• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.5
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• pp.873-883
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• 2013

Security vulnerability quantification is the method that identify potential vulnerabilities by scoring vulnerabilities themselves and their countermeasures. However, due to the structural feature of smart grid system, it is difficult to apply existing security threat evaluation schemes. In this paper, we propose a network model to evaluate smartgrid security threat for AMI and derive attack scenarios. Additionally, we show that the result of security threat evaluation for proposed network model and attack scenario by applying MTTC scheme.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.235-245
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• 2012

Logistic discrimination is an useful statistical technique for quantitative analysis of financial service industry. Especially it is not only easy to be implemented, but also has good classification rate. Generalized additive model is useful for credit scoring since it has the same advantages of logistic discrimination as well as accounting ability for the nonlinear effects of the explanatory variables. It may, however, need too many additive terms in the model when the number of explanatory variables is very large and there may exist dependencies among the variables. Mixtures of factor analyzers can be used for dimension reduction of high-dimensional feature. This study proposes to use the low-dimensional factor scores of mixtures of factor analyzers as the new features in the generalized additive model. Its application is demonstrated in the classification of some real credit scoring data. The comparison of correct classification rates of competing techniques shows the superiority of the generalized additive model using factor scores.

• The KIPS Transactions:PartD
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• v.19D no.4
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• pp.263-270
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• 2012

With the current development of high speed Internet and massive database technology, the amount of web documents increases rapidly, and thus, classifying those documents automatically is getting important. In this study, we propose an effective method to extract document features based on Hangeul morpheme and keyword analyses, and to classify non-structured documents automatically by predicting subjects of those documents. To extract document features, first, we select terms using a morpheme analyzer, form the keyword set based on term frequency and subject-discriminating power, and perform the scoring for each keyword using the discriminating power. Then, we generate the classification model by utilizing the commercial software that implements the decision tree, neural network, and SVM(support vector machine). Experimental results show that the proposed feature extraction method has achieved considerable performance, i.e., average precision 0.90 and recall 0.84 in case of the decision tree, in classifying the web documents by subjects.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.410-419
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• 2004

In this paper. we propose a method of confidence measure fusion under Bayesian framework for speech recognition. Centralized and distributed schemes are considered for confidence measure fusion. Centralized fusion is feature level fusion which combines the values of individual confidence scores and makes a final decision. In contrast. distributed fusion is decision level fusion which combines the individual decision makings made by each individual confidence measuring method. Optimal Bayesian fusion rules for centralized and distributed cases are presented. In isolated word Out-of-Vocabulary (OOV) rejection experiments. centralized Bayesian fusion shows over 13% relative equal error rate (EER) reduction compared with the individual confidence measure methods. In contrast. the distributed Bayesian fusion shows no significant performance increase.

• ETRI Journal
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• v.42 no.5
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• pp.761-772
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• 2020

This paper presents an automatic proficiency assessment method for a non-native Korean read utterance using bidirectional long short-term memory (BLSTM)-based acoustic models (AMs) and speech data augmentation techniques. Specifically, the proposed method considers two scenarios, with and without prompted text. The proposed method with the prompted text performs (a) a speech feature extraction step, (b) a forced-alignment step using a native AM and non-native AM, and (c) a linear regression-based proficiency scoring step for the five proficiency scores. Meanwhile, the proposed method without the prompted text additionally performs Korean speech recognition and a subword un-segmentation for the missing text. The experimental results indicate that the proposed method with prompted text improves the performance for all scores when compared to a method employing conventional AMs. In addition, the proposed method without the prompted text has a fluency score performance comparable to that of the method with prompted text.

• Korean Journal of Health Education and Promotion
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• v.22 no.3
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• pp.83-95
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• 2005

Objectives: The aim of this study was to assess the quality of the information and characteristics associated with information packaging, and develop suggestions for how this web site might be improved. Methods: The 50 sites were selected for evaluation. Inclusion criteria for evaluation were the purpose and the popularity of the sites. Two kinds of evaluation tool were employed for the analysis: one that evaluate the quality of information and the design of the web sites, and another that evaluate the covered contents. A scoring system allowed the sites point on yes/no basis on the evaluation items. The association between quality of the web sites on sexuality education and their site characteristics were assessed using ANOVA. Conclusions: Major conclusions were as follows. First, the scope and currency of the selected web sites were found to be appropriate. Second, the authority of the information was found to be the most serious problem of the selected sites. Third, the category of sexual behavior found to be the most frequently mentioned and sexual health was the second. The least mentioned category was personal skills. Finally, sites operated by private organization were found to have more accurate information and better design feature than those operated by public organization and/or individual.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.185-198
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• 2021

With the development of Internet technology, because traditional recommendation algorithms cannot learn the in-depth characteristics of users or items, this paper proposed a recommendation algorithm based on the AMITI(attention mechanism and improved TF-IDF) to solve this problem. By introducing the two-layer attention mechanism into the CNN, the feature extraction ability of the CNN is improved, and different preference weights are assigned to item features, recommendations that are more in line with user preferences are achieved. When recommending items to target users, the scoring data and item type data are combined with TF-IDF to complete the grouping of the recommendation results. In this paper, the experimental results on the MovieLens-1M data set show that the AMITI algorithm improves the accuracy of recommendation to a certain extent and enhances the orderliness and selectivity of presentation methods.

• Research in Mathematical Education
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• v.25 no.4
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• pp.285-309
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• 2022

A large body of previous studies investigated mathematical tasks by analyzing the design process prior to lessons or textbooks. While researchers have revealed the significant roles of mathematical tasks within written curricular, there has been a call for studies about how mathematical tasks are implemented or what is experienced and learned by students as enacted curriculum. This article proposes a mathematical task analytic framework based on a holistic definition of tasks encompassing both written tasks and the process of task enactment. We synthesized the features of the mathematical tasks and developed a task analytic framework with multiple dimensions: breadth, depth, bridging, openness, and interaction. We also applied the scoring rubric to analyze three multiplication tasks to illustrate the framework by its five dimensions. We illustrate how a series of tasks are analyzed through the framework when students are engaged in multiplicative thinking. The framework can provide important information about the qualities of planned tasks for mathematics instruction (proactive) and the qualities of implemented tasks during instruction (reactive). This framework will be beneficial for curriculum designers to design rich tasks with more careful consideration of how each feature of the tasks would be attained and for teachers to transform mathematical tasks with the provision of meaningful learning activities into implementation.

• The Korean Society of Law and Medicine
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• v.15 no.1
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• pp.185-209
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• 2014

While the local health insurance and the employment-based insurance were integrated in July 2000, the insured is divided into employment-based insured and the local insured and the relevant premium has been applied to both groups. The health insurance premium having the feature of social solidarity has to be determined depending on income, that is, the ability to pay in accordance with the principles of social insurance. While employment-based insurance premium has been determined depending on the earned income, the local insurance premium for the local insured has been determined by scoring gross income(evaluated income), property and possession of automobiles. A variety of improvement approaches has been implemented including introduction of the employment-based insurance premium ceiling system (2002) and the change of property scoring system for the local insured (2006). However, the health insurance system which was merged in 2000 has been implemented up to now without significant change even though there were lots of socio-demographic change including increase of income level and the population structure such as low birth and aging. In other words, it is required to implement the premium rating system securing the income-based equity. Nevertheless, it was inevitable to apply the diverse rating standards in the early stage because it was very difficult to verify the income of the self-employed. Although the income verification rate was significantly increased from 23% in 1989 to 44% in 2010, the irrational standards including property, automobiles, living standard and activity rate have been still applied to the local insured because it is difficult to secure the validity of insurance premium rating system and it severely lacks of security. This paper investigated whether the current insurance premium rating system for the local insured imposing the premium on the basis of 'gender' and 'age' complies with the basic human rights secured by the current Constitution of the Republic of Korea with respect to the practical and theoretic irrationality of insurance premium rating system and standards for he local insured. In accordance with the analysis results, this paper proposed the approach to improve the system.