Search results for " NEURAL NETWORKS"
showing 10 items of 390 documents
Defects in glasses
1995
Abstract The absence of long range order in the glass structure allows to define only point defects in these materials. They are: 1) intrinsic defects—atomic size local deviation from short range order; 2) impurity defects—isolated impurity atoms or ions in the glass network; 3) intrinsic impurity defects—complexes consisting of the impurity atoms chemically bonded to one of the intrinsic defect atoms. The latter defects are characteristic for the doped glasses. Presence of point defects in glasses introduces new spectroscopic properties of these solid materials. Defect generation, interaction and recombination reactions resulting from the external influence causes the glass spectroscopic p…
A Novel Systolic Parallel Hardware Architecture for the FPGA Acceleration of Feedforward Neural Networks
2019
New chips for machine learning applications appear, they are tuned for a specific topology, being efficient by using highly parallel designs at the cost of high power or large complex devices. However, the computational demands of deep neural networks require flexible and efficient hardware architectures able to fit different applications, neural network types, number of inputs, outputs, layers, and units in each layer, making the migration from software to hardware easy. This paper describes novel hardware implementing any feedforward neural network (FFNN): multilayer perceptron, autoencoder, and logistic regression. The architecture admits an arbitrary input and output number, units in la…
Spin Glasses on Thin Graphs
1995
In a recent paper we found strong evidence from simulations that the Isingantiferromagnet on ``thin'' random graphs - Feynman diagrams - displayed amean-field spin glass transition. The intrinsic interest of considering such random graphs is that they give mean field results without long range interactions or the drawbacks, arising from boundary problems, of the Bethe lattice. In this paper we reprise the saddle point calculations for the Ising and Potts ferromagnet, antiferromagnet and spin glass on Feynman diagrams. We use standard results from bifurcation theory that enable us to treat an arbitrary number of replicas and any quenched bond distribution. We note the agreement between the f…
Effect of the milling conditions on the degree of amorphization of selenium by milling in a planetary ball mill
2007
The effect of the milling parameters (rotation speed of the milling device and duration of milling) on the phase composition of the products of milling of fully crystalline selenium has been investigated. The milling was conducted using a planetary micromill and the phase composition of the milling products was determined by differential thermal analysis. It has been found that ball milling leads to the partial amorphization of the starting crystalline material. The content of amorphous phase in the milling products depends, in a rather complicated way, on the milling parameters. At the milling parameters adopted in the present study, the milling product was never fully amorphous. The compl…
Devitrification of the Kob-Andersen glass former: Competition with the locally favored structure
2018
Abstract Supercooled liquids are kinetically trapped materials in which the transition to a thermodynamically more stable state with long-range order is strongly suppressed. To assess the glass-forming abilities of a liquid empirical rules exist, but a comprehensive microscopic picture of devitrification is still missing. Here we study the crystallization of a popular model glass former, the binary Kob-Andersen mixture, in small systems. We perform trajectory sampling employing the population of the locally favored structure as order parameter. While for large population a dynamical phase transition has been reported, here we show that biasing towards a small population of locally favored s…
Critical phenomena without “hyper scaling”: How is the finite-size scaling analysis of Monte Carlo data affected?
2010
Abstract The finite size scaling analysis of Monte Carlo data is discussed for two models for which hyperscaling is violated: (i) the random field Ising model (using a model for a colloid-polymer mixture in a random matrix as a representative) (ii) The Ising bi-pyramid in computing surface fields.
Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network
2020
In this study we develop a proof of concept of using generative adversarial neural networks in hyperspectral skin cancer imagery production. Generative adversarial neural network is a neural network, where two neural networks compete. The generator tries to produce data that is similar to the measured data, and the discriminator tries to correctly classify the data as fake or real. This is a reinforcement learning model, where both models get reinforcement based on their performance. In the training of the discriminator we use data measured from skin cancer patients. The aim for the study is to develop a generator for augmenting hyperspectral skin cancer imagery. peerReviewed
Neural Networks to Determine the Relationships Between Business Innovation and Gender Aspects
2021
Gender aspects of management, innovation and entrepreneurship are gaining more and more importance as cross-cutting issues for researchers, practitioners and decision makers. Extant literature pays a growing attention to the hypothesis that there exists a correlation between the gender diversity of corporate boards of directors and the business attitude to innovation. In this paper we introduce a working framework to test the aforementioned hypothesis and to examine the correlation between board diversity and innovation perception of a business. This framework is based on correlation computation and feed-forward neural networks, and it is used to evaluate whether the gender component may be…
Slow and fast methyl group rotations in fragile glass-formers studied by NMR
2000
Abstract The spin-lattice relaxation times of the selectively ring deuterated, fragile glass-formers propylene carbonate and toluene were compared with those measured for species which were specifically labeled at the methyl groups. It was found that the dynamics of the CD 3 group is strongly decoupled from that associated with the primary response of toluene, while for propylene carbonate the degree of decoupling is relatively weak. The experimental results could be described successfully using a model which takes into account the ring dynamics as well as those of the methyl group.
Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement
2022
Part of this research was funded by the project RTI2018-096224-J-I00 that has been cofounded by the Spanish Ministry of Science and Innovation, inside the National Program for Fostering Excellence in Scientific and Technical Research, National Subprogram of Knowledge Generation, 2018 call, in the framework of the Spanish National Plan for Scientific and Technical Research and Innovation 2017-2020, and by the European Union, through the European Regional Development Fund, with the main objective of Promoting technological development, innovation and quality research. Part of this work was financially supported by the Italian Ministry of University and Research with the research Grant PRIN 20…