With the emergence of the semantic web, ontology has attracted a great deal of attention in field of information retrieval. But the conceptual formalism supported by typical ontology is not sufficient for handling incomplete information that is confronted in the real world knowledge. To tackle this problem, a semantic information retrieval approach based on a rough ontology is proposed. Rough ontology in this paper is in the form of an ontology information system. Given a keyword based query, our approach infers the individuals and properties correlated to the query through a procedure of association searches in the rough ontology, and takes properties as equivalence relations to construct an approximation space of rough ontology. Afterward, an algorithm of computing similarity in rough ontology is presented, and approximation space is employed to compute similarity for ranking documents in semantic document indexing space. The proposed approach has been compared with two other information retrieval techniques, and the experiments conducted on CNKI collections, support the better efficacy which results from our approach.
This paper focuses on the detection technology for Electric Multiple Units (EMU) break valves features. Aiming at the issues of EMU break valves features detection, this paper propose a kind of EMU break valves feature detection technology based on neural network algorithm which does not overly dependent on break valve characteristic parameters. The spatial function neural network algorithm is used to predict the EMU break valves features. The experiments illustrate the proposed algorithm can increase the detection accuracy with satisfactory effects in EMU break valves features detection.
Semiconductor device manufacturers have made technological advances in fabricating devices at 65nm and 45nm nodes. Technology is advancing towards 32nm node devices. Reticles at these device nodes are designed with tight critical dimension (CD) specifications and sub-resolution features. Inspection tools capable of detecting CD defects on the order of 20 nm are required to accommodate these device nodes. To meet this challenge, KLA-Tencor has developed a new "CD Detector" capability on the TeraScanHR reticle inspection tool that efficiently detects two-sided CD defects on reticles at the 45nm node and beyond. The CD Detector is available in both Die-to-Die (DD) and Die-to-Database (DB) inspection modes. This paper presents results of a CD Detector Beta evaluation on variety of advanced reticles in a production setting at Advanced Mask Technology Center (AMTC) in Germany. Inspection results will demonstrate improved sensitivity to two-sided CD defects and good inspectability, at inspection times similar to a standard HiRes inspection. Discussion will focus on enabling the highest sensitivity to CD defects at 72nm pixel inspections, which is suitable for advanced research and development studies, as well as improved sensitivity at 90nm pixel inspections for higher productivity.
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