• Journal of Digital Convergence
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• v.15 no.4
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• pp.191-198
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• 2017

It is needed to support intelligent customized health information service for user convenience in PHR based Personal Health Care Service Platform. In this paper, we specify an ontology-based health data model for Personal Health Care Service Platform. We also design a knowledge search algorithm that can be used to figure out similar health record by applying machine learning and data mining techniques. Axis-based mining algorithm, which we proposed, can be performed based on axis-attributes in order to improve relevance of knowledge exploration and to provide efficient search time by reducing the size of candidate item set. And K-Nearest Neighbor algorithm is used to perform to do grouping users byaccording to the similarity of the user profile. These algorithms improves the efficiency of customized information exploration according to the user 's disease and health condition. It can be useful to apply the proposed algorithm to a process of inference in the Personal Health Care Service Platform and makes it possible to recommend customized health information to the user. It is useful for people to manage smart health care in aging society.

• Journal of Korean Clinical Health Science
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• v.10 no.1
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• pp.1553-1558
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• 2022

Purpose: The aim of this study was to determine the association between stigmatism and amblyopia. Methods: It was a hospital based, cross-sectional retrospective study conducted in Nepal Eye Hospital. Medical record of amblyopic children aged 13 years or younger from were reviewed. Children with amblyopic eyes due to simple astigmatism were included. Relation between depth of amblyopia with magnitude and types of astigmatism, orientation of axis was determined. Out of 139 amblyopic eyes of 82 children, 93 were simple myopic astigmatism and remaining 42 were simple hyperopic astigmatism. Results: Mean age of patients was 7.38±2.61 years. Visual acuity improved by at least one line in Snellen chart in 4/5th of eyes after astigmatic correction. Moderate amblyopia was found to be present in 45% eyes while severe amblyopia in 16% of eyes. With the rule astigmatism was found to be present in 88% eyes. Mean astigmatism was 2.47±0.98D and majority of eyes (67.7%) had high astigmatism. Depth of amblyopia was not associated with magnitude of astigmatism (p > 0.05) but number of lines improved with astigmatic correction was correlated with the magnitude of astigmatism (p < 0.001). Risk of amblyopia is more in high myopic astigmatism. Conclusion: Presenting age of amblyopic children was late in Nepal. Depth of amblyopia was not associated with magnitude of astigmatism.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.459-466
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• 2011

In this paper, we proposed a data mining framework for the management of alerts in order to improve the performance of the intrusion detection systems. The proposed alert data mining framework performs alert correlation analysis by using mining tasks such as axis-based association rule, axis-based frequent episodes and order-based clustering. It also provides the capability of classify false alarms in order to reduce false alarms. We also analyzed the characteristics of the proposed system through the implementation and evaluation of the proposed system. The proposed alert data mining framework performs not only the alert correlation analysis but also the false alarm classification. The alert data mining framework can find out the unknown patterns of the alerts. It also can be applied to predict attacks in progress and to understand logical steps and strategies behind series of attacks using sequences of clusters and to classify false alerts from intrusion detection system. The final rules that were generated by alert data mining framework can be used to the real time response of the intrusion detection system.