Towards a conceptual remodeling of information technologies based on a broad consideration of complexity

Actas.

Dynamic Soil-Structure Interaction in Bridge Abutments

Strong motion obtained in instrumental short-span bridges show the importance of the abutments in the dynamic response of the whole structure. Many models have been used in order to take into account the influence of pier foundations although no reliable ones have been used to analyse the abutment performance. In this work three-dimensional Boundary Element models in frequency domain have been proposed and dimensionless dynamic stiffness of standard bridge abutments have been obtained.

Probabilistic Analysis of Tunnel Liners

The use of probabilistic methods to analyse reliability of structures is being applied to a variety of engineering problems due to the possibility of establishing the failure probability on rational grounds. In this paper we present the application of classical reliability theory to analyse the safety of underground tunnels.

Simplified Procedure for the Nonlinear Seismic Analysis of Bridges

The severe accidents suffered by bridges during recent earthquake show that more careful analysis are needed to guarantee their behaviour. In particular simplified non-linear analysis could be useful to bridge the gap between theoretical research and practical applications. This paper presents one of those simplified methods that can be applied for first designs or to retrofitting of groups of bridges.

Limits of the power of Tissue P systems with cell division

Tissue P systems generalize the membrane structure tree usual in original models of P systems to an arbitrary graph. Basic opera- tions in these systems are communication rules, enriched in some variants with cell division or cell separation. Several variants of tissue P systems were recently studied, together with the concept of uniform families of these systems. Their computational power was shown to range between P and NP ? co-NP , thus characterizing some interesting borderlines between tractability and intractability. In this paper we show that com- putational power of these uniform families in polynomial time is limited by the class PSPACE . This class characterizes the power of many clas- sical parallel computing models

Anisotropic magnetoresistive study in bilayer NiFe-NiO for sensor applications

Related with the detection of weak magnetic fields, the anisotropic magnetoresistive (AMR) effect is widely utilized in sensor applications. Exchange coupling between an antiferromagnet (AF) and the ferromagnet (FM) has been known as a significant parameter in the field sensitivity of magnetoresistance because of pinning effects on magnetic domain in FM layer by the bias field in AF. In this work we have studied the thermal evolution of the magnetization reversal processes in nanocrystalline exchange biased Ni80Fe20/Ni-O bilayers with large training effects and we report the anisotropic magnetoresistance ratio arising from field orientation in the bilayer.

A Knowledge Model for Automatic Configuration of Traffic Messages

This paper describes a knowledge model for a configuration problem in the do-main of traffic control. The goal of this model is to help traffic engineers in the dynamic selection of a set of messages to be presented to drivers on variable message signals. This selection is done in a real-time context using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based solution that implements two abstract problem solving methods according to a model-based approach recently proposed in the knowledge engineering field. Finally, the paper presents a discussion about the advantages and drawbacks found for this problem as a consequence of the applied knowledge modeling ap-proach.

Depth filtering for auto-stereoscopic mobile devices

In this work we address a scenario where 3D content is transmitted to a mobile terminal with 3D display capabilities. We consider the use of 2D plus depth format to represent the 3D content and focus on the generation of synthetic views in the terminal. We evaluate different types of smoothing filters that are applied to depth maps with the aim of reducing the disoccluded regions. The evaluation takes into account the reduction of holes in the synthetic view as well as the presence of geometrical distortion caused by the smoothing operation. The selected filter has been included within an implemented module for the VideoLan Client (VLC) software in order to render 3D content from the 2D plus depth data format.

An optimal yet fast pruning algorithm to reduce latency in multiview prediction structures

We propose a new algorithm for the design of prediction structures with low delay and limited penalty in the rate-distortion performance for multiview video coding schemes. This algorithm constitutes one of the elements of a framework for the analysis and optimization of delay in multiview coding schemes that is based in graph theory. The objective of the algorithm is to find the best combination of prediction dependencies to prune from a multiview prediction structure, given a number of cuts. Taking into account the properties of the graph-based analysis of the encoding delay, the algorithm is able to find the best prediction dependencies to eliminate from an original prediction structure, while limiting the number of cut combinations to evaluate. We show that this algorithm obtains optimum results in the reduction of the encoding latency with a lower computational complexity than exhaustive search alternatives.

Fast 2D to 3D conversion using a clustering-based hierarchical search in a machine learning framework

Automatic 2D-to-3D conversion is an important application for filling the gap between the increasing number of 3D displays and the still scant 3D content. However, existing approaches have an excessive computational cost that complicates its practical application. In this paper, a fast automatic 2D-to-3D conversion technique is proposed, which uses a machine learning framework to infer the 3D structure of a query color image from a training database with color and depth images. Assuming that photometrically similar images have analogous 3D structures, a depth map is estimated by searching the most similar color images in the database, and fusing the corresponding depth maps. Large databases are desirable to achieve better results, but the computational cost also increases. A clustering-based hierarchical search using compact SURF descriptors to characterize images is proposed to drastically reduce search times. A significant computational time improvement has been obtained regarding other state-of-the-art approaches, maintaining the quality results.

Behavior of different soot combustion catalysts under NOx/O2. Importance of the catalyst–soot contact

Four different catalysts (Pt/Al2O3, Ce0.8Zr0.2O2, PrO2−x and SrTiCuO3) have been investigated on a laboratory scale to evaluate their potential as diesel soot combustion catalysts under different experimental conditions, which simulate the situation found in a continuous regeneration technology trap (dual-bed configuration of catalyst and soot) or a catalyst-coated filter system (single-bed configuration, both catalyst and soot particles mixed under loose-contact mode). Under dual-bed configuration, the behavior of the catalysts towards soot combustion are very similar, despite the differences observed in the NO2 production profiles. However, under single-bed configuration, there are important differences in the soot combustion activities and in the NO2 slip profiles. The configurations chosen have an enormous impact on CO/(CO + CO2) ratios of combustion products as well. The most active catalyst under NOx + O2 is PrO2−x combining a high contribution of active oxygen-assisted soot combustion as well as high NO2 production activity along the catalytic bed.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

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