Search results for "BS"
showing 10 items of 20952 documents
Iterated greedy with variable neighborhood search for a multiobjective waste collection problem
2020
Abstract In the last few years, the application of decision making to logistic problems has become crucial for public and private organizations. Efficient decisions clearly contribute to improve operational aspects such as cost reduction or service improvement. The particular case of waste collection service considered in this paper involves a set of economic, labor and environmental issues that translate into difficult operational problems. They pose a challenge to nowadays optimization technologies since they have multiple constraints and multiple objectives that may be in conflict. We therefore need to resort to multiobjective approaches to model and solve this problem, providing efficie…
Scale invariant line matching on the sphere
2013
International audience; This paper proposes a novel approach of line matching across images captured by different types of cameras, from perspective to omnidirectional ones. Based on the spherical mapping, this method utilizes spherical SIFT point features to boost line matching and searches line correspondences using an affine invariant measure of similarity. It permits to unify the commonest cameras and to process heterogeneous images with the least distortion of visual information.
Sensorless Speed Control for Double-Sided Linear Induction Motor Applications
2019
In this work, a flux and speed observer for double-sided linear induction motor applications is presented and experimentally validated. More in detail, from a Double-Sided Linear Induction Motor (DLIM) prototype, the complete modelling and the determination of the related parameters are here reported. Furthermore, the equations for a d-flux and q-flux observer are conceived and several simulation tests are performed. From the good agreements between the trends over time of the speed estimated by the observer and the simulated one, it can be stated that the observer is well designed. Moreover, in order to experimentally validate the proposed observer, a test bench is set-up for the DLIM/obse…
Networked Bio-Inspired Evolutionary Dynamics on a Multi-Population
2019
We consider a multi-population, represented by a network of groups of individuals. Every player of each group can choose between two options, and we study the problem of reaching consensus. The dynamics not only depend on the dynamics within the group, but they also depend on the topology of the network, so neighboring groups influence individuals as well. First, we develop a mathematical model of this networked bio-inspired evolutionary behavior and we study its steady-state. We look at the special case where the underlying network topology is a regular and unweighted graph and show that the steady-state is a consensus equilibrium. A sufficient condition for exponential stability is given.…
Graph-theoretical derivation of brain structural connectivity
2020
Brain connectivity at the single neuron level can provide fundamental insights into how information is integrated and propagated within and between brain regions. However, it is almost impossible to adequately study this problem experimentally and, despite intense efforts in the field, no mathematical description has been obtained so far. Here, we present a mathematical framework based on a graph-theoretical approach that, starting from experimental data obtained from a few small subsets of neurons, can quantitatively explain and predict the corresponding full network properties. This model also changes the paradigm with which large-scale model networks can be built, from using probabilisti…
Gradient-based time to contact on paracatadioptric camera
2013
International audience; The problem of time to contact or time to collision (TTC) estimation is largely discussed in perspective images. However, a few works have dealt with images of catadioptric sensors despite of their utility in robotics applications. The objective of this paper is to develop a novel model for estimating TTC with catadioptric images relative to a planar surface, and to demonstrate that TTC can be estimated only with derivative brightness and image coordinates. This model, called "gradient based time to contact", does not need high processing such as explicit estimation of optical flow and feature detection/or tracking. The proposed method allows to estimate TTC and give…
Types of Mimetics for the Design of Intelligent Technologies
2019
Mimetic design means using a source in the natural or artificial worlds as an inspiration for technological solutions. It is based around the abstraction of the relevant operating principles in a source domain. This means that one must be able to identify the correct level of analysis and extract the relevant patterns. How this should be done is based on the type of source. From a mimetic perspective, if the design goal is intelligent technology, an obvious source of inspiration is human information processing, which we have called cognitive mimetics. This article offers some conceptual clarification on the nature of cognitive mimetics by contrasting it with biomimetics in the context of in…
A Hybrid Control Strategy for Quadratic Boost Converters with Inductor Currents Estimation
2020
International audience; This paper deals with a control strategy for a DC-DC quadratic boost converter. In particular, a hybrid control scheme is proposed to encompass a control law and an observer for the estimation of the system states, based only on the measurements of the input and output voltages. Differently from classical control methods, where the controller is designed from a small-signal model, here the real model of the system is examined without considering the average values of the discrete variables. Using hybrid dynamical system theory, asymptotic stability of a neighborhood of the equilibrium point is established, ensuring practical stability of the origin, which contains es…
Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?
2020
Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…
Comparison of fully non-stationary artificial accelerogram generation methods in reproducing seismicity at a given site
2020
Abstract Seismic input modelling is a crucial step when Non-Linear Time-History Analyses (NLTHAs) are performed, the seismic response of structures being highly responsive to the input employed. When natural accelerograms able to represent local seismicity are not available, the use of generated accelerograms is an efficient solution for input modelling. The aim of the present paper is to compare four methods for generating fully non-stationary artificial accelerograms on the basis of a target spectrum, identified using seven recorded accelerograms registered in the neighbourhood of the construction site during a single event, assumed as target accelerograms. For each method, seven accelero…