Hot embossing is an effective way to achieve high-quality Microstructures at low cost. At present papers, the effects of
geometry and shear on filling profile and polymer deformation have studied through experiments or computations. In
this paper, the parameters on different polymer deformation modes: single peak, dual peak and embossing stage have
researched. Especially it is referred that the mainly reasons of embossing stage phenomenon are the ratio of cavity width
to height 2w/hi, the ratio of cavity width to tool width w/(w+s), and shear thinning. In addition, the temperature variation
of polymer due to internal friction has discussed with evolution of imprint speed. And the simulation results prove a
better coincidence with experiments.
In this paper, a multi-level image representation model is developed and used for multi-spectral remote sensing image
retrieval in order to narrow the gap between the low-level feature and high-level semantic. This model consists of an
image segmentation part, a feature extraction part and semantic extraction part. The first two parts aim at the extraction
of primitive region feature of an image. In these two steps, an improved JSEG algorithm is used to segment the image
stored in the database, then spectral feature and texture feature are extracted for each region. In semantic extraction part,
the semantic information hidden in different regions of different images is extracted by Bayesian method and expectation
maximization (EM) method. At last, positive example and negative example concept is used in image retrieval instead of
relevant feedback. Experiment shows that this method not only improves the accuracy of the result but also decreases the
complexity of retrieval.