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Mining actor correlations from TV series enables semantic level video understanding and facilitates users to conduct correlation-based query. In this paper, we introduce a graph-based actor correlations mining framework, which serves as the first attempt for effective actor association presentation and concurrence search. We leverage face detection and tracking to locate actors with 2D-PCA detector...
This paper presents a novel data mining approach for fault diagnosis of turbine-generator units. The proposed rough set theory based approach generates the diagnosis rules from inconsistent and redundant information using genetic algorithm and process of rule generalization. In this paper, a fault diagnosis decision table is obtained from discretization of continuous symptom attributes in the data...
In this paper, we consider hybrid flow shop (HFS) scheduling problem with a special blocking constraint. Objective function is makespan minimization. HFS and RCb blocking constraint are firstly presented. Then, an integer linear model is presented to find the optimal solution and a lower bound is proposed for high size problems. In order to faster obtain a solution, especially for big size problems,...
The increasing number of complex jobs scheduled to execute on embedded systems has increased the importance of fast response times in job scheduling and task switching on embedded processors. This paper addresses the issue of reducing context-switching overhead. We present a novel register file architecture, the paged register file (pRF), that comprises two novel mechanisms for reducing context-switching...
In double patterning lithography (DPL), coloring conflict and stitch minimization are the two main challenges. Post layout decomposition algorithm may not be enough to achieve high quality solution for DPL-unfriendly designs, due to complex 2D patterns in lower metal layers. Therefore, DPL-friendliness is needed at routing stage. Another key yield improvement technique is redundant via insertion....
With the rapid development of information technology, the competition of market is increasingly severe. The demand of customers tends to individuation, and different customers bring different profitability for corporations, so it is important to analyze the precise customer profitability, to distinguish between different types of customers and to carry out the right management to control costs of...
Clustering analysis is an important function of data mining. Various clustering methods are need for different domains and applications. A clustering algorithm for data mining based on swarm intelligence called Ant-Cluster is proposed in this paper. Ant-Cluster algorithm introduces the concept of multi-population of ants with different speed, and adopts fixed moving times method to deal with outliers...
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