4,218 publications from this institution
Searching for renewable and green energy is one of the most urgent challenges to the sustainable development of human civilization owing to the threat of global warming and energy crises. Solar is probably the most abundant clean and renewable energy. Semiconductor nanowires (NWs) have a lot of advantages as candidates for photovoltaic (PV) applications(1) due to their large surface-to-volume ratio, better charge collection(2) and the possibility of enhanced absorption through light trapping(3, 4); at the other side, nanowires will cause large surface and interface recombination, which could be overcome by surface passivation(5) and epitaxial growth of p-n junctions(6). The core-shell geometry of NWs is proposed to be able to enhance the efficiency of charge collection by shortening the paths travelled by minority carriers(5-7), increasing the optical quality of the material(8), or strain engineering of the bandgap(8).
The German high-speed train system (ICE) as one of the critical infrastructures is mapped into a distance-weighted undirected network.The aim of the analysis is to make full use of quantitative graph theory in order to analyze the vulnerabilities of the network and to detect the centers and hubs of the system.When conducting network analysis of railways, there is a tradition of such an analysis that the betweenness centrality measure and the efficiency measure would be applied; however, based on these two measures, we offer a new promising one that we call betweenness-efficiency vulnerability measure, which can be used to detect the most vulnerable nodes on an aggregated level.By analyzing and comparing the results of these three measures, highly vulnerable stations are identified, which therefore have more potential to harm the overall system in case of disruption.This can help decision-makers to understand the structure, behavior and vulnerabilities of the network more directly from the point of view of quantitative graph theory.Finally, the problem of adapting a new vulnerability measure to this kind of system is discussed.
The calculation of the sentence semantic distance acts a base role in many intelligent systems.Based on multiscale analysis,a multi-level semantic distance calculation framework was proposed.All sentence pairs were filtered by word-level semantic distance algorithm first,and then syntax parsing and semantic parsing were executed for the sentence pairs which semantic distances were below the threshold.After getting the standard semantic frameworks,the core conceptions in the frameworks were compared then.The final semantic distances of the sentence pairs passing the second level filter were obtained using isomorphism-based semantic distance algorithm,which could dynamically adjust its weights.Experiments show that the total precision of the method reaches 73.3%.For the cases,it has higher relevance,reaches 91.4%,similar to the semantic-level algorithm.