A golden template self-generating method for patterned wafer inspection

This paper presents a novel golden template self-generating technique for detecting possible defects in periodic two-dimensional wafer images. A golden template of the patterned wafer image under inspection can be obtained from the wafer image itself and no other prior knowledge is needed. It is a bridge between the existing self-reference methods and image-to-image reference methods. Spectral estimation is used in the first step to derive the periods of repeating patterns in both directions. Then a building block representing the structure of the patterns is extracted using interpolation to obtain sub-pixel resolution. After that, a new defect-free golden template is built based on the extracted building block. Finally, a pixel-to-pixel comparison is all we need to find out possible defects. A comparison between the results of the proposed method and those of the previously published methods is presented

The development of computer science research in the People's Republic of China 2000-2009: A bibliometric study

This paper reports a bibliometric study of the development of computer science research in the People's Republic of China in the 21st century, using data from the Web of Science, Journal Citation Reports and CORE databases. Focusing on the areas of data mining, operating systems and web design, it is shown that whilst the productivity of Chinese research has risen dramatically over the period under review, its impact is still low when compared with established scientific nations such as the USA, the UK and Japan. The publication and citation data for China are compared with corresponding data for the other three BRIC nations (Brazil, Russian and India). It is shown that China dominates the BRIC nations in terms of both publications and citations, but that Indian publications often have a greater individual impact. © The Author(s) 2012

Integrating Document Clustering and Topic Modeling

Document clustering and topic modeling are two closely related tasks which can mutually benefit each other. Topic modeling can project documents into a topic space which facilitates effective document clustering. Cluster labels discovered by document clustering can be incorporated into topic models to extract local topics specific to each cluster and global topics shared by all clusters. In this paper, we propose a multi-grain clustering topic model (MGCTM) which integrates document clustering and topic modeling into a unified framework and jointly performs the two tasks to achieve the overall best performance. Our model tightly couples two components: a mixture component used for discovering latent groups in document collection and a topic model component used for mining multi-grain topics including local topics specific to each cluster and global topics shared across clusters.We employ variational inference to approximate the posterior of hidden variables and learn model parameters. Experiments on two datasets demonstrate the effectiveness of our model.Comment: Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013

A golden block based self-refining scheme for repetitive patterned wafer inspections

This paper presents a novel technique for detecting possible defects in two-dimensional wafer images with repetitive patterns using prior knowledge. It has a learning ability that is able to create a golden block database from the wafer image itself, modify and refine its content when used in further inspections. The extracted building block is stored as a golden block for the detected pattern. When new wafer images with the same periodical pattern arrives, we do not have to re-calculate its periods and building block. A new building block can be derived directly from the existing golden block after eliminating alignment differences. If the newly derived building block has better quality than the stored golden block, then the golden block is replaced with the new building block. With the proposed algorithm, our implementation shows that a significant amount of processing time is saved. And the storage overhead of golden templates is also reduced significantly by storing golden blocks only

Visualization in spatial modeling

This chapter deals with issues arising from a central theme in contemporary computer modeling - visualization. We first tie visualization to varieties of modeling along the continuum from iconic to symbolic and then focus on the notion that our models are so intrinsically complex that there are many different types of visualization that might be developed in their understanding and implementation. This focuses the debate on the very way of 'doing science' in that patterns and processes of any complexity can be better understood through visualizing the data, the simulations, and the outcomes that such models generate. As we have grown more sensitive to the problem of complexity in all systems, we are more aware that the twin goals of parsimony and verifiability which have dominated scientific theory since the 'Enlightenment' are up for grabs: good theories and models must 'look right' despite what our statistics and causal logics tell us. Visualization is the cutting edge of this new way of thinking about science but its styles vary enormously with context. Here we define three varieties: visualization of complicated systems to make things simple or at least explicable, which is the role of pedagogy; visualization to explore unanticipated outcomes and to refine processes that interact in unanticipated ways; and visualization to enable end users with no prior understanding of the science but a deep understanding of the problem to engage in using models for prediction, prescription, and control. We illustrate these themes with a model of an agricultural market which is the basis of modern urban economics - the von Thünen model of land rent and density; a model of urban development based on interacting spatial and temporal processes of land development - the DUEM model; and a pedestrian model of human movement at the fine scale where control of such movements to meet standards of public safety is intrinsically part of the model about which the controllers know intimately. © Springer-Verlag Berlin Heidelberg 2006

Large-eddy simulation for flow and dispersion in urban streets

Large-eddy simulations (LES) with our recently developed inflow approach (Xie &Castro, 2008a) have been used for flow and dispersion within a genuine city area -the DAPPLE site, located at the intersection of Marylebone Rd and Gloucester Plin Central London. Numerical results up to second-order statistics are reported fora computational domain of 1.2km (streamwise) x 0.8km (lateral) x 0.2km (in fullscale), with a resolution down to approximately one meter in space and one secondin time. They are in reasonable agreement with the experimental data. Such a comprehensiveurban geometry is often, as here, composed of staggered, aligned, squarearrays of blocks with non-uniform height and non-uniform base, street canyons andintersections. Both the integrative and local effect of flow and dispersion to thesegeometrical patterns were investigated. For example, it was found that the peaksof spatially averaged urms, vrms, wrms and < u0w0 > occurred neither at the meanheight nor at the maximum height, but at the height of large and tall buildings. Itwas also found that the mean and fluctuating concentrations in the near-source fieldis highly dependent on the source location and the local geometry pattern, whereasin the far field (e.g. >0.1km) they are not. In summary, it is demonstrated thatfull-scale resolution of around one meter is sufficient to yield accurate prediction ofthe flow and mean dispersion characteristics and to provide reasonable estimationof concentration fluctuation

Global Λ\Lambda Polarization in high energy collisions

With a Yang-Mills flux-tube initial state and a high resolution (3+1)D Particle-in-Cell Relativistic (PICR) hydrodynamics simulation, we calculate the $\Lambda$ polarization for different energies. The origination of polarization in high energy collisions is discussed, and we find linear impact parameter dependence of the global $\Lambda$ polarization. Furthermore, the global $\Lambda$ polarization in our model decreases very fast in the low energy domain, and the decline curve fits well the recent results of Beam Energy Scan (BES) program launched by the STAR collaboration at the Relativistic Heavy Ion Collider (RHIC). The time evolution of polarization is also discussed