• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.199-209
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• 2022

Typical anomaly detection algorithms are trained by using prior data. Thus the batch learning based algorithms cause inevitable performance degradation when characteristics of newly incoming normal data change over time. We propose an online anomaly detection algorithm which can consider the gradual characteristic changes of incoming normal data. The proposed algorithm based on one-class classification model includes both offline and online learning procedures. In offline learning procedure, the algorithm learns the prior data to be close to centroid of the latent space and then updates the centroid of the latent space incrementally by new incoming data. In the online learning, the algorithm continues learning by using the updated centroid. Through experiments using public underwater acoustic data, the proposed online anomaly detection algorithm takes only approximately 2 % additional learning time for the incremental centroid update and learning. Nevertheless, the proposed algorithm shows 19.10 % improvement in Area Under the receiver operating characteristic Curve (AUC) performance compared to the offline learning model when new incoming normal data comes.

• The Journal of Information Technology
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• v.4 no.1
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• pp.1-7
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• 2001

The well-known tradeoff of Java's portability is the inefficiency of its basic execution model, which relies on the interpretation of an virtual machine. Many solutions have been proposed to overcome this problem, such as just-in-time(JIT) and offline bytecode compilers. However, JIT compiler can not avoid the overhead of runtime. since it translate bytecode into native code at runtime. And, pure offline bytecode compiler limits the ability of dynamic class loading. In this paper, we present an approach which preserves the ability to dynamically load bytecode, and is more efficient than JIT. In contrast to existing bytecode-to-C translator using the old NMI, our translator maintain complete compatibility and portability through using the Java Native Interface(JNI) standard. We have designed and implemented an translator for converting bytecode to C code with JNI.. named MyJNItool.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.197-206
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• 2019

Telemarketing has been used in finance due to the reduction of offline channels. In order to select telemarketing target customers, various machine learning techniques have emerged to maximize the effect of minimum cost. However, there are problems that the class imbalance, which the number of marketing success customers is smaller than the number of failed customers, and the recall rate is lower than accuracy. In this paper, we propose a method that solve the imbalanced class problem and increase the recall rate to improve the efficiency. The hybrid sampling method is applied to balance the data in the class, and the stacked deep network is applied to improve the recall and precision as well as the accuracy. The proposed method is applied to actual bank telemarketing data. As a result of the comparison experiment, the accuracy, the recall, and the precision is improved higher than that of the conventional methods.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.125-133
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• 2021

Due to Covid-19, the un-contact culture has affected society as a whole, and the methods of education conducted offline has been greatly affected. In the private education of preparing for university entrance, the public official examinations and certification acquisition, the method of online education has been shown to have positive effects. While private class and school class which have offered in off-line to cope with rapid changes caused various problems such as decline in quality for education. Due to the characteristic of design class, practical training is important. As interactive feedback between students and educators is more important than one-way of delivering knowledge while class is conducted in online, educators have a challenge when they prepare for class. This study handles the methods of online education for the purpose of practical education methods in university nowadays, Especially, the non-face-to-face education methods for game animation production. Based on this study, I propose an effective educational method with non-face-to-face class that allows students to be satisfied and increases their knowledge, beyond face-to-face class.

• English Language & Literature Teaching
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• v.16 no.4
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• pp.39-69
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• 2010

This study aims to identify how participants in online-incorporated English learning perceive interaction between achievement and factors of learning and personality. Using grounded theory analysis, this study attempts to generate a theoretical model depicting how the factors work with the L2 learners situated in the learning setting. A total of 231 college freshmen participated in online and offline EFL learning programs for the duration of one semester. In addition, all respondents completed a survey questionnaire on their learning experiences. In the investigation of the differences between low- and high-proficiency groups, audio-taped interviews with 20 selected students, 10 from each group, have revealed differences not only in the types of personal and instructional factors, but also, more importantly, in the interrelationship between these factors in each group's learning model. These models effectively explained the statistically significant differences in four questionnaire items, such as online learning and contributions of offline class sections to their L2 achievement. These findings entail L2 practitioners' shared understandings of their students' perspectives of learning in the specific L2 learning context.

• Journal of the Korea Society of Computer and Information
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• v.23 no.5
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• pp.73-78
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• 2018

Recently, Flipped Learning is attracting attention as a method for qualitative growth of university education. Flipped Learning is a kind of computer based education and consisted of online video lectures and offline student activities. This paper introduces the results of applying Flipped Learning for one semester to Korean linguistic norms course. As for this course, the contents related to the knowledge and information were provided individually before the class through online video, and the offline classes focused on student-led activities. When qualitatively evaluating the results of the course, students developed a more comprehensive and flexible mind set beyond the preexisting normative attitudes and showed increase in analytical and critical thinking in understanding the principles of linguistic norms and spelling system. According to these results we argue that it is necessary to actively adopt Flipped Learning in the humanities education, including the grammar classes.

• Journal of Communications and Networks
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• v.10 no.3
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• pp.351-361
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• 2008

This paper presents a delay-margin based traffic engineering (TE) approach to provide end-to-end quality of service (QoS) in multi-protocol label switching (MPLS) networks using differentiated services (DiffServ) at the link level. The TE, including delay, class, and route assignments, is formulated as a nonlinear optimization problem reflecting the inter-class and inter-link dependency introduced by DiffServ and end-to-end QoS requirements. Three algorithms are used to provide a solution to the problem: The first two, centralized offline route configuration and link-class delay assignment, operate in the convex areas of the feasible region to consecutively reduce the objective function using a per-link per-class decomposition of the objective function gradient. The third one is a heuristic that promotes/demotes connections at different links in order to deal with concave areas that may be produced by a trunk route usage of more than one class on a given link. Approximations of the three algorithms suitable for on-line distributed TE operation are also derived. Simulation is used to show that proposed approach can increase the number of users while maintaining end-to-end QoS requirements.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.155-165
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• 2014

This study deals with the proposals and the verification of the causal relationship between improvements of corporate manager's learning attitude for enterprises productivity and managerial effectiveness, the learner's familiarity and personal character strengths that are classified as positive psychology-based theory. For this study, researchers designed the structural equation model using the AMOS analysis. And researchers conducted the interviews using a questionnaire survey of quantitative research methods. Results of the analysis are as below. First, both online and offline classes were identified as the learner's character strengths affect the positive effect to the learner's familiarity strengths. Second, the learner's familiarity affects the positive effect to improvements of learning attitude. And the last, the learner's character strengths and improvements of learning attitude are not significant effect each other, therefore researcher could be found that the role of mediating variables of the learner's familiarity strengths. In this study, researchers analyzed the relationship between familiarity strengths and improving the learning attitudes needed for a desirable curriculum development considering the learners' personality factors. These findings contribute to an ideal course of study when educator design a curriculum and contribute to a successful communication strategy.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.169-174
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• 2023

The purpose of this study is to analyze Korean college students' perceptions of interactions and senses of community, among students, and instructors and students as they took face-to-face classes by the time students and instructors came back to the classroom. Forty-nine college students participated in the study, and all of them had experienced non-face-to-face classes during the last two years from 2020 through 2021. They responded to the revised Rovai (2002)'s Classroom Community Scale (CCS), and the data were analyzed using a frequency analysis. The findings of data analysis showed that the students positively perceived the class contents and teaching formats of face-to-face classes, in terms of understanding and concentration on the class. On the other hand, it was found out that the students would still need more time for being familiar with face-to-face classes, and their affective variables of the educational environment should be considered.

• Journal of Digital Convergence
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• v.6 no.1
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• pp.123-135
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• 2008

In this study it is aimed to find out the relationship between the effective factors on learning motivation of the digital textbook. To carry on such exploration the learning motivation theory of Keller has been taken as the theoretical background. This is an experimental research with the data collected from 310 students who took the digital textbook class in the computer-mediated environment. It is compared and verified whether the factors causing learning motivation of the ARCS model embedded in the offline class influence on learner's motivation and achievement. With the outcomes, it has been tried to find out some practical suggestions for the achievement of the digital textbook. The results of the data show that the learning motivation of the digital textbook is significantly influence on the learning achievement.