Alcohol-related facial flushing is a sign of compromised alcohol metabolism and increased risk of certain cancers. This project examined how facial flushing might be used to reduce alcohol use to lower cancer risks. Interviews with Chinese university students identified gender, friendship, and drinking purpose as important variables related to whether someone would encourage a person who flushes when drinking alcohol to stop or reduce their drinking. A questionnaire was developed that incorporated these variables into 24 drinking scenarios in which someone flushed while drinking. Students responded whether they would (a) encourage the flusher to stop or drink less; (b) do nothing while wishing they could; or (c) do nothing because there was no need. Analysis of survey responses from 2912 university students showed a three-way interaction of the variables and implied that the probability students will intervene when a drinker flushes was highest when the flusher was a female, a close friend, and the drinking purpose was for fun and lowest if the flusher was a male, the friendship was general, and the drinking purpose was risky. The results provide important details about the social factors affecting how other people respond to a person who flushes when drinking alcohol. This information is useful for those considering ways to reduce and prevent aerodigestive cancers through education and information programs.

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since the CF model has been proposed, it has been successfully applied in some areas and there is one of the representative systems MYCIN. However, the traditional CF model also has a few problems, for example, the inconsistencies of the degree of belief in a hypothesis and Conditional probability to some extent. Then this paper will proposed an improved method of the CF model which is the improved CF model base on normal distribution and Euclidean distance. It can resolve the serious inconsistencies of the degree of belief in a hypothesis and Conditional probability to some extent effectively.Index Terms-CF model, uncertainly reasoning, normal Distribution, Euclidean Distance I.

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