The most persistent soft-clique in a set of sampled graphs

When searching for characteristic subpatterns in potentially noisy graph data, it appears self-evident that having multiple observations would be better than having just one. However, it turns out that the inconsistencies introduced when different graph instances have different edge sets pose a serious challenge. In this work we address this challenge for the problem of finding maximum weighted cliques. We introduce the concept of most persistent soft-clique. This is subset of vertices, that 1) is almost fully or at least densely connected, 2) occurs in all or almost all graph instances, and 3) has the maximum weight. We present a measure of clique-ness, that essentially counts the number of edge missing to make a subset of vertices into a clique. With this measure, we show that the problem of finding the most persistent soft-clique problem can be cast either as: a) a max-min two person game optimization problem, or b) a min-min soft margin optimization problem. Both formulations lead to the same solution when using a partial Lagrangian method to solve the optimization problems. By experiments on synthetic data and on real social network data we show that the proposed method is able to reliably find soft cliques in graph data, even if that is distorted by random noise or unreliable observations. Copyright 2012 by the author(s)/owner(s).

Soft ferrite used as thermal-magnetic conversion intermedium in the flux pumping technology

Recent progress in material science has proved that high-temperature superconductors, such as bulk melt-processed yttrium barium copper oxide (YBCO) single domains, have a great potential to trap significant magnetic fields. In this paper, we will describe a novel method of YBCO magnetization that only requires the applied field to be at the level of a permanent magnet. Instead of applying a pulsed high magnetic field on the YBCO, a thermally actuated material (TAM), such as Mg0.15}hbox{Cu}0.15} hbox{Zn0.7 Ti0.04}Fe1.96boxO4, has been used as an intermedium to create a travelling magnetic field by changing the local temperature so that the local permeability is changed to build up the magnetization of the YBCO gradually after multiple pumping cycles. It is well known that the relative permeability of ferrite is a function of temperature and its electromagnetic properties can be greatly changed by adding dopants such as Mg or Ti; therefore, it is considered to be the most promising TAM for future flux pumping technology. Ferrite samples were fabricated by means of the conventional ceramic method with different dopants. Zinc and iron oxides were used as raw materials. The samples were sintered at 1100 C, 1200 C} , and 1300 C. The relative permeability of the samples was measured at temperatures ranging from 77 to 300 K. This work investigates the variation of the magnetic properties of ferrites with different heat treatments and doping elements and gives a smart insight into finding better ferrites suitable for flux pumping technology. © 2002-2011 IEEE.

An example of the use of neural computing techniques in materials science - The modelling of fatigue thresholds in Ni-base superalloys

Two adaptive numerical modelling techniques have been applied to prediction of fatigue thresholds in Ni-base superalloys. A Bayesian neural network and a neurofuzzy network have been compared, both of which have the ability to automatically adjust the network's complexity to the current dataset. In both cases, despite inevitable data restrictions, threshold values have been modelled with some degree of success. However, it is argued in this paper that the neurofuzzy modelling approach offers real benefits over the use of a classical neural network as the mathematical complexity of the relationships can be restricted to allow for the paucity of data, and the linguistic fuzzy rules produced allow assessment of the model without extensive interrogation and examination using a hypothetical dataset. The additive neurofuzzy network structure means that redundant inputs can be excluded from the model and simple sub-networks produced which represent global output trends. Both of these aspects are important for final verification and validation of the information extracted from the numerical data. In some situations neurofuzzy networks may require less data to produce a stable solution, and may be easier to verify in the light of existing physical understanding because of the production of transparent linguistic rules. © 1999 Elsevier Science S.A.

The soft impact response of composite laminate beams

The quasi-static and dynamic responses of laminated beams of equal areal mass, made from monolithic CFRP and Ultra high molecular weight Polyethylene (UHMWPE), have been measured. The end-clamped beams were impacted at mid-span by metal foam projectiles to simulate localised blast loading. The effect of clamping geometry on the response was investigated by comparing the response of beams bolted into the supports with the response of beams whose ends were wrapped around the supports. The effect of laminate shear strength upon the static and dynamic responses was investigated by testing two grades of each of the CFRP and UHMWPE beams: (i) CFRP beams with a cured matrix and uncured matrix, and (ii) UHMWPE laminates with matrices of two different shear strengths. Quasi-static stretch-bend tests indicated that the load carrying capacity of the UHWMPE beams exceeds that of the CFRP beams, increases with diminishing shear strength of matrix, and increases when the ends are wrapped rather than through-bolted. The dynamic deformation mode of the beams is qualitatively different from that observed in the quasi-static stretch-bend tests. In the dynamic case, travelling hinges emanate from the impact location and propagate towards the supports; the beams finally fail by tensile fibre fracture at the supports. The UHMWPE beams outperform the CFRP beams in terms of a lower mid-span deflection for a given impulse, and a higher failure impulse. Also, the maximum attainable impulse increases with decreasing shear strength for both the UHMWPE and CFRP beams. The ranking of the beams for load carrying capacity in the quasi-static stretch-bend tests is identical to that for failure impulse in the impact tests. Thus, the static tests can be used to gauge the relative dynamic performances of the beams. © 2013 Elsevier Ltd. All rights reserved.

Interaction model for steel compliant riser on soft seabed

The use of catenary steel-compliant-riser (SCR) systems has increased as hydrocarbon production has moved progressively farther offshore and into deeper waters. The issue of fatigue damage caused by cyclic interaction of a riser with the seabed has gained prominence with the widespread use of SCRs and with the lengthening of the spans. The problem involves a number of complex factors, including trench configuration, nonlinear soil stiffness, breakaway of the riser from the seafloor, and degradation of soil resistance during cyclic loading. This paper presents a soilinteraction model capable of modeling these complexities, using input parameters that can be obtained with reasonable expenditure. Model simulations for typical offshore soft-soil conditions indicate that the model is capable of realistic predictions of cyclic bending moments. The degradation of soil resistance has a major effect on cyclic bending moments, particularly when uplift motions at the riser touchdown point (TDP) are large. © 2008 Society of Petroleum Engineers.

Modeling of soft clays response for seismic triggering of submarine slides

Submarine landslides pose considerable hazards to coastal communities and offshore structures. The difficulty and cost of obtaining undisturbed samples of offshore soils for determining material properties required for slope stability analyses contribute to the complexity of the problem. There are significant advantages in using a simplified model for the seismic response of submarine slopes, compatible with the limited amount of information that can be realistically gathered, but still able to capture the key elements of clay behavior. This paper illustrates the process of parameter determination and calibration of the SIMPLE DSS model, developed for the study of seismic triggering of submarine slope instabilities. The selection of parameters and predictions of monotonic and cyclic simple shear response are carried out for Boston Blue Clay, a marine clay extensively studied and with a large experimental database available in the literature. The results show that the simplified model is able to reproduce the important trends in the response of the soil, especially in accounting for the effect of the slope.

Seismic triggering of submarine slides in soft cohesive soil deposits

The geological profile of many submerged slopes on the continental shelf consists of normally to lightly overconsolidated clays with depths ranging from a few meters to hundreds of meters. For these soils, earthquake loading can generate significant excess pore water pressures at depth, which can bring the slope to a state of instability during the event or at a later time as a result of pore pressure redistribution within the soil profile. Seismic triggering mechanisms of landslide initiation for these soils are analyzed with the use of a new simplified model for clays which predicts realistic variations of the stress-strain-strength relationships as well as pore pressure generation during dynamic loading in simple shear. The proposed model is implemented in a finite element program to analyze the seismic response of submarine slopes. These analyses provide an assessment of the critical depth and estimated displacements of the mobilized materials and thus are important components for the estimation of submarine landslide-induced tsunamis. © 2003 Elsevier B.V. All rights reserved.

A Grassmann-Rayleigh quotient iteration for computing invariant subspaces

The classical Rayleigh quotient iteration (RQI) allows one to compute a one-dimensional invariant subspace of a symmetric matrix A. Here we propose a generalization of the RQI which computes a p-dimensional invariant subspace of A. Cubic convergence is preserved and the cost per iteration is low compared to other methods proposed in the literature.