Hierarchical recurrent neural encoder for video representation with application to captioning

© 2016 IEEE. Recently, deep learning approach, especially deep Convolutional Neural Networks (ConvNets), have achieved overwhelming accuracy with fast processing speed for image classification. Incorporating temporal structure with deep ConvNets for video representation becomes a fundamental problem for video content analysis. In this paper, we propose a new approach, namely Hierarchical Recurrent Neural Encoder (HRNE), to exploit temporal information of videos. Compared to recent video representation inference approaches, this paper makes the following three contributions. First, our HRNE is able to efficiently exploit video temporal structure in a longer range by reducing the length of input information flow, and compositing multiple consecutive inputs at a higher level. Second, computation operations are significantly lessened while attaining more non-linearity. Third, HRNE is able to uncover temporal tran-sitions between frame chunks with different granularities, i.e. it can model the temporal transitions between frames as well as the transitions between segments. We apply the new method to video captioning where temporal information plays a crucial role. Experiments demonstrate that our method outperforms the state-of-the-art on video captioning benchmarks

An advanced meshless method for time fractional diffusion equation

Recently, because of the new developments in sustainable engineering and renewable energy, which are usually governed by a series of fractional partial differential equations (FPDEs), the numerical modelling and simulation for fractional calculus are attracting more and more attention from researchers. The current dominant numerical method for modeling FPDE is Finite Difference Method (FDM), which is based on a pre-defined grid leading to inherited issues or shortcomings including difficulty in simulation of problems with the complex problem domain and in using irregularly distributed nodes. Because of its distinguished advantages, the meshless method has good potential in simulation of FPDEs. This paper aims to develop an implicit meshless collocation technique for FPDE. The discrete system of FPDEs is obtained by using the meshless shape functions and the meshless collocation formulation. The stability and convergence of this meshless approach are investigated theoretically and numerically. The numerical examples with regular and irregular nodal distributions are used to validate and investigate accuracy and efficiency of the newly developed meshless formulation. It is concluded that the present meshless formulation is very effective for the modeling and simulation of fractional partial differential equations

Study on cognitive load of OM interface and eye movement experiment for nuclear power system

The operation and monitoring (OM) interface is the digital medium between nuclear power system and operators. The cognitive load of OM interface has an important effect on the operation errors made by operator during OM task between operator and computer. The cognitive load model of OM interface is constructed for analysing the composition and influencing factors of OM interface cognitive load. And to study the coping strategies and methods for cognitive load of nuclear power system. An experiment method based on eye movement is proposed to measure the cognitive load of OM interface. Experiment case is carried out with 20 subjects and typical OM interface of a nuclear power system simulator. The OM interface is optimized based on the experiment results. And the results comparison between the original OM interface and the optimized OM interface shows that the cognitive load model and proposed method is valuable contributions in reducing the cognitive load and improving the interaction efficiency of OM tasks

Structured embedding via pairwise relations and long-range interactions in knowledge base

Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. We consider the problem of embedding entities and relations of knowledge bases into low-dimensional continuous vector spaces (distributed representations). Unlike most existing approaches, which are primarily efficient for modelling pairwise relations between entities, we attempt to explicitly model both pairwise relations and long-range interactions between entities, by interpreting them as linear operators on the low-dimensional embeddings of the entities. Therefore, in this paper we introduces path ranking to capture the long-range interactions of knowledge graph and at the same time preserve the pairwise relations of knowledge graph; we call it structured embedding via pairwise relation and /ong-range interactions (referred to as SePLi). Comparing with the-state-of-the-art models, SePLi achieves better performances of embeddings

Non-Abelian Medium Effects in Quark-Gluon Plasma

Based on the kinetic theory, the non-Abelian medium property of hot Quark-Gluon Plasma is investigated. The nonlinearity of the plasma comes from two aspects: The nonlinear wave-wave interaction and self-interaction of color field. The non-Abelian color permittivity is obtained by expanding the kinetic equations to third order. As an application, the nonlinear Landau damping rate and the nonlinear eigenfrequency shift are calculated in the longwave length limit.Comment: 12 pages(Revtex), no figure

Ionic liquid gate-induced modifications of step edges at SrCoO_2.5 surfaces

Intense electric fields developed during gating at the interface between an ionic liquid and an oxide layer have been shown to lead to significant structural and electronic phase transitions in the entire oxide layer. An archetypical example is the reversible transformation between the brownmillerite SrCoO2.5 and the perovskite SrCoO3 engendered by ionic liquid gating. Here we show using in situ atomic force microscopy studies with photothermal excitation detection, that allows for high quality measurements in the viscous environment of the ionic liquid that the edges of atomically smooth terraces at the surface ofSrCoO2.5 films are significantly modified by ionic liquid gating but that the terraces themselves remain smooth. The edges develop ridges that we show, using complementary X-ray photoemission spectroscopy studies, result from the adsorption of hydroxyl groups. Our findings exhibit a way of electrically controlled surface modifications in emergent ionitronic applications

Semiclassical vibrational spectroscopy with Hessian databases

We report on a new approach to ease the computational overhead of ab initio "on-the-fly" semiclassical dynamics simulations for vibrational spectroscopy. The well known bottleneck of such computations lies in the necessity to estimate the Hessian matrix for propagating the semiclassical pre-exponential factor at each step along the dynamics. The procedure proposed here is based on the creation of a dynamical database of Hessians and associated molecular geometries able to speed up calculations while preserving the accuracy of results at a satisfactory level. This new approach can be interfaced to both analytical potential energy surfaces and on-the-fly dynamics, allowing one to study even large systems previously not achievable. We present results obtained for semiclassical vibrational power spectra of methane, glycine, and N-acetyl-L-phenylalaninyl-L-methionine-amide, a molecule of biological interest made of 46 atoms