• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.241-251
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• 2006

Data mining is the method to find useful information for large amounts of data in database It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. We analyze industrial waste database using data mining technique. We use k-means algorithm for clustering and C5.0 algorithm for decision tree and Apriori algorithm for association rule. We can use these analysis outputs for environmental preservation and environmental improvement.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1067-1076
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• 2003

Database sharing system (DSS) refers to a system for high performance transaction processing. In DSS, the processing nodes are locally coupled via a high speed network and share a common database at the disk level. Each node has a local memory and a separate copy of operating system. To reduce the number of disk accesses, the node caches database pages in its local memory buffer. In this paper, we propose a dynamic transaction routing algorithm to balance the load of each node in the DSS. The proposed algorithm is novel in the sense that it can support node-specific locality of reference by utilizing the primary copy authority assigned to each node; hence, it can achieve better cache hit ratios and thus fewer disk I/Os. Furthermore, the proposed algorithm avoids a specific node being overloaded by considering the current workload of each node. To evaluate the performance of the proposed algorithm, we develop a simulation model of the DSS, and then analyze the simulation results. The results show that the proposed algorithm outperforms the existing algorithms in the transaction processing rate. Especially the proposed algorithm shows better performance when the number of concurrently executed transactions is high and the data page access patterns of the transactions are not equally distributed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2926-2945
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• 2017

In geo-location database oriented spectrum sharing system, the entire geographic area is divided into meshes to classify, store and delivery the cognitive information. In this paper, we propose a flexible polygon mesh division scheme to reduce the number of meshes. Hence the cognitive information can be reduced correspondingly. Besides, polygon mesh can approximate the real environment and reduce the error of cognitive information because the edges of polygon are selected along the boundaries of the networks. We have designed the polygon approximation algorithm and have analyzed the relation between the error and the number of polygon's edges. Finally, the simulation results are provided to verify the algorithm and analysis. The polygon mesh division scheme in this paper provides an efficient approach for cognitive information organization in database oriented spectrum sharing system.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.51-64
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• 1988

A new approach to the logical design of 4NF database shceme, which can be easily automated, is proposed. The main features of the approach are : introduction of a single attribute right hand side, extension of the concept of independent relations, semantic analysis, and adaoption of dependency matrix. The underlying viewpoints of functional relationships of the approach are different from Fagin's in that we distinguish functional and multivalued dependency in terms of cardinality. An algorithm for automatic generation of fourth normal form is presented and implemented.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.569-572
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• 1998

In this paper, we devised pulse rate diagnosis for provide basic index of cold-hot diagnosis. The system consist of database part and pulse rate detection part for detection pulse wave, respiration and ECG. The database is constructed windwos95 platform using DAO(data access object). Search algorithm used ISAM algorithm. The database consist of one's information and medical report for a subject and detected pulse wave.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.932-938
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• 2013

Recently, the Fingerprint, which is one of the methods of indoor localization using WLAN, has been many studied owing to robustness about ranging error by the diffraction and refraction of radio waves. However, in the signal gathering process and comparison operation for the measured signals with the database, this method requires time consumption and computational complexity. In order to compensate for these problems, this paper presents, based on proposed modified database, WLAN indoor localization algorithm using selective operation of collected signal in real time. The proposed algorithm reduces the configuration time and the size of the data in the database through linear interpolation and thresholding according to the signal strength, the localization accuracy, while reducing the computational complexity, is maintained through selective operation of the signals which are measured in real time. The experimental results show that the accuracy of localization is improved to 17.8% and the computational complexity reduced to 46% compared to conventional Fingerprint in the corridor by using proposed algorithm.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.1
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• pp.9-16
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• 2002

Join operation exert a great effect on the performance of system in temporal database as in the relational database. Especially, as for the temporal join, the optimization of interval partition decides the performance of query processing. In this paper, to improve the efficiency of parallel join query in temporal database. I proposed Minimum Interval Partition(MIP) scheme that time interval partitioning. The validity of this MIP algorithm that decides minimum breakpoint of the partition is proved by example scenario and I confirmed improved efficiency as compared with existing partition algorithm.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.71-86
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• 1999

The performance of relational database is measured by the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to vertically partition relations into fragments and to allow attribute replication to reduce the number of disk accesses. To reduce the computational time, heuristic search method using genetic algorithm is used. Genetic algorithm used employs a rank-based-sharing fitness function and elitism. Desirable parameters of genetic algorithm are obtained through experiments and used to find the solutions. Solutions of attribute replication and attribute non-replication problems are compared. Optimal solutions obtained by branch and bound method and by heuristic solutions(genetic algorithm) are also discussed. The solution method proposed is able to solve large-sized problems within acceptable time limit and shows solutions near the optimal value.

• Nuclear Engineering and Technology
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• v.36 no.3
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• pp.219-228
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• 2004

[1] and [2] present an approach to diagnosing possible defects in the mechanical systems of a nuclear power plant. In this paper, by using a fault library as a database and training data, we develop a diagnostic algorithm 1) to decide whether an Air Operated Valve system is sound or not and 2) to identify the defect from which an Air-Operated Valve system suffers, if any. This algorithm is composed of three stages: a neural net stage, a non-neural net stage, and an integration stage. The neural net stage is a simple perceptron, a pattern-recognition module, using a neural net. The non-neural net stage is a simple pattern-matching algorithm, which translates the degree of matching into a corresponding number. The integration stage collects each output and makes a decision. We present a simulation result and confirm that the developed algorithm works accurately, if the input matches one in the database.