• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.90-92
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• 2006

기존의 Support Vector Data Description (SVDD) 방법은 학습 데이터의 개수가 증가함에 따라 학습 시간이 지수 함수적으로 증가하므로, 대량의 데이터를 학습하는 데에는 한계가 있었다. 본 논문에서는 학습 속도를 빠르게 하기 위해 K-means clustering 알고리즘을 이용하는 SVDD 알고리즘을 제안하고자 한다. 제안된 알고리즘은 기존의 decomposition 방법과 유사하게 K-means clustering 알고리즘을 이용하여 학습 데이터 영역을 sub-grouping한 후 각각의 sub-group들을 개별적으로 학습함으로써 계산량 감소 효과를 얻는다. 이러한 sub-grouping 과정은 hypersphere를 이용하여 학습 데이터를 둘러싸는 SVDD의 학습 특성을 훼손시키지 않으면서 중심점으로 모여진 작은 영역의 학습 데이터를 학습하도록 함으로써, 기존의 SVDD와 비교하여 학습 정확도의 차이 없이 빠른 학습을 가능하게 한다. 다양한 데이터들을 이용한 모의실험을 통하여 그 효과를 검증하도록 한다.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.175-182
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• 2007

The support vector machine has been successful in many applications because of its flexibility and high accuracy. However, when a training data set is large or imbalanced, the support vector machine may suffer from significant computational problem or loss of accuracy in predicting minority classes. We propose a modified version of the support vector machine using the K-means clustering that exploits the information in class labels during the clustering process. For large data sets, our method can save the computation time by reducing the number of data points without significant loss of accuracy. Moreover, our method can deal with imbalanced data sets effectively by alleviating the influence of dominant class.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.291-298
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• 2019

This study aimed to examine disabled women to determine whether differences existed in parenting stress, resilience, social support, and parenting competency based on the disability type using an latent means analysis. The research data was sampled from 167 mentally disabled women and 132 physically disabled women. Parenting stress and social support had higher latent means in the mentally disabled women. Parenting competence and resilience had higher latent means in the physically disabled women. The results of this study suggested that differentiated, practical intervention approaches should be implemented for each disability type.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.81-102
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• 2017

Financing, manpower support and tax are the most popular tools for policy for small and medium enterprises (SMEs). This paper, however, will introduce information analysis support for SMEs and will prove that can be a good tool. The information analysis support means the support of technology and market information for the technology development or commercialization of SMEs. Therefore, the support is a customized one. In the theory domain, we adopt and prove two theoretical grounds as an SMEs policy such as market and system failure. In the policy tool domain, we suggest four requirements to be an SMEs policy and prove the tool to satisfy these requirements. All the data and proofs are from a government research institute called K.

• Safety and Health at Work
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• v.7 no.3
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• pp.185-193
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• 2016

Background: Management and workers in small and medium-sized enterprises (SMEs) often find it hard to comprehend the requirements related to controlling risks due to exposure to substances. An intervention study was set up in order to support 45 SMEs in improving the management of the risks of occupational exposure to chemicals, and in using the control banding tool and exposure model Stoffenmanager in this process. Methods: A 2-year intervention study was carried out, in which a mix of individual and collective training and support was offered, and baseline and effect measurements were carried out by means of structured interviews, in order to measure progress made. A seven-phase implementation evolutionary ladder was used for this purpose. Success and failure factors were identified by means of company visits and structured interviews. Results: Most companies clearly moved upwards on the implementation evolutionary ladder; 76% of the companies by at least one phase, and 62% by at least two phases. Success and failure factors were described. Conclusion: Active training and coaching helped the participating companies to improve their chemical risk management, and to avoid making mistakes when using and applying Stoffenmanager. The use of validated tools embedded in a community platform appears to support companies to organize and structure their chemical risk management in a business-wise manner, but much depends upon motivated occupational health and safety (OHS) professionals, management support, and willingness to invest time and means.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.19-26
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• 2012

The rapid increase of information imposes new demands of content management. The purpose of automatic audio segmentation and classification is to meet the rising need for efficient content management. With this reason, this paper proposes a high-accuracy algorithm that segments audio signals and classifies them into different classes such as speech, music, silence, and environment sounds. The proposed algorithm utilizes support vector machine (SVM) to detect audio-cuts, which are boundaries between different kinds of sounds using the parameter sequence. We then extract feature vectors that are composed of statistical data and they are used as an input of fuzzy c-means (FCM) classifier to partition audio-segments into different classes. To evaluate segmentation and classification performance of the proposed SVM-FCM based algorithm, we consider precision and recall rates for segmentation and classification accuracy for classification. Furthermore, we compare the proposed algorithm with other methods including binary and FCM classifiers in terms of segmentation performance. Experimental results show that the proposed algorithm outperforms other methods in both precision and recall rates.

• Journal of Korean Society of Rural Planning
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• v.22 no.1
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• pp.113-120
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• 2016

The purpose of this paper is to decide priorities of policy-objectives and support measures related to the $6^{th}$ industrialization of agriculture, and prepare policy-objectives and alternatives to contribute to maintaining and promoting the community through creation of more jobs and added value. We used the Analytic Hierarchy Process (AHP) to reflect the experts' opinions about objectives, means and priorities of the $6^{th}$ industrialization of agriculture. The important objectives of the 6th industrialization of agriculture were to create jobs, to increase added values, and to maintain and activate the community. The results showed that the most important objectives for the $6^{th}$ industrialization of agriculture were maintaining and activating the community, expanding added values and creating employment in order. Policy means to achieve these objectives were financial support, human resource training & consulting, research & development, and marketing. The decision-makers determined marketing as the most important among the policy means to achieve the objectives of the $6^{th}$ industrialization.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.73-76
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• 2006

Pilots and navigators have through history used everything available to support them in the execution of their task. From the simple sounding means (for instance a stick or a line with a heavy object tied to it) to the advanced electronic support systems that are available today. This means that apart from the more traditional side of his set of tasks the influence of modern technology is felt. In general it concerns such diverse and complex subjects that it requires the pilot to remain up to date with regard to the most modern techniques. In a sense this also concurs with the change form a provider of (local) knowledge to that of a manager of a high risk operation. More information flows can reach the pilot on the place where he executes his profession. With marginal scope the pilot has to translate such information to the situation in which he finds himself in order to give a balanced advice. Knowledge of the surroundings, variable circumstances in his specific area but also language and culture play a crucial role. This paper touches on the history of pilot support systems and examines the developments of pilot support systems in the present day operating environment and addresses the implications. These range from the historic basic needs for pilot information to the present and future possibilities, supporting the pilot to make the most precise assessment at each operational stage to continually execute a safe journey in and out of port.

• Knowledge Management Research
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• v.15 no.1
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• pp.21-43
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• 2014

This paper investigate relationship between job burnout, social support and knowledge creation, sharing. also, social support are moderate on the relationship between job burnout and knowledge creation, sharing. We build up main effect and moderating effect hypothesis. To test hypothesis, survey method are performed. The results are as follows. first, emotional exhaustion and low personal accomplishment have negative effects on knowledge creation, but haven't effect on knowledge sharing. second, social support significant positively impact on knowledge creation and sharing. third, both of supervisor' support and coworker's support partially moderate the relationship between job burnout and knowledge creation, sharing. especially, emotional exhaustion reduce supervisor' support to knowledge creation, sharing and low personal accomplishment reduce co-worker' support to knowledge sharing, which means although job burnout preceded, if employees perceived high level of social support that have buffering effects on the relationships.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.925-936
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• 2008

An association rule mining finds the relation among each items in massive volume database. In generating association rules, the researcher specifies the measurements randomly such as support, confidence and lift, and produces the rules. The rule is not produced if it is not suitable to the one any condition which is given value. For example, in case of a little small one than the value which a confidence value is specified but a support and lift's value is very high, this rule is meaningful rule. But association rule mining can not produce the meaningful rules in this case because it is not suitable to a given condition. Consequently, we creat insignificant error which is not selected to the meaningful rules. In this paper, we suggest clustering technique to association rule measures for finding effective association rules using measure of association.