Cross-modal integration processes are essential for service robots to reliably perceive relevant parts of the partially known unstructured environment. We demonstrate how multimodal integration on different abstraction levels leads to reasonable behavior that would be difficult to achieve with unimodal approaches. Sensing and acting modalities are composed to multimodal robot skills via a fuzzy multisensor fusion approach. Single modalities constitute basic robot skills that can dynamically be c...

Multimodal documents combining language and graphs are wide-spread in print media as well as in electronic media. One of the most important tasks to be solved in comprehending graph-text combinations is construction of causal chains among the meaning entities provided by modalities. In this study we focus on the role of annotation position and shape of graph lines in simple line graphs on causal attributions concerning the event presented by the annotation and the processes (i.e. increases and d...

The sparse representation-based classification algorithm has been used for human face recognition. But an image database was restricted to human frontal faces with only slight illumination and expression changes. Cropping and normalization of the face needs to be done beforehand. This paper uses a sparse representation-based algorithm for generic image classification with some intra-class variations and background clutter. A hierarchical framework based on the sparse representation is developed ...

This paper presents a method for locating text based on a simplified pulse coupled neural network (PCNN). The PCNN generates a firings map in a similar way to the human visual system with non-linear image processing. The PCNN is used to segment the original image into different planes and edges detected using both the PCNN firings map and a phase congruency detector. The different edges are integrated using an automatically adjusted weighting coefficient. Both the simplified PCNN and the phase c...

A neural network fire detection method was developed using detection information for temperature, smoke density, and CO concentration to determine the probability of three representative fire conditions. The method overcomes the shortcomings of domestic fire alarm systems using single sensor information. Test results show that the identification error rates for fires, smoldering fires, and no fire are less than 5%, which greatly reduces leak-check rates and false alarms. This neural network fire...

Cayley graphs have many good properties as models of communication networks. This study analyzes the reliability of the Cayley graph based on the dihedral graph. Graph theory and analyses show that almost all Cayley graphs of the dihedral graph D_2n are optimal super-λ. The number N_i(G) of cutsets of size i,λ≤i≤λ′ is given as

Partition-Based Global Placement Considering Wire-Density Uniformity for CMP Variations^*

2011, 16(1): 41-50.   doi:10.1016/S1007-0214(11)70007-4

Abstract ( 142 )  ( 31 )   Save

This paper presents a multilevel hypergraph partitioning method that balances constraints on not only the cell area but also the wire weight with a partition-based global placement algorithm that maximizes the wire density uniformity to control chemical-mechanical polishing (CMP) variations. The multilevel partitioning alternately uses two FM variants in the refinement stage to give a more uniform wire distribution. The global placement is based on a top-down recursive bisection framework. The p...