Search results for " NEURAL NETWORKS"

showing 10 items of 390 documents

Why retail investors traded equity during the pandemic? An application of artificial neural networks to examine behavioral biases

2021

Behavioral biases are known to influence the investment decisions of retail investors. Indeed, extant research has revealed interesting findings in this regard. However, the literature on the impact of these biases on millennials' trading activity, particularly during a health crisis like the COVID-19 pandemic, as well as the equity recommendation intentions of such investors, is limited. The present study addressed these gaps by investigating the influence of eight behavioral biases: overconfidence and self-attribution, over-optimism, hindsight, representativeness, anchoring, loss aversion, mental accounting, and herding on the trading activity and recommendation intentions of millennials …

MarketingActuarial scienceMental accounting:Samfunnsvitenskap: 200::Økonomi: 210::Bedriftsøkonomi: 213 [VDP]Behavioral economicsRepresentativeness heuristicVDP::Samfunnsvitenskap: 200::Økonomi: 210Investment decisionsLoss aversionVDP::Samfunnsvitenskap: 200::Psykologi: 260detaljhandelHerdingPsychologyartificial neural networkspandemiApplied PsychologyHindsight biasOverconfidence effectPsychology & Marketing
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Dynamics of Singlet Oxygen Molecule Trapped in Silica Glass Studied by Luminescence Polarization Anisotropy and Density Functional Theory

2020

The support from M-ERANET project “MyND” is acknowledged. A.A., M.M-S., and L.R. were supported by the Research Council of Lithuania (Grant M-ERA.NET-1/2015). The authors thank A. Pasquarello for providing the structures of the amorphous SiO 2 matrix for our computational work and K. Kajihara (Tokyo Metropolitan University) for valuable advice in PL kinetics measurements.

Materials science02 engineering and technology010402 general chemistryCondensed Matter::Disordered Systems and Neural Networks7. Clean energy01 natural sciencesMolecular physicschemistry.chemical_compound:NATURAL SCIENCES:Physics [Research Subject Categories]MoleculePhysics::Chemical PhysicsPhysical and Theoretical ChemistryPolarization (electrochemistry)AnisotropySinglet oxygenDynamics (mechanics)021001 nanoscience & nanotechnology0104 chemical sciencesSurfaces Coatings and FilmsElectronic Optical and Magnetic MaterialsCondensed Matter::Soft Condensed MatterGeneral EnergyPhotobiologychemistry13. Climate actionDensity functional theory0210 nano-technologyLuminescenceThe Journal of Physical Chemistry C
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Using a neural network for predicting the average grain size in friction stir welding processes

2009

In the paper the microstructural phenomena in terms of average grain size occurring in friction stir welding (FSW) processes are focused. A neural network was linked to a finite element model (FEM) of the process to predict the average grain size values. The utilized net was trained starting from experimental data and numerical results of butt joints and then tested on further butt, lap and T-joints. The obtained results show the capability of the AI technique in conjunction with the FE tool to predict the final microstructure in the FSW joints.

Materials scienceArtificial neural networkFSW metallurgy neural networksMechanical EngineeringMetallurgyMicrostructureGrain sizeFinite element methodComputer Science ApplicationsLap jointModeling and SimulationButt jointFriction stir weldingGeneral Materials ScienceFriction weldingComposite materialSettore ING-IND/16 - Tecnologie E Sistemi Di LavorazioneCivil and Structural Engineering
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Mechanical and microstructural properties prediction by artificial neural networks in FSW processes of dual phase titanium alloys

2012

Abstract Friction Stir Welding (FSW), as a solid state welding process, seems to be one of the most promising techniques for joining titanium alloys avoiding a large number of difficulties arising from the use of traditional fusion welding processes. In order to pursue cost savings and a time efficient design, the development of numerical simulations of the process can represent a valid choice for engineers. In the paper an artificial neural network was properly trained and linked to an existing 3D FEM model for the FSW of Ti–6Al–4V titanium alloy, with the aim to predict both the microhardness values and the microstructure of the welded butt joints at the varying of the main process parame…

Materials scienceArtificial neural networkbusiness.industryStrategy and ManagementTitanium alloyWeldingStructural engineeringManagement Science and Operations ResearchMicrostructureIndustrial and Manufacturing EngineeringFinite element methodlaw.inventionFusion weldingFriction Stir Welding Titanium alloy Neural Networks FEMlawButt jointFriction stir weldingFriction Stir Welding Titanium alloys Neural networks FEMbusinessSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione
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Interaction of Lamb modes with two-level systems in amorphous nanoscopic membranes

2007

Using a generalized model of interaction between a two-level system (TLS) and an arbitrary deformation of the material, we calculate the interaction of Lamb modes with TLSs in amorphous nanoscopic membranes. We compare the mean free paths of the Lamb modes with different symmetries and calculate the heat conductivity $\kappa$. In the limit of an infinitely wide membrane, the heat conductivity is divergent. Nevertheless, the finite size of the membrane imposes a lower cut-off for the phonons frequencies, which leads to the temperature dependence $\kappa\propto T(a+b\ln T)$. This temperature dependence is a hallmark of the TLS-limited heat conductance at low temperature.

Materials scienceCondensed matter physicsCondensed Matter - Mesoscale and Nanoscale PhysicsMean free pathPhononFOS: Physical sciencesConductanceDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsAmorphous solidThermal conductivityMembraneMesoscale and Nanoscale Physics (cond-mat.mes-hall)Deformation (engineering)Nanoscopic scale
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Dynamics of nanoparticles in a supercooled liquid

2008

The dynamic properties of nanoparticles suspended in a supercooled glass forming liquid are studied by x-ray photon correlation spectroscopy. While at high temperatures the particles undergo Brownian motion the measurements closer to the glass transition indicate hyperdiffusive behavior. In this state the dynamics is independent of the local structural arrangement of nanoparticles, suggesting a cooperative behavior governed by the near-vitreous solvent.

Materials scienceCondensed matter physicsDynamics (mechanics)slow dynamicsGeneral Physics and AstronomyNanoparticleX-ray scattering; glass transition; anomalous diffusion; slow dynamicsX-ray scatteringCondensed Matter::Disordered Systems and Neural NetworksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Condensed Matter::Soft Condensed MatterSolventDynamic light scatteringChemical physicsanomalous diffusionglass transitionCooperative behaviorSupercoolingGlass transitionBrownian motion
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Secondary relaxation in the glass-transition regime of ortho-terphenyl observed by incoherent neutron scattering.

1992

We report on incoherent-neutron-scattering measurements in the supercooled regime of the van der Waals liquid ortho-terphenyl. A secondary localized relaxational process on the picosecond time scale is found. In accordance with mode-coupling theories of the glass transition, the relaxational dynamics around a critical temperature ${\mathit{T}}_{\mathit{c}}$ decomposes into two time regimes.

Materials scienceCondensed matter physicsIncoherent scatterNeutron scatteringCondensed Matter::Disordered Systems and Neural NetworksCondensed Matter::Soft Condensed Mattersymbols.namesakechemistry.chemical_compoundchemistryCritical point (thermodynamics)TerphenylPicosecondsymbolsPhysics::Chemical Physicsvan der Waals forceGlass transitionSupercoolingPhysical review. B, Condensed matter
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Glass transition of binary mixtures of dipolar particles in two dimensions

2010

We study the glass transition of binary mixtures of dipolar particles in two dimensions within the framework of mode-coupling theory, focusing in particular on the influence of composition changes. In a first step, we demonstrate that the experimental system of K\"onig et al. [Eur. Phys. J. E 18, 287 (2005)] is well described by point dipoles through a comparison between the experimental partial structure factors and those from our Monte Carlo simulation. For such a mixture of point particles we show that there is always a plasticization effect, i.e. a stabilization of the liquid state due to mixing, in contrast to binary hard disks. We demonstrate that the predicted plasticization effect i…

Materials scienceCondensed matter physicsMonte Carlo methodFOS: Physical sciencesThermodynamicsBinary numberDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Soft Condensed MatterCondensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsColloidDipoleExperimental systemMaterials ChemistryCeramics and CompositesSoft Condensed Matter (cond-mat.soft)Point (geometry)Glass transitionMixing (physics)Journal of Non-Crystalline Solids
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Amorphous silica between confining walls and under shear: a computer simulation study

2002

Molecular dynamics computer simulations are used to investigate a silica melt confined between walls at equilibrium and in a steady-state Poisseuille flow. The walls consist of point particles forming a rigid face-centered cubic lattice and the interaction of the walls with the melt atoms is modelled such that the wall particles have only a weak bonding to those in the melt, i.e. much weaker than the covalent bonding of a Si-O unit. We observe a pronounced layering of the melt near the walls. This layering, as seen in the total density profile, has a very irregular character which can be attributed to a preferred orientational ordering of SiO4 tetrahedra near the wall. On intermediate lengt…

Materials scienceCondensed matter physicsStatistical Mechanics (cond-mat.stat-mech)Shear viscosityGeneral Physics and AstronomyFOS: Physical sciencesSlip (materials science)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksPhysics::Fluid DynamicsMolecular dynamicsLattice (order)TetrahedronPhysical and Theoretical ChemistryLayeringAmorphous silicaCondensed Matter - Statistical Mechanics
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Modeling non-linear dielectric susceptibilities of supercooled molecular liquids

2021

Advances in high-precision dielectric spectroscopy have enabled access to non-linear susceptibilities of polar molecular liquids. The observed non-monotonic behavior has been claimed to provide strong support for theories of dynamic arrest based on the thermodynamic amorphous order. Here, we approach this question from the perspective of dynamic facilitation, an alternative view focusing on emergent kinetic constraints underlying the dynamic arrest of a liquid approaching its glass transition. We derive explicit expressions for the frequency-dependent higher-order dielectric susceptibilities exhibiting a non-monotonic shape, the height of which increases as temperature is lowered. We demons…

Materials scienceFOS: Physical sciencesGeneral Physics and AstronomyDisordered Systems and Neural Networks (cond-mat.dis-nn)DielectricCondensed Matter - Soft Condensed MatterCondensed Matter - Disordered Systems and Neural NetworksAmorphous solidDielectric spectroscopyCondensed Matter::Soft Condensed MatterNonlinear systemChemical physicsSoft Condensed Matter (cond-mat.soft)PolarRelaxation (physics)Physical and Theoretical ChemistrySupercoolingGlass transition
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