With people's increasing concern about food safety, cold-chain logistics distribution centre is playing an important role in preventing food from going bad. Now cold-chain logistics distribution centres have the problems of too much transportation, low degree of automation, unreasonable layout planning, complex distribution process etc. It is important to solve these problems in order to achieve efficient distribution. Firstly the modeling and simulation for the operation process of a fruits and vegetables cold-chain logistics distribution centre by using Flexsim software is realized. Then the paper analyses the preliminary output data and finds out the bottleneck and idle resources. Finally this paper makes adjustments for the system to get a better result which hopes to give a reference for the modeling and simulation for the operation process of other cold-chain logistics distribution centres.

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Chinese Electronic Medical Records (EMRs) contains a large number of complex medical free text which includes a variety of information, such as temporal information, patients’ symptoms and laboratory data. However, as an important knowledge base, these unstructured text data in EMR are hard to process directly by computer to support further medical research. This paper proposes a novel text structuring method to extract knowledge from EMR texts and reorganize them in chronological order according to the temporal information in the text. By implementing some entropy-based algorithms as contrast, experiments evaluate the performance of the proposed method, which indicates the new method can significantly reduce the complexity of EMR text. This work is significant in structuring the EMR free text into temporal-structured data for further medical analysis.

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This paper presents an improved outlier detection algorithm based on K-means clustering to identify suspicious medical fraud in medical insurance audits. This paper elaborates how to preprocess medical insurance data for medical insurance fraud, and puts forward the improved principle and process of outlier detection algorithm based on K-means clustering. The experiment is carried out by using real medical insurance data, and the efficiency of the algorithm conducted a test.