Search results for "Cluster"
showing 10 items of 3640 documents
Static and Dynamic Objects Analysis as a 3D Vector Field
2017
International audience; In the context of scene modelling, understanding, and landmark-based robot navigation, the knowledge of static scene parts and moving objects with their motion behaviours plays a vital role. We present a complete framework to detect and extract the moving objects to reconstruct a high quality static map. For a moving 3D camera setup, we propose a novel 3D Flow Field Analysis approach which accurately detects the moving objects using only 3D point cloud information. Further, we introduce a Sparse Flow Clustering approach to effectively and robustly group the motion flow vectors. Experiments show that the proposed Flow Field Analysis algorithm and Sparse Flow Clusterin…
Reliable diagnostics using wireless sensor networks
2019
International audience; Monitoring activities in industry may require the use of wireless sensor networks, for instance due to difficult access or hostile environment. But it is well known that this type of networks has various limitations like the amount of disposable energy. Indeed, once a sensor node exhausts its resources, it will be dropped from the network, stopping so to forward information about maybe relevant features towards the sink. This will result in broken links and data loss which impacts the diagnostic accuracy at the sink level. It is therefore important to keep the network's monitoring service as long as possible by preserving the energy held by the nodes. As packet trans…
A novel clustering-based algorithm for solving spatially-constrained robotic task sequencing problems
2021
The robotic task sequencing problem (RTSP) appears in various forms across many industrial applications and consists of developing an optimal sequence of motions to visit a set of target points defined in a task space. Developing solutions to problems involving complex spatial constraints remains challenging due to the existence of multiple inverse kinematic solutions and the requirements for collision avoidance. So far existing studies have been limited to relaxed RTSPs involving a small number of target points and relatively uncluttered environments. When extending existing methods to problems involving greater spatial constraints and large sets of target points, they either require subst…
Globally Optimal Line Clustering and Vanishing Point Estimation in Manhattan World
2012
The projections of world parallel lines in an image intersect at a single point called the vanishing point (VP). VPs are a key ingredient for various vision tasks including rotation estimation and 3D reconstruction. Urban environments generally exhibit some dominant orthogonal VPs. Given a set of lines extracted from a calibrated image, this paper aims to (1) determine the line clustering, i.e. find which line belongs to which VP, and (2) estimate the associated orthogonal VPs. None of the existing methods is fully satisfactory because of the inherent difficulties of the problem, such as the local minima and the chicken-and-egg aspect. In this paper, we present a new algorithm that solves t…
Ensuring the Reliability of an Autonomous Vehicle
2017
International audience; In automotive applications, several components, offering different services, can be composed in order to handle one specific task (autonomous driving for example). Nevertheless, component composition is not straightforward and is subject to the occurrence ofbugs resulting from components or services incompatibilities for instance. Hence, bugs detection in component-based systems at thedesign level is very important, particularly, when the developed system concerns automotive applications supporting critical services.In this paper, we propose a formal approach for modeling and verifying the reliability of an autonomous vehicle system, communicatingcontinuously with of…
Selection of time windows in the horizontal-to-vertical noise spectral ratio by means of cluster analysis
2016
The selection of the elementary analysis windows in continuous noise recordings for optimal estimation of the mean horizontal‐to‐vertical spectral ratio (HVSR) curve is generally performed by visual inspection of HVSR curves considered as functions of time. Starting from full‐length records, HVSR curves are determined in consecutive time windows of appropriate lengths. Time windows with HVSR curves that are anomalous on the basis of a simple visual inspection are generally ignored in the computation of the average HVSR curve. It is often very difficult to optimize the selection of time windows to be used for the calculation of the HVSR curve representative of a site. The use of nonobjective…
Novel Autotrophic Organisms Contribute Significantly to the Internal Carbon Cycling Potential of a Boreal Lake
2018
ABSTRACT Oxygen-stratified lakes are typical for the boreal zone and also a major source of greenhouse gas emissions in the region. Due to shallow light penetration, restricting the growth of phototrophic organisms, and large allochthonous organic carbon inputs from the catchment area, the lake metabolism is expected to be dominated by heterotrophic organisms. In this study, we test this assumption and show that the potential for autotrophic carbon fixation and internal carbon cycling is high throughout the water column. Further, we show that during the summer stratification carbon fixation can exceed respiration in a boreal lake even below the euphotic zone. Metagenome-assembled genomes an…
Distinctive Histogenesis and Immunological Microenvironment Based on Transcriptional Profiles of Follicular Dendritic Cell Sarcomas
2017
Abstract Follicular dendritic cell (FDC) sarcomas are rare mesenchymal tumors with variable clinical, morphologic, and phenotypic characteristics. Transcriptome analysis was performed on multiple FDC sarcomas and compared with other mesenchymal tumors, microdissected Castleman FDCs, and normal fibroblasts. Using unsupervised analysis, FDC sarcomas clustered with microdissected FDCs, distinct from other mesenchymal tumors and fibroblasts. The specific endowment of FDC-related gene expression programs in FDC sarcomas emerged by applying a gene signature of differentially expressed genes (n = 1,289) between microdissected FDCs and fibroblasts. Supervised analysis comparing FDC sarcomas with mi…
Virus-encoded microRNA contributes to the molecular profile of EBV-positive Burkitt lymphomas
2015
Burkitt lymphoma (BL) is an aggressive neoplasm characterized by consistent morphology and phenotype, typical clinical behavior and distinctive molecular profile. The latter is mostly driven by the MYC over-expression associated with the characteristic translocation (8;14) (q24; q32) or with variant lesions. Additional genetic events can contribute to Burkitt Lymphoma pathobiology and retain clinical significance. A pathogenetic role for Epstein-Barr virus infection in Burkitt lymphomagenesis has been suggested; however, the exact function of the virus is largely unknown. In this study, we investigated the molecular profiles (genes and microRNAs) of Epstein-Barr virus-positive and -negative…
Exceptional Pattern Discovery
2017
This chapter is devoted to a discussion on exceptional pattern discovery, namely on scenarios, contexts, and techniques concerning the mining of patterns which are so rare or so frequent to be considered as exceptional and, then, of interest for an expert to shed lights on the domain. Frequent patterns have found broad applications in areas like association rule mining, indexing, and clustering [1, 20, 23]. The application of frequent patterns in classification also achieved some success in the classification of relational data [6, 13, 14, 19, 25], text [15], and graphs [7]. The part is organized as follows. First, the frequent pattern mining on classical datasets is presented. This is not …