Search results for "DATA"
showing 10 items of 12992 documents
Interrogating witnesses for geometric constraint solving
2012
International audience; Classically, geometric constraint solvers use graph-based methods to decompose systems of geometric constraints. These methods have intrinsic limitations, which the witness method overcomes; a witness is a solution of a variant of the system. This paper details the computation of a basis of the vector space of free infinitesimal motions of a typical witness, and explains how to use this basis to interrogate the witness for dependence detection. The paper shows that the witness method detects all kinds of dependences: structural dependences already detectable by graph-based methods, but also non-structural dependences, due to known or unknown geometric theorems, which…
GRASP and tabu search for the generalized dispersion problem
2021
Abstract The problem of maximizing dispersion requires the selection of a specific number of elements from a given set, in such a way that the minimum distance between the pairs of selected elements is maximized. In recent years, this problem has received a lot of attention and has been solved with many complex heuristics. However, there is a recent variant in which the selected elements have to satisfy two realistic constraints, a minimum capacity limit and a maximum budget, which in spite of its practical significance in facility location, has received little attention. In this paper, we first propose mathematical models to obtain the optimal solution of small- and medium-size instances, …
JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES
2018
In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By leveraging the Kalman filter framework, a three steps iterative algorithm is utilized to predict and update signal estimation as well as graph topology learning, called Topological Kalman Filter or TKF. Similar to the regular Kalman filter, we first predict the a posterior signal state based on the prior available data and then this prediction is updated and corrected based on the recently arrived measurement. But contrary to the conventional Kalman filter algorithm, we have no information of the transition matrix and hence we relate t…
Online dimensional control of rolled steel profiles using projected fringes
2020
AbstractFringe projection is a versatile method for mapping the topography of surfaces. In this paper, it is used to measure the defects on the head of railroad rails while the rails are moving. Railroad rails are made by hot rolling. The quality of the finished product is generally good, but surface texture will deteriorate with increasing temperature. A method for online inspection therefore is very desirable. In the present experiment, dimensional inspection of the railroad rails was made online while moving at a speed of 1–2 m/s. Therefore, it is important to minimize the registration time. To achieve this, we apply a method of fringe location with sub-pixel accuracy that requires only …
Time-varying Sampled-data Observer with Asynchronous Measurements
2019
International audience; In this paper a time-varying observer for a linear continuous-time plant with asynchronous sampled measurements is proposed. The observer is contextualized in the hybrid systems framework providing an elegant setting for the proposed solution. In particular some theoretical tools are provided, in terms of LMIs, certifying asymptotic stability of a certain compact set where the estimation error is zero. We consider sampled asynchronous measurements that occur at arbitrary times in a certain window with an upper and lower bound. The design procedure, that we propose for the selection of the time-varying gain, is based on a constructive algorithm that is guaranteed to f…
Calibration of mobile manipulators using 2D positional features.
2018
International audience; Robotic manipulators are increasingly being attached to Automatic Ground Vehicles (AGVs) to aid in the efficiency of assembly for manufacturing systems. However, calibrating these mobile manipulators is difficult as the offset between the robotic manipulator and the AGV is often unknown. This paper provides a novel, simple, and low-cost method for calibrating and measuring the performance of mobile manipulators by using data collected from a laser retroreflector that digitally detects the horizontal two-dimensional (2D) position of reflectors on an artifact as well as a navigation system that provides the heading angle and 2D position of the AGV. The method is mathem…
Buckling and post-buckling analysis of cracked stiffened panels via an X-Ritz method
2019
Abstract A multi-domain eXtended Ritz formulation, called X-Ritz, for the analysis of buckling and post-buckling of stiffened panels with cracks is presented. The theoretical framework is based on the First-order Shear Deformation Theory and accounts for von Karman's geometric nonlinearities. The structure is modeled as assembly of plate elements. Penalty techniques are used to fulfill the continuity condition along the edges of contiguous elements and to satisfy essential boundary conditions requirements. The use of an extended set of approximating functions allows to model through-the-thickness cracks and to capture the crack opening and tip singular fields as well as the structural behav…
A Meta-Model for Intelligent Engineering Design of Complex City
2019
A city is a complex system, requiring the input of multiple disciplines for its (re)design. It shares some properties of two kinds of objects: empirical objects as well as theoretical objects. As city emerges as a complex object for multi-disciplinary studies, it is of the highest importance to adopt a systemic and global approach in order to bring new knowledge to this field. To master the growing complexity of cities and to consider in the same spot heterogeneous ways of thinking of city, we need intellectual tools and models. The goal of this paper is to propose a model for describing engineering modelling knowledge with relationships and transformations between four domains: (1) citizen…
Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics
2016
To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This pape…
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…