• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.369-378
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• 2004

In partially free word order languages like Korean and Japanese, the rule-based method is effective for text chunking, and shows the performance as high as machine learning methods even with a few rules due to the well-developed overt Postpositions and endings. However, it has no ability to handle the exceptions of the rules. Exception handling is an important work in natural language processing, and the exceptions can be efficiently processed in memory-based teaming. In this paper, we propose a hybrid of rule-based method and memory-based learning for Korean text chunking. The proposed method is primarily based on the rules, and then the chunks estimated by the rules are verified by memory-based classifier. An evaluation of the proposed method on Korean STEP 2000 corpus yields the improvement in F-score over the rules or various machine teaming methods alone. The final F-score is 94.19, while those of the rules and SVMs, the best machine learning method for this task, are just 91.87 and 92.54 respectively.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.109-119
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• 2004

In COSMOS, an area for signal coordination is divided into subareas composed of several signalized intersections that share a common cycle time. Each subarea contains only one critical intersection having heavy traffic load. Subarea is a basic unit of control. The performance of COSMOS is highly dependent on the linkage rule between adjacent subareas. The purpose of this study is to provide an appropriate subarea linkage rule in COSMOS. This study developed a control strategy for Critical Intersection and Sub Area linkage. Critical Intersections calculate the Offset Pattern both East-West Axis and North-South Axis, and the coordination direction either East-West Axis or North-South Axis. Subarea can be combined with other one in all directions. The performance of the suggested linkage rule was evaluated on the real network in Gangnam-Gu. The result was that travel time was reduced by the suggested linkage rule.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.611-618
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• 2015

By Wikipedia, big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Data mining is the computational process of discovering patterns in huge data sets involving methods at the intersection of association rule, decision tree, clustering, artificial intelligence, machine learning. Association rule is a well researched method for discovering interesting relationships between itemsets in huge databases and has been applied in various fields. There are positive, negative, and inverse association rules according to the direction of association. If you want to set the evaluation criteria of association rule, it may be desirable to consider three types of association rules at the same time. To this end, we proposed a balanced comparative confidence considering sensitivity, specificity, false positive, and false negative, checked the conditions for association threshold by Piatetsky-Shapiro, and compared it with comparative confidence and inversely comparative confidence through a few experiments.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.49-56
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• 2017

Among the techniques for analyzing big data, the association rule mining is a technique for searching for relationship between some items using various relevance evaluation criteria. This associative rule scheme is based on the direction of rule creation, and there are positive, negative, and inverse association rules. The purpose of this paper is to investigate the applicability of various types of relatively causal strength measures to the types of association rules from the point of view of interestingness measure. We also clarify the relationship between various types of confidence measures. As a result, if the rate of occurrence of the posterior item is more than 0.5, the first measure ($RCS_{IJ1}$) proposed by Good (1961) is more preferable to the first measure ($RCS_{LR1}$) proposed by Lewis (1986) because the variation of the value is larger than that of $RCS_{LR1}$, and if the ratio is less than 0.5, $RCS_{LR1}$ is more preferable to $RCS_{IJ1}$.

• Journal of the Korean School Mathematics Society
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• v.26 no.1
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• pp.21-47
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• 2023

This study examines the activity system of teaching and learning about informal statistical inference using sampling simulation, based on cultural-historical activity theory. The research explores what contradictions arise in the activity system and how the system changes as a result of these contradictions. The participants were 20 elementary school students in the 5th to 6th grades who received classes on informal statistical inference using sampling simulations. Thematic analysis was used to analyze the data. The findings show that a contradiction emerged between the rule and the object, as well as between the mediating artifact and the object. It was confirmed that visualization of empirical sampling distribution was introduced as a new artifact while resolving these contradictions. In addition, contradictions arose between the subject and the rule and between the rule and the mediating artifact. It was confirmed that an algorithm to calculate the mean of the sample means was introduced as a new rule while resolving these contradictions.

• Special Issue of the Society of Naval Architects of Korea
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• 2015.09a
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• pp.69-73
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• 2015

An evaluation of the accidental limit state (ALS) for design of a semi-submersible drilling rig is one of the essential design requirements as well as ultimate limit state (ULS) and fatigue limit state (FLS). This paper describes the ALS evaluation on the explosion accident at shale shaker room of semi-submersible drilling rig. There are three steps for the ALS evaluation such as structural analysis at concept design, risk based safety design and structural analysis at detailed design. For the ALS evaluation at concept design, conceptual explosion overpressure from the Rule guided by the classification society was used in the structural analysis that was carried out using LS-DYNA. To set up the design accidental load (DAL), explosion analysis was carried out using FLACS taking safety barriers into consideration. Then, the structural analysis was carried out applying DAL for the ALS evaluation at detailed design. Through the ALS evaluation on the explosion at shale shaker room, the importance of the risk based safety design was described.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.189-195
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• 2022

The Korean government has made it a major national task to contribute to the revitalization of the creative economy, such as creating new industries and jobs, by encouraging the private opening and utilization of public data. The Korean government is promoting public data quality improvement through activities such as conducting public data quality management level evaluation for high-quality public data retention. However, there is a difference in diagnosis results depending on the understanding and data expertise of users of the public data quality diagnosis tool. Therefore, it is difficult to ensure the accuracy of the diagnosis results. This paper proposes a public data quality management level evaluation domain rule mapping model applicable to validation diagnosis among the data quality diagnosis standards. This increases the stability and accuracy of public data quality diagnosis.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.461-466
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• 2002

In many applications of computer aided geometric design and computer graphics, B-spline is one of the most popular representation for curves and surfaces, and the evaluation of B-spline curves and surfaces is the most frequently used operation. For the evaluation and others, the power form representation of the curves and surfaces is preferred because it is possible to speed-up the operation using Horner's rule. In this paper, we present a new algorithm for the above-mentioned conversion focusing on a dynamic case. Experiment shows that the proposed algorithm significantly outperforms the conventional approach when one or more control points of a B-spline curve and surface are dynamically moving.

• KIEE International Transactions on Power Engineering
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• v.3A no.1
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• pp.7-16
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• 2003

A new method to evaluate the protection capability of distribution systems is reported in this paper. This work describes the fuzzy evaluation attributes and aggregation method of evaluation results based on a hierarchical model and the modified combination rule. An evaluation grade index called "protectability" is proposed and is expected to be a very uscful tool in defining an optimal protection and realizing the adaptive protection.rotection.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.215-223
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• 2018

Recently, as interest of wearable devices has increased, commercially available smart wristbands and applications have been used as a tool for personal healthy management. However most previous studies have focused on evaluating the accuracy and reliability of the technical problems of wearable devices, especially step counts, walking distance, and energy consumption measured from the smart wristbands. In this study, we propose a physical activity evaluation model using classification rules, induced from the associative classification mining approach. These rules associated with five physical activities were generated by considering activities and walking times in target heart rate zones such as 'Out-of Zone', 'Fat Burn Zone', 'Cardio Zone', and 'Peak Zone'. In the experiment, we evaluated the prediction power of classification rules and verified its effectiveness by comparing classification accuracies between the proposed model and support vector machine.