• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.606-611
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• 2009

This paper describes a method for achieving a novel design within a class of 3D objects that would create a preferred impression on users. Physical parameters of the 3D objects that might strongly contribute to their visual impressions are sought through computational investigation of the impression ratings obtained for learning samples. "Car body" was selected as the class of 3D objects to be investigated. A morphable 3D model of car bodies that describes the variations in appearance using a smaller number of parameters was obtained. Based on each car body's rating for the impression of speediness obtained by paired comparison, the visual impression was transformed by manipulating the parameters defined in the morphable 3D model. The validity of the proposed method was confirmed by psychological experiments. A new scheme is also proposed to properly re-sample a novel object of a peculiar shape so that such an object could also be represented by the morphable 3D model.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.171-183
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• 2020

Capsule endoscopy is one of the increasingly demanded diagnostic methods among patients in recent years because of its ability to observe small intestine difficulties. It is often conducted for 12 to 14 hours, but significant frames constitute only 10% of whole frames. Thus, it has been designed to automatically acquire significant frames through deep learning. For example, studies to track the position of the capsule (stomach, small intestine, etc.) or to extract lesion-related information (polyps, etc.) have been conducted. However, although grouping or labeling the training images according to similar features can improve the performance of a learning model, various attributes (such as degree of wrinkles, presence of valves, etc.) are not considered in conventional approaches. Therefore, we propose a class-labeling method that can be used to design a learning model by constructing a knowledge model focused on main lesions defined in standard terminologies for capsule endoscopy (minimal standard terminology, capsule endoscopy structured terminology). This method enables the designing of a systematic learning model by labeling detailed classes through differentiation of similar characteristics.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.362-371
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• 2022

As considerable interests in noise emission from the ships have been increased, International Maritime Organization (IMO) standardized the Underwater Radiated Noise (URN) measurement process of commercial ships in deep seas by enacting the related ISO standard ISO 17208-1 and classification societies responded with the enactment or revision of corresponding notations. According to this trend, a new hybrid underwater sound propagation model based on underwater sound propagation theories was developed and its accuracy on analysis was verified through the result comparison with the results of other generally used models. Using the verified model, each URN propagation characteristics adjusted by the correction methods proposed in the ISO standard and class notations were analyzed and compared in two assumed URN measurement cases. The results showed that the effects of transmission loss corrections in the circumstances with less bottom reflections generally similar but they had rather large differences in the model analysis results with bottom-reflection-dominant conditions. It was concluded that the deep consideration of effective bottom-reflection-correction method should be made in future revisions of ISO standard and class notations.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.1
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• pp.1-6
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• 2023

This study developed models using decision forest, support vector machine, and logistic regression methods to predict and prevent suicidal ideation among Korean adolescents. The study sample consisted of 51,407 individuals after removing missing data from the raw data of the 18th (2022) Youth Health Behavior Survey conducted by the Korea Centers for Disease Control and Prevention. Analysis was performed using the MS Azure program with Two-Class Decision Forest, Two-Class Support Vector Machine, and Two-Class Logistic Regression. The results of the study showed that the decision forest model achieved an accuracy of 84.8% and an F1-score of 36.7%. The support vector machine model achieved an accuracy of 86.3% and an F1-score of 24.5%. The logistic regression model achieved an accuracy of 87.2% and an F1-score of 40.1%. Applying the logistic regression model with SMOTE to address data imbalance resulted in an accuracy of 81.7% and an F1-score of 57.7%. Although the accuracy slightly decreased, the recall, precision, and F1-score improved, demonstrating excellent performance. These findings have significant implications for the development of prediction models for suicidal ideation among Korean adolescents and can contribute to the prevention and improvement of youth suicide.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.537-543
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• 2016

This paper suggests a class model to improve the English oral proficiency for intermediate low English speaking learners. Utilizing the four English skills (reading, writing, listening and speaking), the class model focuses on the learners' schema and discussion strategies. To enhance the learners' motivation and match their cognitive capacity, 10 discussion topics were prepared by surveying the learners. A pilot experiment was conducted to investigate the teaching effects of the discussion class model with 26 college students majoring in English in Seoul. The participants' oral proficiency was measured both before, and after the instructions by OPIc (Oral Proficiency Interview in computer). As a result of the experiment, the percentage of participants whose oral proficiency levels were lower than intermediate mid decreased from 82% to 47%. In addition, the percentage of participants with higher oral proficiency than intermediate low was increased dramatically from 18% to 53%, which supports the claim that through discussion, the class learners' diverse and creative ideas need to be expressed in a formal and intelligible language. Finally, through the findings of the study, the possibility of a discussion class can be expected, regardless of the learners' low level of oral proficiency.

• Korean Journal of Mathematics
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• v.16 no.2
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• pp.233-242
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• 2008

We deal with the closed forms of European option pricing for the general class of volatility asset model and the jump-type volatility asset model by several methods.

• Journal of Gifted/Talented Education
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• v.22 no.2
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• pp.291-315
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• 2012

This study try to analyze feature of model creation and model developing process for gifted students and the activity of students and teachers affected those processes in scientific model constructing class for phase change of moon. For this, I teach scientific model constructing class for science gifted students. I shoot video and record the voice for whole class and each group activity, have a face-to-face talk for selected group members, analyze the paper of activities. I reconstruct model creation and model developing process for each groups and each students, draw a influence that activity aspects of the students and role of the teacher affected modelling process based on those data. After analyzing, I find that discussion in the group contribute model creation and model developing process and developing process of each model changed according to the similarity between target model and first model. The more the students actively participate group activities, the more first model is diversified and final model is more elaborated. Also, the teacher influence model creation and developing process.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.39-47
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• 2016

The purpose of this study is to investigate the smartwork use resistance and Non-Class-Related Behavior of attendees in university smartwork class with the perspective of Motivation-Threat-Ability. To do this, this study built a research model and examined how smartwork switching cost, threat and self-efficacy affect Non-Class-Related Behavior through smartwork use resistance. We also examined the relationship between self-efficacy and Non-Class-Related Behavior. The survey method was used for this paper, and data from a total of 80 university students were used for the analysis. And structural equation model was used to analyze the data. The results of this empirical study is summarized as followings. First, switching cost and threat have direct effects on the use resistance of smartwork services. Second, smartwork use resistance has a negative effect on Non-Class-Related Behavior but self-efficacy has a positive effect on it. Further, it will provide meaning suggestion point of the importance of use resistance motivations in establishing the use policy of smartwork services.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1A
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• pp.30-37
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• 2006

In this paper, we propose a QoS-aware efficient bandwidth re-provisioning scheme in a next generation wireless packet transport network. At the transport network layer, it classifies the traffic of the radio network layer into a real time class and a non-real time class. Using an auto-regressive time-series model and a given packet loss probability, our scheme predicts the needed bandwidth of the non-real time class at every re-provisioning interval. Our scheme increases the system capacity by releasing the unutilized bandwidth of the non-real time traffic class for the real-time traffic class while insuring a controllable upper bound on the packet loss probability of a non-real time traffic class. Through empirical evaluations using the real Internet traffic traces, our scheme is validated that it can increase the bandwidth efficiency while guaranteeing the quality of service requirements of the non-real time traffic class.

• Journal of Korea Water Resources Association
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• v.48 no.3
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• pp.233-243
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• 2015

The bimodal flocculation of cohesive sediments in water environments describes the aggregation and breakage process developing a bimodal floc size distribution with dense flocculi and floppy flocs. A two class population balance equation (TCPBE) was tested for simulating the bimodal flocculation by a model-data fitting analysis with two sets of experimental data (low and high turbulent flows) from 1-D flocculation-settling column tests. In contrast to the Single-Class PBE (SCPBE), the TCPBE could simulate interactions between flocculi and flocs and the flocculation mechanism by differential settling in a low turbulent flow. Also, the TCPBE could perform the same quality of simulation as the elaborate Multi-Class PBE (MCPBE), with a small number of floc size classes and differential equations. Thus, the TCPBE was proven to be the simplest model that is capable of simulating the bimodal flocculation of cohesive sediments in water environments and water, wastewater treatment systems.