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13 results on '"Cao, Mengyun"'

2. What Makes it Difficult to Understand a Scientific Literature?

Author

Cao, Mengyun, Tian, Jiao, Cheng, Dezhi, Liu, Jin, and Sun, Xiaoping

Subjects
Computer Science - Computation and Language
Abstract

In the artificial intelligence area, one of the ultimate goals is to make computers understand human language and offer assistance. In order to achieve this ideal, researchers of computer science have put forward a lot of models and algorithms attempting at enabling the machine to analyze and process human natural language on different levels of semantics. Although recent progress in this field offers much hope, we still have to ask whether current research can provide assistance that people really desire in reading and comprehension. To this end, we conducted a reading comprehension test on two scientific papers which are written in different styles. We use the semantic link models to analyze the understanding obstacles that people will face in the process of reading and figure out what makes it difficult for human to understand a scientific literature. Through such analysis, we summarized some characteristics and problems which are reflected by people with different levels of knowledge on the comprehension of difficult science and technology literature, which can be modeled in semantic link network. We believe that these characteristics and problems will help us re-examine the existing machine models and are helpful in the designing of new one., Comment: Accepted by SKG2015

Published
2015

8. The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link Network

Author

Cao, Mengyun, Sun, Xiaoping, Zhuge, Hai, Cao, Mengyun, Sun, Xiaoping, and Zhuge, Hai

Abstract

The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing.

Published
2018

9. Research on induction heating welding process of large diameter Cu/Al alloy thin wall tube.

Author

CAO Mengyun, CHENG Shiduo, HUANG Tian, LIU Xinkuan, MA Fengcang, LIU Ping, WANG Ziyan, XUE Siyu, and CAO Kai

Abstract

Using induction heating method, in this paper, a kind of operational and uncomplicated process was explored, by which large diameter thin-walled aluminum alloy and copper pipe could be welded. The effect of welding current, welding-length and welding high temperature insulation time on large diameter thin-walled copper aluminum tubes was studied. The microstructures of the interface were observed by scanning electron microscope (SEM) and polarizing microscope (PM), and the interfacial reaction products were analyzed by X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDX). When the heating time was 6 s and weld length was 15 mm, the quality of copper aluminum welded pipe was the best, and the tensile strength was highest. The copper-aluminum intermediate compounds layer were only Al2 Cu and AlCu, and no Al4Cu9-type compounds had been found. [ABSTRACT FROM AUTHOR]

Published
2019
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