• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.822-832
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• 2001

We have implemented an inductive learning system that learns PROSPECTOR-rule-style classification rules from sets of examples. In our a approach, a genetic algorithm is used in which a population consists of rule-sets and rule-sets generate offspring through the exchange of rules relying on genetic operators such as crossover, mutation, and inversion operators. In this paper, we describe our learning environment centering on the syntactic structure and meaning of classification rules, the structure of a population, and the implementation of genetic operators. We also present a method to evaluate the performance of rules and a heuristic approach to generate rules, which are developed to implement mutation operators more efficiently. Moreover, a method to construct a classification system using multiple learned rule-sets to enhance the performance of a classification system is also explained. The performance of our learning system is compared with other learning algorithms, such as neural networks and decision tree algorithms, using various data sets.

• Journal of Preventive Medicine and Public Health
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• v.36 no.2
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• pp.147-152
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• 2003

Objectives : To develop a Diagnosis-Related Group (DRG) fraud candidate detection method, using data mining techniques, and to examine the efficiency of the developed method. Methods ; The Study included 79,790 DRGs and their related claims of 8 disease groups (Lens procedures, with or without, vitrectomy, tonsillectomy and/or adenoidectomy only, appendectomy, Cesarean section, vaginal delivery, anal and/or perianal procedures, inguinal and/or femoral hernia procedures, uterine and/or adnexa procedures for nonmalignancy), which were examined manually during a 32 months period. To construct an optimal prediction model, 38 variables were applied, and the correction rate and lift value of 3 models (decision tree, logistic regression, neural network) compared. The analyses were peformed separately by disease group. Results : The correction rates of the developed method, using data mining techniques, were 15.4 to 81.9%, according to disease groups, with an overall correction rate of 60.7%. The lift values were 1.9 to 7.3 according to disease groups, with an overall lift value of 4.1. Conclusions : The above findings suggested that the applying of data mining techniques is necessary to improve the efficiency of DRG fraud candidate detection.

• International Journal of Fluid Machinery and Systems
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• v.8 no.4
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• pp.264-273
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• 2015

This presentation describes an experimental approach for the detection of cavitation in hydraulic machines by use of ultrasonic signal analysis. Instead of using the high frequency pulses (typically 1MHz) only for transit time measurement different other signal characteristics are extracted from the individual signals and its correlation function with reference signals in order to gain knowledge of the water conditions. As the pulse repetition rate is high (typically 100Hz), statistical parameters can be extracted of the signals. The idea is to find patterns in the parameters by a classifier that can distinguish between the different water states. This classification scheme has been applied to different cavitation sections: a sphere in a water flow in circular tube at the HSLU in Lucerne, a NACA profile in a cavitation tunnel and two Francis model test turbines all at LMH in Lausanne. From the signal raw data several statistical parameters in the time and frequency domain as well as from the correlation function with reference signals have been determined. As classifiers two methods were used: neural feed forward networks and decision trees. For both classification methods realizations with lowest complexity as possible are of special interest. It is shown that two to three signal characteristics, two from the signal itself and one from the correlation function are in many cases sufficient for the detection capability. The final goal is to combine these results with operating point, vibration, acoustic emission and dynamic pressure information such that a distinction between dangerous and not dangerous cavitation is possible.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.571-573
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• 2018

Wireless sensor networks have unbalanced energy consumption due to the convergence structure in which data is concentrated to sink nodes. To solve this problem, in the previous research, the relay node was placed between the source node and the sink node to merge the data before being concentrated to the sink node. However, selecting a relay node that does not consider the link quality causes packet loss according to the link quality of the reconfigured routing path. Therefore, in this paper, we propose a link cost calculation method for data reliability in routing path reconfiguration for relay node selection. We propose a link cost estimation formula considering the number of hops and RSSI as the routing metric value and select the RSSI threshold value through the packet transmission experiment between the sensor modules.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.383-390
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• 2015

It is appropriate to use the NETCONF to monitor and manage today's complex networks that are composed of variety links and heterogeneous equipment. Since the first standard of the NETCONF are launched, there have been several revisions, but disadvantages of each layer capabilities is still present and the most typical disadvantage is XML document processing efficiency of the Content layer. In this paper, we perform data modeling by constructing a sub-tree based on the dependencies between Content layer data, and suggest method of extract efficiently data from XML by applying the extended VTD-XML technique for the XPath query. We performs experiment to compare NETCONF in proposed method to NETCONF in previous studies and NETCONF standard. we validate superiority of improved NETCONF in the paper. As experimental results, we verify that improved NETCONF is better than the other two NETCONF each 4% and 10% in terms of query processing rate, and faster than each 3.9 seconds and 10.4 seconds in terms of query processing speed.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.11-18
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• 2005

In this paper, we propose a new technology mapping algorithm for CPLD consider area under time constraint. This algorithm detect feedbacks from boolean networks, then variables that have feedback are replaced to temporary variables. Creating the temporary variables transform sequential circuit to combinational circuit. The transformed circuits are represented to DAG. After traversing all nodes in DAG, the nodes that have output edges more than two are replicated and reconstructed to fanout free tree. Using time constraints and delay time of device, the number of graph partitionable multi-level is decided. Several nodes in partitioned clusters are merged by collapsing, and are fitted to the number of OR-terms in a given CLB by bin packing. Proposed algorithm have been applied to MCNC logic synthesis benchmark circuits, and have reduced the number of CLBs by $62.2\%$ than those of DDMAP. And reduced the number of CLBs by $17.6\%$ than those of TEMPLA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.354-361
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• 2011

Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.259-269
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• 2020

With the proposal-agreement procedure, RSTP can reduce the network recovery time to 400 ms or less in the case of 40 bridges. While the legacy RSTP reverts the previous agreement at the bridge with the alternate port role in the ring during the fault recovery, a new position based fast fault recovery procedure is proposed in this paper to guarantee a single proposal-agreement transaction which can provide more faster recovery. By knowing the relative position of the faulty link or bridge in hops, the bridge on the middle of the ring can complete the recovery procedure without revert. The performance of proposed procedure is numerically calculated and verified by simulation and the result shows that the recovery time can be reduced up to 100 ms, which is 1/4 times of the legacy RSTP.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.155-159
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• 2008

In this thesis, in order to develop a new classification model of Sasang Constitutional medical types, which is helpful for improving the accuracy of diagnosis of medical types. various data-mining classification models such as discriminant analysis. decision trees analysis, neural networks analysis, logistics regression analysis, clustering analysis which are main classification methods were applied to the questionnaires of medical type classification. In this manner, a model which scientifically classifies constitutional medical types in the field of Sasang Constitutional Medicine, one of a traditional Korean medicine, has been developed. Also, the above-mentioned analysis models were systematically compared and analyzed. In this study, a classification of Sasang constitutional medical types was developed based on the discriminate analysis model and decision trees analysis model of which accuracy is relatively high, of which analysis procedure is easy to understand and to explain and which are easy to implement. Also, a diagnosis system of Sasang constitution was implemented applying the two analysis models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3B
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• pp.349-359
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• 2004

To provide multicasting service, several multicast protocols for mobile hosts have been proposed. But they include glitches such as a non-optimal delivery route, data loss when hosts move another network, therefore they have some insecure problems about multicast data transmission. In this paper, we consider these problems and propose a new reliable and efficient multicast routing protocol for Mobile If networks. The proposed protocol provides reliable multicast transmission by compensating data loss from the previous agent when a mobile host moves another network. Also it provides additional function that is directly to connect a multicast tree according to the status of agents. It provides more efficient and optimal multicast path. The performance of the proposed protocol is proved by simulation of various conditions.