Search results for " NEURAL NETWORKS"
showing 10 items of 390 documents
Validation procedures in radiological diagnostic models. Neural network and logistic regression
1999
The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validatio…
Aging Effects in a Lennard-Jones Glass
1997
Using molecular dynamics simulations we study the out of equilibrium dynamic correlations in a model glass-forming liquid. The system is quenched from a high temperature to a temperature below its glass transition temperature and the decay of the two-time intermediate scattering function C(t_w,t+t_w) is monitored for several values of the waiting time t_w after the quench. We find that C(t_w,t+t_w) shows a strong dependence on the waiting time, i.e. aging, depends on the temperature before the quench and, similar to the case of spin glasses, can be scaled onto a master curve.
A multiscale method for gamma/h discrimination in extensive air showers
2011
We present a new method for the identification of extensive air showers initiated by different primaries. The method uses the multiscale concept and is based on the analysis of multifractal behaviour and lacunarity of secondary particle distributions together with a properly designed and trained artificial neural network. The separation technique is particularly suited for being applied when the topology of the particle distribution in the shower front is as largely detailed as possible. Here, our method is discussed and applied to a set of fully simulated vertical showers in the experimental framework of ARGO-YBJ, taking advantage of both the space and time distribution of the detected sec…
Online Web Bot Detection Using a Sequential Classification Approach
2019
A significant problem nowadays is detection of Web traffic generated by automatic software agents (Web bots). Some studies have dealt with this task by proposing various approaches to Web traffic classification in order to distinguish the traffic stemming from human users' visits from that generated by bots. Most of previous works addressed the problem of offline bot recognition, based on available information on user sessions completed on a Web server. Very few approaches, however, have been proposed to recognize bots online, before the session completes. This paper proposes a novel approach to binary classification of a multivariate data stream incoming on a Web server, in order to recogn…
Wittgenstein, Turing, and Neural Networks
2018
The main task of this paper is grounding the socio-anthropological “naturalization” of meaning operated by the later Wittgenstein in his remarks on rule-following in the Philosophical Investigations in considerations relating to models of low-level (biological) processes of imitation, training, and learning. If the operation suggested above is successful, two of its immediate consequences are that the social aspect of language can no longer be considered as a primitive notion, but needs to be placed upon, if not reduced to, a biological foundation; and that the study of thought, and, actually, of certain brain processes, becomes prior in the order of explanation to the study of language. Th…
Effect of disorder on Majorana localization in topological superconductors: a quasiclassical approach
2020
Two-dimensional (2D) topological superconductors (TS) host chiral Majorana modes (MMs) localized at the boundaries. In this work, we study the effect of disorder on the localization length of MMs in two-dimensional spin-orbit (SO) coupled superconductors within quasiclassical approximation. We find nonmonotonic behavior of the Majorana localization length as a function of disorder strength. At weak disorder, the Majorana localization length decreases with an increasing disorder strength. Decreasing the disorder scattering time below a crossover value ${\ensuremath{\tau}}_{c}$, the Majorana localization length starts to increase. The crossover scattering time depends on the relative magnitud…
A nonlinear oscillators network devoted to image processing
2004
A contrast enhancement and image inverting tool using a lattice of uncoupled nonlinear oscillators is proposed. We show theoretically and numerically that the gray scale picture contrast is strongly enhanced even if this one is initially very small. An image inversion can be also obtained in real time with the same Cellular Nonlinear Network (CNN) without reconfiguration of the network. A possible electronic implementation of this CNN is finally discussed.
Experimental and numerical enhancement of Vibrational Resonance in a neural circuit
2012
International audience; A neural circuit exactly ruled by the FitzHugh-Nagumo equations is excited by a biharmonic signal of frequencies f and F with respective amplitudes A and B. The magnitude spectrum of the circuit response is estimated at the low frequency driving f and presents a resonant behaviour versus the amplitude B of the high frequency. For the first time, it is shown experimentally that this Vibrational Resonance effect is much more pronounced when the two frequencies are multiple. This novel enhancement is also confirmed by numerical predictions. Applications of this nonlinear effect to the detection of weak stimuli are finally discussed.
Research and implementation of artificial neural networks models for high velocity oxygen fuel thermal spraying
2020
In the high velocity oxygen fuel (HVOF) spray process, the coating properties are sensitive to the characteristics of in-flight particles, which are mainly determined by the process parameters. Due to the complex chemical and thermodynamic reactions during the deposition procedure, obtaining a comprehensive multi-physical model or analytical analysis of the HVOF process is still a challenging issue. This study proposes to develop a robust methodology via artificial neural networks (ANN) to solve this problem for the HVOF sprayed NiCr-Cr3C2 coatings under different operating parameters.First, 40 sets of HVOF spray experiments were conducted and the coating properties were tested for analysis…
High third and second order non linearities of chalcogenide glasses and fibers for compact infrared non linear devices.
2008
Due to their intrinsic nature, chalcogenide glasses present attractive nonlinearities from third and second order, with values reaching between 10 and 1000 times those of silica. We present a study of their properties and their shaping with the purpose to reach efficient devices in the near-mid infrared.