Growing Graphs with Hyperedge Replacement Graph Grammars

Discovering the underlying structures present in large real world graphs is a fundamental scientific problem. In this paper we show that a graph's clique tree can be used to extract a hyperedge replacement grammar. If we store an ordering from the extraction process, the extracted graph grammar is guaranteed to generate an isomorphic copy of the original graph. Or, a stochastic application of the graph grammar rules can be used to quickly create random graphs. In experiments on large real world networks, we show that random graphs, generated from extracted graph grammars, exhibit a wide range of properties that are very similar to the original graphs. In addition to graph properties like degree or eigenvector centrality, what a graph "looks like" ultimately depends on small details in local graph substructures that are difficult to define at a global level. We show that our generative graph model is able to preserve these local substructures when generating new graphs and performs well on new and difficult tests of model robustness.Comment: 18 pages, 19 figures, accepted to CIKM 2016 in Indianapolis, I

Silicon-on ceramic process: Silicon sheet growth and device development for the large-area silicon sheet task of the low-cost solar array project

The technical feasibility of producing solar-cell-quality sheet silicon to meet the Department of Energy (DOE) 1986 overall price goal of $0.70/watt was investigated. With the silicon-on-ceramic (SOC) approach, a low-cost ceramic substrate is coated with large-grain polycrystalline silicon by unidirectional solidification of molten silicon. This effort was divided into several areas of investigation in order to most efficiently meet the goals of the program. These areas include: (1) dip-coating; (2) continuous coating designated SCIM-coating, and acronym for Silicon Coating by an Inverted Meniscus (SCIM); (3) material characterization; (4) cell fabrication and evaluation; and (5) theoretical analysis. Both coating approaches were successful in producing thin layers of large grain, solar-cell-quality silicon. The dip-coating approach was initially investigated and considerable effort was given to this technique. The SCIM technique was adopted because of its scale-up potential and its capability to produce more conventiently large areas of SOC

Dip coating process: Silicon sheet growth development for the large-area silicon sheet task of the low-cost silicon solar array project

The research program to investigate the technical and economic feasibility of producing solar-cell-quality sheet silicon by dip-coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon is reported. The initial effort concentrated on the design and construction of the experimental dip-coating facility. The design was completed and its experimental features are discussed. Current status of the program is reported, including progress toward solar cell junction diffusion and miscellaneous ceramic substrate procurement

Dip-coating process: Silicon sheet growth development for the large-area silicon sheet task of the low-cost silicon solar array project

The objective of this research program is to investigate the technical and economic feasibility of producing solar-cell-quality sheet silicon by coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon from the melt. The past quarter demonstrated significant progress in several areas. Seeded growth of silicon-on-ceramic (SOC) with an EFG ribbon seed was demonstrated. Different types of mullite were successfully coated with silicon. A new method of deriving minority carrier diffusion length, L sub n from spectral response measurements was evaluated. ECOMOD cost projections were found to be in good agreement with the interim SAMIS method proposed by JPL. On the less positive side, there was a decrease in cell performance which we believe to be due to an unidentified source of impurities

Silicon on ceramic process. Silicon sheet growth development for the large-area silicon sheet task of the low-cost silicon solar array project

The technical and economic feasibility of producing solar-cell-quality sheet silicon was investigated. The sheets were made by coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon from the melt. Significant progress was made in all areas of the program

Dip coating process: Silicon sheet growth development for the large-area silicon sheet task of the low-cost silicon solar array project

To date, an experimental dip-coating facility was constructed. Using this facility, relatively thin (1 mm) mullite and alumina substrates were successfully dip-coated with 2.5 - 3.0 ohm-cm, p-type silicon with areas of approximately 20 sq cm. The thickness and grain size of these coatings are influenced by the temperature of the melt and the rate at which the substrate is pulled from the melt. One mullite substrate had dendrite-like crystallites of the order of 1 mm wide and 1 to 2 cm long. Their axes were aligned along the direction of pulling. A large variety of substrate materials were purchased or developed enabling the program to commence a substrate definition evaluation. Due to the insulating nature of the substrate, the bottom layer of the p-n junction may have to be made via the top surface. The feasibility of accomplishing this was demonstrated using single crystal wafers

Silicon-on-ceramic process: Silicon sheet growth and device development for the large-area silicon sheet task of the low-cost solar array project

The technical feasibility of producing solar cell quality sheet silicon to meet the DOE 1986 cost goal of 70 cents/watt was investigated. The silicon on ceramic approach is to coat a low cost ceramic substrate with large grain polycrystalline silicon by unidirectional solidification of molten silicon. Results and accomplishments are summarized

Silicon on Ceramic Process: Silicon Sheet Growth and Device Development for the Large-area Silicon Sheet and Cell Development Tasks of the Low-cost Solar Array Project

The technical and economic feasibility of producing solar cell quality sheet silicon was investigated. It was hoped this could be done by coating one surface of carbonized ceramic substrates with a thin layer of large-grain polycrystalline silicon from the melt. Work was directed towards the solution of unique cell processing/design problems encountered with the silicon-ceramic (SOC) material due to its intimate contact with the ceramic substrate. Significant progress was demonstrated in the following areas; (1) the continuous coater succeeded in producing small-area coatings exhibiting unidirectional solidification and substatial grain size; (2) dip coater succeeded in producing thick (more than 500 micron) dendritic layers at coating speeds of 0.2-0.3 cm/sec; and (3) a standard for producing total area SOC solar cells using slotted ceramic substrates was developed

A Bayesian spatio‐temporal model for short‐term forecasting of precipitation fields

With extreme weather events becoming more common, the risk posed by surface water flooding is ever increasing. In this work we propose a model, and associated Bayesian inference scheme, for generating short-term, probabilistic forecasts of localised precipitation on a spatial grid. Our generative hierarchical dynamic model is formulated in discrete space and time with a lattice-Markov spatio-temporal auto-regressive structure, inspired by continuous models of advection and diffusion. Observations from both weather radar and ground based rain gauges provide information from which we can learn the precipitation field through a latent process in addition to unknown model parameters. Working in the Bayesian paradigm provides a coherent framework for capturing uncertainty, both in the underlying model parameters and in our forecasts. Further, appealing to simulation based sampling using MCMC yields a straightforward solution to handling zeros, treated as censored observations, via data augmentation. Both the underlying state and the observations are of moderately large dimension ( [] and [] respectively) and this renders standard inference approaches computationally infeasible. Our solution is to embed the ensemble Kalman smoother within a Gibbs sampling scheme to facilitate approximate Bayesian inference in reasonable time. Both the methodology and the effectiveness of our posterior sampling scheme are demonstrated via simulation studies and by a case study of real data from the Urban Observatory project based in Newcastle upon Tyne, UK