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Existing node contact pattern and data routing algorithm of mobile delay tolerant network are introduced as follows.
The WDP was exemplified by the U.S.A. food pattern, and data was also obtained from the FAO food balance sheets.
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In particular typical concentrations in products, use patterns and data on product use are missing.
Evaluation of the sequence patterns and data entry were independently performed by two observers.
The technical appendix gives a more detailed description of the data collection and classification, model building, missing data patterns, and data imputation, along with a number of supplementary results.
In the field of pattern recognition and data mining, various methods and models are proposed to solve different problems.
Internal validity is ensured by making use of the clear formulation of the research framework, pattern matching, and data triangulation.
The K-Nearest-Neighbor (K-NN) classifier is one of the most basic classifiers for pattern recognition and data classification.
Pattern recognition and data classification were conducted using MATLAB (The MathWorks).
In pattern recognition and data mining, recall is defined as the fraction of relevantly retrieved instances.
In pattern recognition and data mining, precision is the fraction of relevantly retrieved instances.
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