Electronic prototyping

The potential benefits of automation in space are significant. The science base needed to support this automation not only will help control costs and reduce lead-time in the earth-based design and construction of space stations, but also will advance the nation's capability for computer design, simulation, testing, and debugging of sophisticated objects electronically. Progress in automation will require the ability to electronically represent, reason about, and manipulate objects. Discussed here is the development of representations, languages, editors, and model-driven simulation systems to support electronic prototyping. In particular, it identifies areas where basic research is needed before further progress can be made

Sign Stable Projections, Sign Cauchy Projections and Chi-Square Kernels

The method of stable random projections is popular for efficiently computing the Lp distances in high dimension (where 0<p<=2), using small space. Because it adopts nonadaptive linear projections, this method is naturally suitable when the data are collected in a dynamic streaming fashion (i.e., turnstile data streams). In this paper, we propose to use only the signs of the projected data and analyze the probability of collision (i.e., when the two signs differ). We derive a bound of the collision probability which is exact when p=2 and becomes less sharp when p moves away from 2. Interestingly, when p=1 (i.e., Cauchy random projections), we show that the probability of collision can be accurately approximated as functions of the chi-square similarity. For example, when the (un-normalized) data are binary, the maximum approximation error of the collision probability is smaller than 0.0192. In text and vision applications, the chi-square similarity is a popular measure for nonnegative data when the features are generated from histograms. Our experiments confirm that the proposed method is promising for large-scale learning applications

New Methods for Inferring Past Climatic Changes from Underground Temperatures

In this thesis new methods have been developed for the recovery of past surface temperature variations from underground temperature-depth profiles. This has been undertaken from a Bayesian standpoint with an emphasis on model comparison, which allows differently parameterised inverse models (inferred past temperature histories) to be automatically constructed and compared in the light of the data and the prescribed prior information. In the first contribution a new method for inverting temperature-depth profiles is presented which relies on trans-dimensional Bayesian sampling. The temperature histories are parameterised in terms of a variable number of linear segments over time. Relying on the natural parsimony of Bayesian inference, whereby simpler models which can adequately explain the data are preferred, the complexity or roughness of the temperature histories can be determined without the need for explicit a priori smoothing. This method therefore allows a more objective inference of the past temperature changes. These concepts are extended to the spatial domain in the following chapter using the method of Bayesian partition modelling. This seeks to find the posterior distribution of the number and spatial distribution of independent temperature histories given a spatially distributed ensemble of temperature-depth profiles. The results from application to 23 real boreholes in the UK are discussed in detail and show a clear preference for 8 or 9 independent (and mostly contrasting) temperature histories. It is thus concluded that the majority of these data cannot be considered as reliable sources of palaeoclimate reconstruction. A 3D finite element heat transfer forward model is developed in the latter part of the thesis, and is used to simulate underground temperatures. This forward model is linked to the first of the two Bayesian inverse methods described above. The effect of the reduction in average ground surface temperature with altitude is included in the forward model and inversion of the resultant profiles using a 1D forward model is shown to give significant discrepancies in the inferred temperature histories. Finally the inversion results from the Bayesian formulation are compared with those using a conventional gradient descent method. The thesis concludes with some possibilities for future research in this field which builds upon the work presented herein

Last glacial maximum radiative forcing from mineral dust aerosols in an Earth System model

The mineral dust cycle in pre-industrial (PI) and last glacial maximum (LGM) simulations with the CMIP5 model HadGEM2-A is evaluated. The modeled global dust cycle is enhanced at the LGM, with larger emissions in the Southern hemisphere, consistent with some previous studies. Two different dust uplift schemes within HadGEM2 both show a similar LGM/PI increase in total emissions (60% and 80%) and global loading (100% and 75%), but there is a factor of three difference in the top of the atmosphere net LGM-PI direct radiative forcing (-1.2Wm−2 and -0.4Wm−2, respectively). This forcing is dominated by the short-wave effects in both schemes. Recent reconstructions of dust deposition fluxes suggest that the LGM increase is overestimated in the Southern Atlantic and underestimated over east Antarctica. The LGM dust deposition reconstructions do not strongly discern between these two dust schemes because deposition is dominated by larger (2-6Îijm diameter) particles for which the two schemes show similar loading in both time periods. The model with larger radiative forcing shows a larger relative emissions increase of smaller particles. This is because of the size-dependent friction velocity emissions threshold and different size distribution of the soil source particles compared with the second scheme. Size-dependence of the threshold velocity is consistent with the theory of saltation, implying that the model with larger radiative forcing is more realistic. However, the large difference in radiative forcing between the two schemes highlights the size distribution at emission as a major uncertainty in predicting the climatic effects of dust cycle changes

Validating a network hub in leukaemia stem cells

No abstract available