Search results for " Mach"
showing 10 items of 1388 documents
Simulating Machines: Modelling, Metaphysics and the Mechanosphere
2020
This article explores some of the ways in which the conceptual apparatus of A Thousand Plateaus, and especially its machinic metaphysics, can be connected to recent developments in computer modelling and social simulation, which provide new tools for thinking that are becoming increasingly popular among philosophers and social scientists. Conversely, the successful deployment of these tools provides warrant for the flat ontology articulated in A Thousand Plateaus and therefore contributes to the ‘reversal of Platonism’ for which Deleuze had called in his earlier works, such as Logic of Sense. The first major section offers a brief exposition of some key concepts in A Thousand Plateaus in or…
Design environment for hardware generation of SLFF neural network topologies with ELM training capability
2015
Extreme Learning Machine (ELM) is a noniterative training method suited for Single Layer Feed Forward Neural Networks (SLFF-NN). Typically, a hardware neural network is trained before implementation in order to avoid additional on-chip occupation, delay and performance degradation. However, ELM provides fixed-time learning capability and simplifies the process of re-training a neural network once implemented in hardware. This is an important issue in many applications where input data are continuously changing and a new training process must be launched very often, providing self-adaptation. This work describes a general SLFF-NN design environment to assist in the definition of neural netwo…
Pressure-flow dynamics with semi-stable limit cycles in hydraulic cylinder circuits
2021
In hydraulic circuits of the standard fluid-power actuators and mechanisms, like the linear-stroke cylinders, some hydrodynamic effects are often neglected. It happens mainly due to their complexity and secondariness in comparison with the principal transient and steady-state behavior of the hydromechanical process variables, such as the differential pressure and relative displacement and its rate, in other words the piston stroke and velocity. However, a constrained motion of the cylinder piston can give rise to the back coupled excitation of the pressure-flow dynamics, especially upon mechanical impact at the cylinder limits. Following to that, semi-stable limit cycles can arise while the…
Deep learning for core-collapse supernova detection
2021
The detection of gravitational waves from core-collapse supernova (CCSN) explosions is a challenging task, yet to be achieved, in which it is key the connection between multiple messengers, including neutrinos and electromagnetic signals. In this work, we present a method for detecting these kind of signals based on machine learning techniques. We tested its robustness by injecting signals in the real noise data taken by the Advanced LIGO-Virgo network during the second observing run, O2. We trained a newly developed Mini-Inception Resnet neural network using time-frequency images corresponding to injections of simulated phenomenological signals, which mimic the waveforms obtained in 3D num…
3D-Printable Model of a Particle Trap: Development and Use in the Physics Classroom
2019
Quadrupole ion traps are modern and versatile research tools used in mass spectrometers, in atomic frequency and time standards, in trapped ion quantum computing research, and for trapping anti-hydrogen ions at CERN. Despite their educational potential, quadrupole ion traps are seldom introduced into the physics classroom not least because commercial quadrupole ion traps appropriate for classroom use are expensive and difficult to set up. We present an open hardware 3D-printable quadrupole ion trap suitable for the classroom, which is capable of trapping lycopodium spores. We also provide student worksheets developed in an iterative design process, which can guide students while discovering…
An energy residual-based approach to gradient effects within the mechanics of generalized continua
2012
AbstractGeneralized continua exhibiting gradient effects are addressed through a method grounded on the energy residual (ER)-based gradient theory by the first author and coworkers. A main tool of this theory is the Clausius-Duhem inequality cast in a form differing from the classical one only by a nonstandard extra term, the (nonlocality) ER, required to satisfy the insulation condition (its global value has to vanish or to take a known value). The ER carries in the nonlocality features of the mechanical problem through a strain-like rate field, being the specific nonlocality source, and a concomitant higher-order long-range stress (or microstress) field. The thermodynamic restrictions on …
Noise enhanced stability in magnetic systems
2009
In this paper noise enhanced stability in magnetic systems is studied by both an Ising-type model and a Preisach–Arrhenius model as well as a dynamic Preisach model. It is shown that in one nonequilibrium Ising system noise enhanced stability occurs and that dynamic Preisach model has the capability to predict the occurrence of noise enhanced stability in magnetic systems. On the contrary, in a Preisach–Arrhenius model of a single quadrant magnetic material, noise enhanced stability is not detected.
Improved Neural Networks with Random Weights for Short-Term Load Forecasting.
2015
An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load…
A novel four-quadrant power supply for low-energy correction magnets
2003
Abstract This paper describes an efficient power supply to feed low-energy correction magnets in particle accelerator applications, where a controlled current with trapezoidal profile and four-quadrant operation is needed. The selected design is based on an AC–DC matrix converter topology, which uses the Space Vector Modulation (SVM) technique to obtain a near unity power factor at the AC input and output DC current regulation. This topology allows performing high-frequency isolation, while four-quadrant operation is maintained, and reducing volume and weight as compared with the classical thyristor (SCR)-based technology. Control tasks are implemented on an all-digital control card: output…
Enhanced detection techniques of orbital angular momentum states in the classical and quantum regimes
2021
Abstract The orbital angular momentum (OAM) of light has been at the center of several classical and quantum applications for imaging, information processing and communication. However, the complex structure inherent in OAM states makes their detection and classification nontrivial in many circumstances. Most of the current detection schemes are based on models of the OAM states built upon the use of Laguerre–Gauss (LG) modes. However, this may not in general be sufficient to capture full information on the generated states. In this paper, we go beyond the LG assumption, and employ hypergeometric-Gaussian (HyGG) modes as the basis states of a refined model that can be used—in certain scenar…