Segmentation of news videos based on audio-video information

In this paper, we propose an innovative architecture to segment a news video into the so-called “stories” by both using the included video and audio information. Segmentation of news into stories is one of the key issues for achieving efficient treatment of news-based digital libraries. While the relevance of this research problem is widely recognized in the scientific community, we are in presence of a few established solutions in the field. In our approach, the segmentation is performed in two steps: first, shots are classified by combining three different anchor shot detection algorithms using video information only. Then, the shot classification is improved by using a novel anchor shot detection method based on features extracted from the audio track. Tests on a large database confirm that the proposed system outperforms each single video-based method as well as their combination.

The importance of different timings of excitatory and inhibitory pathways in neural field models

In this paper, we consider a neural field model comprised of two distinct populations of neurons, excitatory and inhibitory, for which both the velocities of action potential propagation and the time courses of synaptic processing are different. Using recently-developed techniques, we construct the Evans function characterising the stability of both stationary and travelling wave solutions, under the assumption that the firing rate function is the Heaviside step. We find that these differences in timing for the two populations can cause instabilities of these solutions, leading to, for example, stationary breathers. We also analyse "anti-pulses", a novel type of pattern for which all but a small interval of the domain (in moving coordinates) is active. These results extend previous work on neural fields with space-dependent delays, and demonstrate the importance of considering the effects of the different time-courses of excitatory and inhibitory neural activity.     

An experimental comparison of a graphite electrode and a gas diffusion electrode for the cathodic production of hydrogen peroxide

This work studies the production of hydrogen peroxide through the cathodic reduction of oxygen in acidic medium, by comparing the results obtained using a commercial graphite and a gas diffusion electrode. A low pH was required to allow the application of hydrogen peroxide generation to an electro-Fenton process. The influence of applied potential and the gas flow composition were investigated. The gas diffusion electrode demonstrates a higher selectivity for hydrogen peroxide production, without significantly compromising the iron regeneration, thus making its successful application to a cathodic Fenton-like treatment, possible. Unlike the graphite cathode, the gas diffusion cathode also proved to be effective in the air flow.     

Kernel ridge regression for out-of-sample mapping in supervised manifold learning

Manifold learning methods for unsupervised nonlinear dimensionality reduction have proven effective in the visualization of high dimensional data sets. When dealing with classification tasks, supervised extensions of manifold learning techniques, in which class labels are used to improve the embedding of the training points, require an appropriate method for out-of-sample mapping.In this paper we propose multi-output kernel ridge regression (KRR) for out-of-sample mapping in supervised manifold learning, in place of general regression neural networks (GRNN) that have been adopted by previous studies on the subject. Specifically, we consider a supervised agglomerative variant of Isomap and compare the performance of classification methods when the out-of-sample embedding is based on KRR and GRNN, respectively. Extensive computational experiments, using support vector machines and k-nearest neighbors as base classifiers, provide statistical evidence that out-of-sample mapping based on KRR consistently dominates its GRNN counterpart, and that supervised agglomerative Isomap with KRR achieves a higher accuracy than direct classification methods on most data sets.     

Quantum Capacitance Effects in Carbon Nanotube Field-Effect Devices

Density functional numerical simulations are reported in which the non-equilibrium coherent transport properties of a coaxially gated carbon nanotube (CNT) are studied. Effects of screening properties of CNT on the channel conductance modulation are shown. Other factors which influence the CNT quantum capacitance beyond the density of states (DOS) are pointed out, first of all many-body effects which even cause the CNT to over-screen the gate field. Results stress the importance of a good electrostatic-design of the gate contact to obtain an effective field-effect current modulation, and suggest new interesting operation modes for quasi-one dimensional channel devices.     

Retrieval of leaf area index in different vegetation types using high resolution satellite data

With the successful launch of the IKONOS satellite, very high geometric resolution imagery is within reach of civilian users. In the 1-m spatial resolution images acquired by the IKONOS satellite, details of buildings, individual trees, and vegetation structural variations are detectable. The visibility of such details opens up many new applications, which require the use of geometrical information contained in the images. This paper presents an application in which spectral and textural information is used for mapping the leaf area index (LAI) of different vegetation types. This study includes the estimation of LAI by different spectral vegetation indices (SVIs) combined with image textural information and geostatistical parameters derived from high resolution satellite data. It is shown that the relationships between spectral vegetation indices and biophysical parameters should be developed separately for each vegetation type, and that the combination of the texture indices and vegetation indices results in an improved fit of the regression equation for most vegetation types when compared with one derived from SVIs alone. High within-field spatial variability was found in LAI, suggesting that high resolution mapping of LAI may be relevant to the introduction of precision farming techniques in the agricultural management strategies of the investigated area.     

Multirobot motion coordination in space and time

This paper describes a solution to the multirobot motion planning problem based on a decoupled analysis in the space domain and in the time domain. It investigates the practical use of the notion of motion plan quality and of the motion plan robustness measures for computing safe motions. The use of anytime algorithms allows one to evaluate the opportunity of looking for alternative solution paths by generating small variations of robot motions affecting both its geometrical path and its scheduled velocity. By using the concept of plan robustness, several alternative paths are generated and evaluated through various performance indices and impact factors, using heuristic rules. These indices allow one to know how much a variation affects a given plan. Finally, some recent experiments are outlined.     

An Attempt at the Classification of Energy Decaying Schemes for Structural and Multibody Dynamics

This paper analyzes the formulation of energy preserving/decaying schemes for dynamics problems. We argue that any energy preserving/decaying scheme can always be seen as composed of an underlying temporal discretization, that is then slightly modified in order to prove a discrete energy bound within a time step. While the details of the modified scheme depend in a critical way on the governing equations, the underlying discretization can in principle be applied to a variety of models. We review some of the temporal underlying schemes recently proposed in the literature, presenting them with a common notation. We show their similarities and highlight their differences.     

Scaling Laws of Vortex Reconnections

The vortex reconnection rate f plays an important role in the dynamics of a tangle of quantised vortices in superfluid turbulence. The question which we address is how f depends on the vortex line density L. In the case of a homogeneous isotropic tangle of vortices we show that, besides the known regime which scales as f ～ L^5/2, another regime exists which scales as f ～ L². In the case of a polarised vortex confguration, we argue that the scaling law changes and show numerical evidence for it. Finally we construct an idealised model of turbulence decay based on vortex reconnections and discuss its implications. PACS numbers: 67.40.Vs, 67.57.Fg.