Speeding-up homography estimation in mobile devices

A critical problem faced by computer vision on mobile devices is reducing the computational cost of algorithms and avoiding visual stalls. In this paper, we introduce a procedure for reducing the number of samples required for fitting a homography to a set of noisy correspondences using a random sampling method. This is achieved by means of a geometric constraint that detects invalid minimal sets. In the experiments conducted, we show that this constraint not only reduces the number of random samples at a negligible computational cost but also balances the processor workload over time preventing visual stalls. In extreme situations of very large outlier proportion and noise level, it reduces in about one order of magnitude the number of required random samples.     

The Composition of Mixed Micelles Formed by Dodecyl Trimethyl Ammonium Bromide and Benzethonium Chloride in Water

The composition of the mixed micelles formed by benzethonium chloride and dodecyl trimethyl ammonium bromide in water were experimentally determined by a combination of surfactant ion-selective electrodes and UV–Vis spectroscopy measurements. Results were compared with the computed compositions from three theories on mixed micelles available in the literature (Regular Solution, Motomura’ and Georgiev’s). The basis of the Junquera and Aicart method and the determination of the micelle aggregation number (N) by pyrene fluorescence quenching, i.e., the constancy of N and the mixed micelle composition when the total concentration is changed, were not supported by our experimental results. Experimental micelle compositions were statistically equal to those computed by Regular Solution Theory. The mixed micelle composition and the quantity of non-micellized surfactant molecules change with concentration above the critical micelle concentration, and therefore do not support the assumptions used in the Junquera and Aicart procedure and in the determination of N by pyrene fluorescence quenching. The reason why the latter procedure gives N values similar to those obtained from other techniques is discussed.     

Viscosity virtual sensor to control combustion in fossil fuel power plants

Thermo-electrical power plants utilize fossil fuel oil to transform the calorific power of fuel into electric power. An optimal combustion in the boiler requires the fuel oil to be in its best conditions. One of fuel's most important properties to consider is viscosity. Viscosity has influence on the optimal combustion between fuel and air. Hardware viscosity meters for fuel oils are expensive and unreliable to operate in power plant conditions. Chemical laboratory measures viscosity accurately with special apparatus, but they cannot be used in a real time process. This paper describes the development of a virtual sensor that estimates fuel oil viscosity in the combustion process of a power plant. A virtual sensor or soft sensor is a computer program that estimates the value of a certain variable based on related measurements and a model of the process where the variable participates. In this project, a probabilistic model is constructed using automatic learning algorithms with historical data and experts' advice. The learning and validation experiments are described and discussed. The virtual sensor is installed in the Tuxpan Power Plant in Veracruz, Mexico.     

Optimization of Sesame Oil Extraction by Screw-Pressing at Low Temperature

Box-Behnken designs were used to optimize a process for sesame oil extraction by screw-pressing at low temperature (50 °C). Experimental designs included seed moisture content (SMC), pressing speed (PS), and restriction die (RD) as the main processing parameters. Extractions at pilot plant scale showed a peak in oil recovery (OR, 71.1 ± 2.80%) at 12.3% SMC, 4 mm RD, and 20 rpm PS. Theoretical models were scanned against experimental data in order to scale up the proposed oil extraction process to industrial scale. A fitted model for OR showed a maximum predicted value similar to the highest experimental value (74.4 ± 1.23%) under the following conditions: 8.03% SMC, 10 mm RD, and 20 rpm PS. Chemical quality parameters of oils obtained at both pilot and industrial scales were in the ranges stated in Codex (FAO/WHO) standards for non-refined sesame oil.     

Experiences in Barcelona with the use of fibres in segmental linings

This paper presents the most outstanding experiences regarding the use of fibres as the main reinforcement in precast segmental linings in the metropolitan area of Barcelona. It is known that the addition of structural fibres improves, on the one hand, the mechanical behaviour of the structure during its construction, especially in cases such as the thrust of the jacks, and on the other hand it leads to a reduction of the global costs by reducing the conventional passive reinforcement. The aim of this paper consists in presenting three real experiences that are representative of the application of FRC in urban tunnels and a design methodology to take into account the structural contribution of the fibres. Two particular cases of the application of this design method are presented. In the first case, the use of 25 kg/m³ of fibres has led to a reduction of 70% of the conventional reinforcement initially proposed in the project. In the second one, which was planned to employ fibres but without considering its structural contribution, the parametric study reflected the possibility of reducing up to a 38% of the rebars adding 25 kg/m³ of steel fibres in the concrete mixture. In light of good results, construction companies in Spain have become aware of the advantages of using fibres in these structures and have carried out experimental stretches. This attitude has also been influenced by the approval of the new Spanish Code, which includes the FRC as a construction material with design purposes.     

Topology optimization for crashworthiness of thin-walled structures under axial impact using hybrid cellular automata

Although topology optimization is well established in most engineering fields, it is still in its infancy concerning highly non-linear structural applications like vehicular crashworthiness. One of the approaches recently proposed and based on Hybrid Cellular Automata is modified here such that it can be applied for the first time to thin-walled structures. Classical methods based on voxel techniques, i.e., on solid three-dimensional volume elements, cannot derive structures made from thin metal sheets where the main energy absorption mode is related to plastic buckling, folding and failure. Because the main components of car structures are made from such thin-walled beams and panels, a special approach using SFE CONCEPT was developed, which is presented in this paper.