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In order to control the maintenance process effectively and improve the maintenance quality, model for quality control points of equipment maintenance process is formulated in this paper. By analyzing the process of equipment maintenance systematically, Control elements of the process are selected as the control targets to build the equipment maintenance process quality control point model. Therefore the maintenance quality indexes can be determined. Using Analytic hierarchy process, the influence of maintenance quality indexes on the general process of the maintenance quality control points are analyzed and calculated. Further, evaluating method is proposed in this paper for the important influence factors of the quality

Time-series microarray techniques are newly used to monitor large-scale gene expression profiles for studying biological systems. Previous studies have discovered novel regulatory relations among genes by analyzing time-series microarray data. In this study, we investigate the problem of mining similar subsequences in time-series microarray data so as to discover novel gene relations. A functional relationship among genes often presents itself by locally similar and potentially time-shifted patterns in their expression profiles. Although a number ofstudies have been done on time-series data analysis, they are insufficient in handlingfour important issues for time-series microarray data analysis, namely scaling, offset, shift, and noise. We proposed a novel method to address the four issues simultaneously, which consists of three phase, namely angular transformation, symbolic transformation and suffix-tree-based similar subsequences searching. Through experimental evaluation, it is shown that our method can effectively discover biological relations among genes by identifying the similar subsequences. Moreover, the execution efficiency ofour method is much better than other approaches.

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