Self-managed topologies in P2P networks

The problem of efficient resource location is an important open issue in P2P systems. This paper introduces DANTE, a self-adapting P2P system that changes its peer links to form topologies where resources are located in an efficient manner via random walks. Additionally, this same self-adaptation capacity makes DANTE capable of reacting to events like changes in the system load or attacks on well-connected nodes by adjusting the topology to the new scenario. This adaptive behavior emerges as the global result of the individual work of nodes, without the intervention of any central entity or the need for global knowledge. Simulations show that this adaptation process makes the system scalable, resilient to attacks, and tolerant to a high transitivity of peers. Simulations are also used to compare this solution with other well-known self-adapting P2P system. From these results it can be concluded that the topologies achieved by DANTE offer better performance.     

A new control scheme for visual servoing

This research presents a new control scheme for visual servoing that takes into account the delay introduced by image acquisition and image processing. Firstly, previous control schemes for visual servoing are discussed and then a new control scheme is proposed and fully described. Afterwards, the capabilities (steady-state errors, stability margins, step time response, etc.) of the proposed control scheme and of previous ones are analytically analyzed and compared. Next, several simulations and experimental results are provided to validate the analytical results and to illustrate the benefits of the proposed control scheme. In particular, it is shown that this new control scheme clearly improves the performance of the previous ones.     

3D Semantic Scene Completion: A Survey

International Journal of Computer Vision - Semantic scene completion (SSC) aims to jointly estimate the complete geometry and semantics of a scene, assuming partial sparse input. In the last years...     

Bond calibration method for Young’s modulus determination in the discrete element method framework

A new methodology for the calibration of bond microparameters in rocks represented by a package of joined random spherical particles in the discrete element method (DEM) framework is presented. Typically, calibration is achieved through a trial-and-error procedure using several DEM simulations of uniaxial compressive tests (UCTs). The bond calibration model (BCM) does not need a time-dependent UCT-DEM simulation to establish the relation between the microproperties of the bond and the macroproperties of the rock specimen. The BCM uses matrices to describe the interaction forces exerted by bonds and, by means of an assembly process similar to the finite element method, it can describe the complex network of bonds, enabling the model to capture small variations in particle size and bond distribution as demonstrated in this work. In this work, the BCM is presented and compared with UCT simulations performed using Esys Particle software. Multiple simulations are done with constant bond properties and different particle size ratios (\(D_{MAX}/D_{MIN})\) that cause small variations in the specimen’s Young’s modulus; these variations are well captured by the BCM with an error of <10%.     

Carbon nano-onion composites: Physicochemical characteristics and biological activity

Carbon nano-onion/surfactant (CNO/surfactant) composites offer the possibility to easily produce the soluble nanostructures. That approach combines the hydrophilicity of surfactants with the robustness of carbon structures to produce composites with superior and unusual physicochemical properties. We used the following surfactants: hexadecyltrimethylammonium bromide (CTAB), sodium dodecyl sulfate (SDS), sodium dodecyl benzene sulfonate (SDBS), 4-(1,1,3,3-tetramethylbutyl)phenyl-polyethylene glycol (Triton X-100), and polyethylene glycol sorbitan monolaurate (Tween 20) to non-covalently modify CNO surfaces. The existence of stable CNO composites are clearly evidenced by direct transmission electron microscopy observations, which are also supported by thermogravimetric analyses. Dynamic light scattering and zeta potential confirmed their dispersion and stability. Additionally, the biological activity of well-dispersed CNO/surfactant composites against a strain of Escherichia coli was assayed. In vitro antimicrobial assays for the composites revealed that only the CNO/CTAB composite decreased cell viability. This activity could be assigned to the simple composite dissociation in water solutions, however antimicrobial properties of the composite are slightly better when compared with pure CTAB. This indicate some synergic effect with respect to the properties of the pure surfactant.     

Solid biofuels in Mexico: a sustainable alternative to satisfy the increasing demand for heat and power

Bioenergy is the largest renewable energy source in Mexico with an estimated 4–9% of total current energy demand. There are large uncertainties and contrasting estimates regarding its current extent and end-uses, particularly with traditional uses. However, a large potential exists to improve the efficiency of existing uses and, at the same time, to diversify the use of SBF in the industrial and power sectors. This paper aims at: providing the first updated and comprehensive estimate of current SBF demand in Mexico including traditional and modern uses; providing a consistent estimate of actual SBF supply potential; estimating the total potential substitution of fossil fuels that could be achieved by SBF considering an integrated “modernization scenario”; and finally describing the main barriers limiting SBF to fully triggering its potential. Results show that current SBF consumption reached 481 PJ/yr in 2015; SBF supply potential reaches 3622 PJ/yr, out of which 883 PJ/yr could be used to substitute up to 29% of current demand of FF, mitigating 66 MtCO_2e/yr of greenhouse gas (GHG) emissions, or near 88 MtCO_2e/yr if mitigation from traditional uses is added.     

Process optimization in the self-reacting friction stir welding of aluminum 6061-T6

Self-reacting friction stir welding (SR-FSW), also called bobbin-tool friction stir welding (BT-FSW), is a solid state welding process similar to friction stir welding (FSW) except that the tool has two opposing shoulders instead of the shoulder and a backing plate found in FSW. The tool configuration results in greater heat input and a symmetrical weld macrostructure. A significant amount of information has been published in the literature concerning traditional FSW while little has been published about SR-FSW. An optimization experiment was performed using a factorial design to evaluate the effect of process parameters on the weld temperature, surface and internal quality, and mechanical properties of self-reacting friction stir welded aluminum alloy 6061-T6 butt joints. The parameters evaluated were tool rotational speed, traverse speed, and tool plunge force. A correlation between weld temperature, defect formation (specifically galling and void formation), and mechanical properties was found. Optimum parameters were determined for the welding of 8-mm-thick 6061-T6 plate.     

Relaxations in semicrystalline polyethyleneterephthalate using thermally stimulated currents

Relaxation processes at temperatures above 20 °C in semicrystalline polyethylene-terephthalate have been studied using thermally stimulated depolarization currents (TSDC). The discharge curve shows three relaxation peaks (c, c and *) whose positions and intensities depend on the polarization conditions and the crystallinity. Relaxations c and c are heteropolar, while * may be homopolar or heteropolar according to the polarization temperature used. The effect of the crystallinity on these relaxations has been analysed by the thermal steps stimulation (TSS) method applied to an amorphous sample. Results show that c is fundamentally a dipolar relaxation associated with the amorphous interlamellar zone. The relaxation c is associated with the release of a free charge trapped in the amorphous regions, and * is a Maxwell–Wagner–Sillars relaxation associated with crystalline – amorphous interphases. For polarization temperatures above 150 °C, two relaxations are observed only as a consequence of overlapping C and * relaxations. © 1998 Chapman & Hall     

The use of coevolution and the artificial immune system for ensemble learning

This paper presents two new approaches for constructing an ensemble of neural networks (NN) using coevolution and the artificial immune system (AIS). These approaches are extensions of the CLONal Selection Algorithm for building ENSembles (CLONENS) algorithm. An explicit diversity promotion technique was added to CLONENS and a novel coevolutionary approach to build neural ensembles is introduced, whereby two populations representing the gates and the individual NN are coevolved. The former population is responsible for defining the ensemble size and selecting the members of the ensemble. This population is evolved using the differential evolution algorithm. The latter population supplies the best individuals for building the ensemble, which is evolved by AIS. Results show that it is possible to automatically define the ensemble size being also possible to find smaller ensembles with good generalization performance on the tested benchmark regression problems. More interestingly, the use of the diversity measure during the evolutionary process did not necessarily improve generalization. In this case, diverse ensembles may be found using only implicit diversity promotion techniques.