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In construction industry, work defects yield time and cost overruns of construction projects and also cause disputes between project participants during construction and operation phases. To date, there hasn't yet been an adequate analytical model to extract useful information from the database of construction defects. The information represented in the form of association rules could enhance quality...
Cutting data mining is an important method to increase efficiency, discover hidden knowledges in cutting database, and provide guidance for cutting decisions. This paper analyze the Apriori algorithm for association rules mining, and make some improvement for this algorithm based on the features of cutting database. Apriori algorithm is improved to mine association rules in cutting database. The results...
Fuzzy extractors are recently proposed error-tolerant cryptographic primitives that are potentially useful to protect biometric templates. However, there are challenges in adopting these primitives. Firstly, fuzzy extractors require the data obtained during both enrollment and verification to be in the same feature representation. However, for better performance on ROC, multiple high quality samples...
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