Search results for " neural networks"
showing 10 items of 390 documents
Towards a deep-learning-based methodology for supporting satire detection
2021
This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.
Mathematical Patterns and Cognitive Architectures
2014
Mathematical patterns are an important subclass of the class of patterns. The main task of this paper is examining a particular proposal concerning the nature of mathematical patterns and some elements of the cognitive architecture an agent should have to recognize them.
Fake News Spreaders Detection: Sometimes Attention Is Not All You Need
2022
Guided by a corpus linguistics approach, in this article we present a comparative evaluation of State-of-the-Art (SotA) models, with a special focus on Transformers, to address the task of Fake News Spreaders (i.e., users that share Fake News) detection. First, we explore the reference multilingual dataset for the considered task, exploiting corpus linguistics techniques, such as chi-square test, keywords and Word Sketch. Second, we perform experiments on several models for Natural Language Processing. Third, we perform a comparative evaluation using the most recent Transformer-based models (RoBERTa, DistilBERT, BERT, XLNet, ELECTRA, Longformer) and other deep and non-deep SotA models (CNN,…
Structural and dynamical properties of sodium silicate melts: An investigation by molecular dynamics computer simulation
2001
We present the results of large scale computer simulations in which we investigate the static and dynamic properties of sodium disilicate and sodium trisilicate melts. We study in detail the static properties of these systems, namely the coordination numbers, the temperature dependence of the Q^(n) species and the static structure factor, and compare them with experiments. We show that the structure is described by a partially destroyed tetrahedral SiO_4 network and the homogeneously distributed sodium atoms which are surrounded on average by 16 silicon and other sodium atoms as nearest neighbors. We compare the diffusion of the ions in the sodium silicate systems with that in pure silica a…
Disordered and Frustrated Spin Systems
2007
A brief review on the effects of quenched disorder on magnetic ordering is given. This disorder can be due to dilution of a ferro- or antiferromagnetic crystal with nonmagnetic atoms, or due to noncrystallinity (amorphous magnetic systems). This disorder in the positions of the magnetic atoms leads to disorder in the exchange interactions between spins. If the disorder is sufficiently weak, the critical temperature of magnetic ordering is somewhat decreased, and the critical behavior may change, but the nature of ordering is maintained. However, if the disorder is sufficiently strong, magnetic long-range order may disappear altogether at a percolation threshold, or a new type of order may a…
The manifestation of dipoles clustering in paraelectric phase of disordered ferroelectrics
2001
Abstract We predict the existence of Griffiths phase in the dielectrics with concentrational crossover between dipole glass (electric analog of spin glass) and ferroelectricity. The peculiar representatives of above substances are KTaO3: Li, Nb, Na or relaxor ferroelectrics like Pb1−xLaxZr0.65Ti0.35O3. Since this phase exists above ferroelectric phase transition temperature (but below that temperature for ordered substance), we call it “para-glass phase”. We assert that the difference between paraelectric and para-glass phase of above substances is the existence of clusters (inherent to “ordinary” Griffiths phase in Ising magnets) of correlated dipoles. We show that randomness play a decisi…
Performance potential for simulating spin models on GPU
2012
Graphics processing units (GPUs) are recently being used to an increasing degree for general computational purposes. This development is motivated by their theoretical peak performance, which significantly exceeds that of broadly available CPUs. For practical purposes, however, it is far from clear how much of this theoretical performance can be realized in actual scientific applications. As is discussed here for the case of studying classical spin models of statistical mechanics by Monte Carlo simulations, only an explicit tailoring of the involved algorithms to the specific architecture under consideration allows to harvest the computational power of GPU systems. A number of examples, ran…
Descriptor-type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor.
2014
This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in …
Hierarchical Structure in Financial Markets
1998
I find a topological arrangement of stocks traded in a financial market which has associated a meaningful economic taxonomy. The topological space is a graph connecting the stocks of the portfolio analyzed. The graph is obtained starting from the matrix of correlation coefficient computed between all pairs of stocks of the portfolio by considering the synchronous time evolution of the difference of the logarithm of daily stock price. The hierarchical tree of the subdominant ultrametric space associated with the graph provides information useful to investigate the number and nature of the common economic factors affecting the time evolution of logarithm of price of well defined groups of sto…
Temporal and spatial persistence of combustion fronts
2002
The spatial and temporal persistence, or first-return distributions are measured for slow combustion fronts in paper. The stationary temporal and (perhaps less convincingly) spatial persistence exponents agree with the predictions based on the front dynamics, which asymptotically belongs to the Kardar-Parisi-Zhang (KPZ) universality class. The stationary short-range and the transient behavior of the fronts is non-Markovian and the observed persistence properties thus do not agree with the theory. This deviation is a consequence of additional time and length scales, related to the crossovers to the asymptotic coarse-grained behavior.