We focus on the quantitative and local topological properties of range images. We consider the spaces Mm of m × m high-contrast patches of range images for m=?3, 5, 7, 9, 11. Using computational topological tools to analyze range image patches, we detect that M3 (M9, M11) has core subsets with the topology of a circle, M3, M5, M7, M9 and that M11 have some subspaces with the topology of a Klein bottle. We also discover that the largest subspace with the Klein bottle’s topology decreases as the measurements of patches increase, which generalizes the results in the paper of H. Adams and G. Carlsson, and demonstrates properties among optical images and range image patches, which are more similar than those established by Lee et al.
High molecular weight, high functionality diamino telechelic polybutadienes (TPBs) were synthesized by ring-opening metathesis polymerization (ROMP) of 1,5-cyclooctadiene (COD) in the presence of a chain transfer agent, 1,8-dicyano-4-octene, followed by lithium aluminum hydride reduction. Melt coupling of diamino TPB with anhydride-terminated polystyrene (PS-anh) resulted in the formation of styrene-butadiene-styrene (SBS) triblock copolymers; ca. 80% maximum conversion of PS-anh was achieved within 30 s. The results from SAXS, TEM, and rheological measurements of the coupling products confirmed the formation of SBS triblock copolymers having lamellar morphology. A fluorescent-labeled PS-anh was used to study the coupling kinetics by diluting the reactants by the addition of non-functional PS. 相似文献
Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex situations. This paper presents a novel algorithm, called self-learning particle swarm optimizer (SLPSO), for global optimization problems. In SLPSO, each particle has a set of four strategies to cope with different situations in the search space. The cooperation of the four strategies is implemented by an adaptive learning framework at the individual level, which can enable a particle to choose the optimal strategy according to its own local fitness landscape. The experimental study on a set of 45 test functions and two real-world problems show that SLPSO has a superior performance in comparison with several other peer algorithms. 相似文献
Based on the empirical electron theory of solids and molecules, the valence-electron structure (VES) of the rim phase in Ti(C,N)-based cermets was calculated, and the relationship between the VES and plasticity was determined. The results indicated that the plasticity of the rim phase in a Ti(C,N)-based cermet could be defined using the sum of the n a values for the covalent bonds, and that chromium dissolution in the rim phase improved the plasticity of the rim phase. Moreover, a series of experiments showed that adding Cr2C3 to a typical Ti(C,N)-based cermet strengthened the interface. Based on those results, a Ti(C,N)-based cermet with added Cr3C2 was manufactured; the new cermet had more than twice the transverse rupture strength of a typical cermet. 相似文献