• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.723-728
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• 2004

Recently, because of the extensive use of geographic information in the various fields, the requirement for the easy circulation and utilization of the various geographic information among the individuals, organizations, societies and countries is raised. In order to support the interoperability of the heterogeneous geographic information in the various fields, OGC(Open GIS Consortium) proposed the GML(Geography Markup Language) specification that defines the XML encoding rule about the heterogeneous geographic information. In addition, ISO/TC 211 adopted the GML specification to make it as the international standard. Therefore, in this paper, we first analyzed the GML 3.0 specification in detail that can support the interoperability of the heterogeneous geographic information. And then we suggested and applied the mapping rule that define the encoding method to improve the encoding process easily and efficiently. Finally, we designed and implemented the GML 3.0 encoding system using the mapping rule to encode the geographic information that was constructed in spatial databases into the GML 3.0 document. Especially, we used ZEUS as a spatial database system to test our encoding system in this paper.

• Korean Management Science Review
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• v.17 no.3
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• pp.19-30
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• 2000

Customization and personalization services are considered as a critical success factor to be a successful Internet store or web service provider. As a representative personalization technique, personalized recommendation techniques are studied and commercialized to suggest products or services to a customer of Internet storefronts based on demographics of the customer or based on an analysis of the past purchasing behavior of the customer. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customers data. however, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed knowledge base. In this paper, we proposed a marketing rule extraction technique for personalized recommendation on Internet storefronts using market basket analysis technique, a well-known data mining technique. Using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store. An experiment has been performed to evaluate the effectiveness of proposed approach comparing with preference scoring approach and random selection.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.57-62
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• 2010

This paper proposes two methods for the construction of job offer and job hunting information in order to supply an environment that can easily connects to job hunting information. First, the database expansion, category rules and ERD(Entity Relation Diagram) are designed for the construction of job hunting site with real example. Second, the prime number labeling rules are designed for the strong intimacy of label rules. Therefore, according to using the systematic and regular rules when we design and construct a database, the consistency and efficiency are improved in the database being constructed and being operated. And the convenience of application program development and operation are easily provided. In addition, the proposed code-expansion rule can be defined and be standardized in the domestic and foreign job offer and job hunting information provision agency.

• Structural Engineering and Mechanics
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• v.19 no.1
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• pp.107-121
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• 2005

The suboptimal control rule is introduced in structural control implementation as an alternative over the optimal control because the optimal control may require large amount of processing time when applied to complex structural control problems. It is well known that any time delay in structural control implementation will cause un-synchronized application of the control forces, which not only reduce the effectiveness of an active control system, but also cause instability of the control system. The effect of time delay on the displacement and acceleration responses of building structures is studied when the suboptimal control rule is adopted. Two examples are given to show the effectiveness of the suboptimal control rule. It is shown through the examples that the present method is easy in implementation and high in efficiency and it can significantly reduce the time delay in structural control implementation without significant loss of performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1582-1587
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• 2005

In coagulant control of water treatment plants, rule extraction, one of datamining categories, was performed for coagulant control of a water treatment plant. Clustering methods were applied to extract control rules from data. These control rules can be used for fully automation of water treatment plants instead of operator's knowledge for plant control. To perform fuzzy clustering, there are some coefficients to be determined and these kinds of studies have been performed over decades such as clustering indices. In this study, statistical indices were taken to calculate the number of clusters. Simultaneously, seed points were found out based on hierarchical clustering. These statistical approaches give information about features of clusters, so it can reduce computing cost and increase accuracy of clustering. The proposed algorithm can play an important role in datamining and knowledge discovery.

• Bulletin of the Society of Naval Architects of Korea
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• v.4 no.1
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• pp.59-65
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• 1967

Since the screw propellers were adopted as ship propulsion devices, the replacement of propeller shaft due to damage was mostly of fatigue failure due to the alternative stresses [1],[2]. To prevent such a failure, hence, it is suggested that careful attention should be paid to account of the alternative stresses on the design stage of the propeller shafts. In connection with this fact the Ship Classification Societies' Rules are regarded simply as guidance for preliminary determination of the shaft diameter. In this paper, limiting the topic to the small and medium-sized motor ships, an evaluation of the Rules formulae to a theoretical based on Soderberg's correlation [5] between the factor of safety and the resultant stresses obtained by application of the maximum shear theory is done. For this purpose eleven (11) ships built recently in Korea were taken as a species(refer to table 2. in text). In the end the following conclusions are made: (1) In general the Rules formulae give considerably larger size of the propeller shaft diameter than that derived from theoretical calculation, that is, about 7% more in AB and BV Rules, and about 20% more in LR and KR-NK Rules. (2) LR Rule gives the largest size of all, and AB Rule is mostly closed value to the theoretical. (3) The formular of the AB Rule is considered to be of the simplest in utilization and of the reasonable.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.438-447
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• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.81-86
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• 2012

In this paper, we proposed a new design methodology of a pattern classification rule based on the local linear discriminant analysis expanded from the generic linear discriminant analysis which is used in the local area divided from the whole input space. There are two ways such as k-Means clustering method and the differential evolutionary algorithm to partition the whole input space into the several local areas. K-Means clustering method is the one of the unsupervised clustering methods and the differential evolutionary algorithm is the one of the optimization algorithms. In addition, the experimental application covers a comparative analysis including several previously commonly encountered methods.

• The Journal of Information Systems
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• v.12 no.2
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• pp.1-20
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• 2003

This paper deals with the application of the genetic algorithm to the technical trading rule of the stock market. MACD(Moving Average Convergence & Divergence) and the Stochastic techniques are widely used technical trading rules in the financial markets. But, it is necessary to determine the parameters of these trading rules in order to use the trading rules. We use the genetic algorithm to obtain the appropriate values of the parameters. We use the daily KOSPI data of eight years during January 1995 and October 2002 as the experimental data. We divide the total experimental period into learning period and testing period. The genetic algorithm determines the values of parameters for the trading rules during the teaming period and we test the performance of the algorithm during the testing period with the determined parameters. Also, we compare the return of the genetic algorithm with the returns of buy-hold strategy and risk-free asset. From the experiment, we can see that the genetic algorithm outperforms the other strategies. Thus, we can conclude that genetic algorithm can be used successfully to the technical trading rule.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.235-240
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• 1996

The automated ECG diagnostic systems that are odd in hospitals have low performance of P-wave detection when faced with some diseases such as conduction block. So, the purpose of this study was the improvement of detection performance in conduction block which is low in P-wave detection. The first procedure was removal of baseline drift by subtracting the median filtered signal of 0.4 second length from the original signal. Then the algorithm detected R peak and T end point and cancelled the QRS-T complex to get'p prototypes'. Next step was magnification of P prototypes with dispersion and detection of'p candidates'in the magnified signal, and then extraction of contextual information concerned with P-waves. For the last procedure, the CIR was applied to P candidates to confirm P-waves. The rule base consisted of three rules that discriminate and confirm P-waves. This algorithm was evaluated using 500 patient's raw data P-wave detection perFormance was in- creased 6.8% compared with the QRS-T complex cancellation method without application of the rule base.