, and they adapt each other in a co-training manner. Through effective model adaptation and segmentation, the algorithm is able to track objects that undergo rigid and non-rigid deformations and considerable shape and appearance variations. The proposed tracking method has been thoroughly evaluated on challenging standard videos, and outperforms state-of-theart tracking methods designed for the same task. Finally, the proposed models allow for an extremely efficient implementation, and thus tracking is very fast