Search results for "Processing"
showing 10 items of 8572 documents
Scalable implementation of measuring distances in a Riemannian manifold based on the Fisher Information metric
2019
This paper focuses on the scalability of the Fisher Information manifold by applying techniques of distributed computing. The main objective is to investigate methodologies to improve two bottlenecks associated with the measurement of distances in a Riemannian manifold formed by the Fisher Information metric. The first bottleneck is the quadratic increase in the number of pairwise distances. The second is the computation of global distances, approximated through a fully connected network of the observed pairwise distances, where the challenge is the computation of the all sources shortest path (ASSP). The scalable implementation for the pairwise distances is performed in Spark. The scalable…
Cross-correlation of whitened vibration signals for low-speed bearing diagnostics
2019
Abstract Rolling-element bearings are crucial components in all rotating machinery, and their failure will initially degrade the machine performance, and later cause complete shutdown. The period between an initial crack and complete failure is short due to crack propagation. Therefore, early fault detection is important to avoid unexpected machine shutdown and to aid in maintenance scheduling. Bearing condition monitoring has been applied for several decades to detect incipient faults at an early stage. However, low-speed conditions pose a challenge for bearing fault diagnosis due to low fault impact energy. To reliably detect bearing faults at an early stage, a new method termed Whitened …
Extreme minimal learning machine: Ridge regression with distance-based basis
2019
The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…
Vision based attitude and altitude estimation for UAVs in dark environments
2011
This paper presents a system dedicated to the real-time estimation of attitude and altitude for unmanned aerial vehicles (UAV) under low light and dark environment. This system consists in a fisheye camera, which allows to cover a large field of view (FOV), and a laser circle projector mounted on a fixed baseline. The approach, close to structured light systems, uses the geometrical information obtained by the projection of the laser circle onto the ground plane and perceived by the camera. We present a theoretical study of the system in which the camera is modelled as a sphere and show that the estimation of a conic on this sphere allows to obtain the attitude and the altitude of the robot…
Omnidirectional vision for UAV: applications to attitude, motion and altitude estimation for day and night conditions
2012
International audience; This paper presents the combined applications of omnidirectional vision featuring on its application to aerial robotics. Omnidirectional vision is first used to compute the attitude, altitude and motion not only in rural environment but also in the urban space. Secondly, a combination of omnidirectional and perspective cameras permits to estimate the altitude. Finally we present a stereo system consisting of an omnidirectional camera with a laser pattern projector enables to calculate the altitude and attitude during the improperly illuminated conditions to dark environments. We demonstrate that omnidirectional camera in conjunction with other sensors is suitable cho…
BIAM: a new bio-inspired analysis methodology for digital ecosystems based on a scale-free architecture
2017
Today we live in a world of digital objects and digital technology; industry and humanities as well as technologies are truly in the midst of a digital environment driven by ICT and cyber informatics. A digital ecosystem can be defined as a digital environment populated by interacting and competing digital species. Digital species have autonomous, proactive and adaptive behaviors, regulated by peer-to-peer interactions without central control point. An interconnecting architecture with few highly connected nodes (hubs) and many low connected nodes has a scale- free architecture. A new bio-inspired analysis methodology (BIAM) environment, an investigation strategy for information flow, fault…
Towards a Reference Architecture for Archival Systems: Use Case With Product Data
2014
Long-term preservation of product data is imperative for many organizations. A product data archive should be designed to ensure information accessibility and understanding over time. Approaches, such as the Open Archival Information System Reference Model (OAIS RM) and the Audit and Certification of Trustworthy Digital Repositories (ACTDR), provide a framework for conceptually describing and evaluating archives. These approaches are generic and do not focus on particular contexts or content types such as product data. Moreover, these approaches offer no guidance on how to formally and comprehensively describe archival systems. Such descriptions should include the business activities that a…
Visual contact with catadioptric cameras
2015
Abstract Time to contact or time to collision (TTC) is utmost important information for animals as well as for mobile robots because it enables them to avoid obstacles; it is a convenient way to analyze the surrounding environment. The problem of TTC estimation is largely discussed in perspective images. Although a lot of works have shown the interest of omnidirectional camera for robotic applications such as localization, motion, monitoring, few works use omnidirectional images to compute the TTC. In this paper, we show that TTC can be also estimated on catadioptric images. We present two approaches for TTC estimation using directly or indirectly the optical flow based on de-rotation strat…
Hankelet-based action classification for motor intention recognition
2017
Powered lower-limb prostheses require a natural, and an easy-to-use, interface for communicating amputee’s motor intention in order to select the appropriate motor program in any given context, or simply to commute from active (powered) to passive mode of functioning. To be widely accepted, such an interface should not put additional cognitive load at the end-user, it should be reliable and minimally invasive. In this paper we present a one such interface based on a robust method for detecting and recognizing motor actions from a low-cost wearable sensor network mounted on a sound leg providing inertial (accelerometer, gyrometer and magnetometer) data in real-time. We assume that the sensor…
Real-time biomechanical modeling of the liver using Machine Learning models trained on Finite Element Method simulations
2020
[EN] The development of accurate real-time models of the biomechanical behavior of different organs and tissues still poses a challenge in the field of biomechanical engineering. In the case of the liver, specifically, such a model would constitute a great leap forward in the implementation of complex applications such as surgical simulators, computed-assisted surgery or guided tumor irradiation. In this work, a relatively novel approach for developing such a model is presented. It consists in the use of a machine learning algorithm, which provides real-time inference, trained on tens of thousands of simulations of the biomechanical behavior of the liver carried out by the finite element me…