• Journal of KIISE:Databases
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• v.32 no.3
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• pp.263-275
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• 2005

In a large DNA database, indexing techniques are widely used for rapid approximate sequence searching. However, most indexing techniques require a space larger than original databases, and also suffer from difficulties in seamless integration with DBMS. In this paper, we suggest a space-efficient and disk-based indexing and query processing algorithm for approximate DNA sequence searching, specially exact match queries, wildcard match queries, and k-mismatch queries. Our indexing method places a sliding window at every possible location of a DNA sequence and extracts its signature by considering the occurrence frequency of each nucleotide. It then stores a set of signatures using a multi-dimensional index, such as R*-tree. Especially, by assigning a weight to each position of a window, it prevents signatures from being concentrated around a few spots in index space. Our query processing algorithm converts a query sequence into a multi-dimensional rectangle and searches the index for the signatures overlapped with the rectangle. The experiments with real biological data sets revealed that the proposed method is at least three times, twice, and several orders of magnitude faster than the suffix-tree-based method in exact match, wildcard match, and k- mismatch, respectively.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.7
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• pp.205-214
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• 2021

For smart manufacturing, most semiconductor sites utilize automated material handling systems(AMHS). As one of the AMHSs, the OHT control system(OCS) manages overhead hoist transports(OHT) that move along rails installed on the ceiling. This paper proposes a real-time scheduling system to efficiently allocate and control the OHTs in semiconductor logistics processes. The proposed system, as an independent subsystem within the OCS, is interconnected with the main subsystem of the OCS, so that it can be easily modified without the effect of other systems. To develop the system, we first identify the functional requirements of the semiconductor logistics process and classify several types of control scenarios of the OHTs. Next, based on SEMI(Semiconductor Equipment and Materials International) standard, we design sequence diagrams and interface messages between the subsystems. The developed system is interoperated with the OCS main subsystem and the database in real time and performs two major roles: 1) OHT dispatching and 2) pathfinding. Six integrated tests were carried out to verify the functions of the developed system. The system was normally operated on six basic scenarios and two exception scenarios and we proved that it is suitable for the mission planning of the OHTs.