• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2005.11a
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• pp.168-168
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• 2005

• Journal of the Society of Naval Architects of Korea
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• v.49 no.4
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• pp.333-339
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• 2012

The main objective of the present study is to investigate the roles of the micro-dimpled surface on the drag reduction. To investigate the effectiveness of the micro-dimpled surface, the flat plates are prepared. The micro-size dimples are directly carved on the metal surface by ultrasonic nano-crystal surface modification (UNSM) method. Momentum of the main flow is increased by the dimple patterns within the turbulent boundary layer (TBL), however, there is no significant change in the turbulence intensity in the TBL. The influence of dimple patterns is examined through the flow field survey near the flat plate trailing edge in terms of the profile drag. The wake flow velocities in the flat plate are measured by PIV technique. The maximum drag reduction rate is 4.6% at the Reynolds number of $10^6{\sim}10^7$. The dimples tend to increase the drag reduction rate consistently even at high Reynolds number range.

• Biomedical Science Letters
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• v.19 no.2
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• pp.153-157
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• 2013

Although culture is the gold standard method to identify mycobacteria, its use in tuberculous lymphadenitis (TBL) is limited due to formalin fixation of the submitted specimens. We evaluated the performance of quantitative real-time PCR (q-PCR) for Mycobacterium Tuberculosis (MTB) in granulomatous lymphadenitis using formalin-fixed paraffin-embedded (FFPE) tissues. From 2000 to 2010, a total number of 117 cases of lymph node samples with granulomatous inflammation which were surgically removed and fixed in formalin were studied. Hematoxylin & Eosin (H&E) and Ziehl-Neelsen-stained (ZN) slides were reviewed. qPCR using Real TB-Taq$^{(R)}$ was performed for all cases to identify Mycobacterium tuberculosis. Thirteen non-tuberculous lymphadenopathy cases were used as negative control. Cervical lymph nodes were more frequently affected (60%, 70/117) than other sites. ZN stain for acid fast bacilli was positive in 19 (16.24%) cases. qPCR for tuberculosis was positive in 92 (78.63%) cases. Caseous necrosis was found in 103 (88.03%) cases. While the ZN stain and qPCR were both negative in all control cases, the qPCR showed a significantly higher positive rate (78.63% vs. 16.24%) compared to ZN stain in histologically diagnosed TBL. Quantitative real-time PCR proves to be more sensitive than ZN stain for diagnosis of tuberculous lymphadenitis.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.63-70
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• 2017

The purpose of this study was to investigate the mediating effect of perceived self-efficacy in the effects of informal communication and mindfulness practice on non-class-related behavior in the Team-Based Learning(TBL) using smartwork tool. To do this, total of 80, college students participated in this survey. The results of this empirical study is summarized as followings. First, informal communication do not have a direct effect on non-class-related behavior but perceived self-efficacy mediates the effect of informal communication. Second, mindfulness practice do not have a direct effect on non-class-related behavior but perceived self-efficacy mediates the effect of mindfulness practice. Third, informal communication and mindfulness practice have positive effect on perceived self-efficacy. In this study, we suggested the importance of perceived self-efficacy in establishing the TBL policy using smartwork tool.

• Fashion & Textile Research Journal
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• v.20 no.1
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• pp.34-49
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• 2018

Sustainability in fashion pertains to all stages within the product lifecycle, starting with the procurement of raw materials and ending with the disposal of the product. To clarify, the Lifecycle Management (LCM) views the Triple Bottom Line (TBL) from the perspective of a product's lifecycle. Sustainable products are identified based on their lifecycle, causing public attention to turn towards Product Lifecycle Management (PLM). As of now, PLM is largely known to have a strong impact on New Product Development (NPD). As such, the objective of this research is to study how PLM-based sustainable NPD models, when applied to the fashion industry, can produce a wide understanding of sustainable fashion products from a variety of angles. In order to achieve the research objective, this study did a selective case study on 20 sustainable fashion brands; conducted 1:1 in-depth interviews with 24 fashion experts, including both sustainable and non-sustainable experts; and took part in participant observation of 5 sustainable fashion brands. The results of the study indicate that there are specific conditions that must be met at each stage of production for the development of sustainable products by fashion brands. However, due to the lack of technological skills and the dearth of sustainability experts within the organization, management, monitoring and systematic collection of data is not properly implemented - leading to problems with the quantification of crucial data. This study aims to further forward the debate regarding the development of sustainable fashion products and its future implications.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.155-160
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• 2010

This paper proposes a method for Korean comparative sentence classification which is a part of comparison mining. Comparison mining, one area of text mining, analyzes comparative relations from the enormous amount of text documents. Three-step process is needed for comparison mining - 1) identifying comparative sentences in the text documents, 2) classifying those sentences into several classes, 3) analyzing comparative relations per each comparative class. This paper aims at the second task. In this paper, we use transformation-based learning (TBL) technique which is a well-known learning method in the natural language processing. In our experiment, we classify comparative sentences into seven classes using TBL and achieve an accuracy of 80.01%.

• Proceedings of the IEEK Conference
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• summer
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• pp.382-386
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• 2004

Recently, with the machine learning trend, most of the machine translation systems on over the world use two syntax tree sets of two relevant languages to learn syntactic tree transfer rules. However, for the English-Vietnamese language pair, this approach is impossible because until now we have not had a Vietnamese syntactic tree set which is correspondent to English one. Building of a very large correspondent Vietnamese syntactic tree set (thousands of trees) requires so much work and take the investment of specialists in linguistics. To take advantage from our available English-Vietnamese Corpus (EVC) which was tagged in word alignment, we choose the SITG (Stochastic Inversion Transduction Grammar) model to construct English- Vietnamese syntactic tree sets automatically. This model is used to parse two languages at the same time and then carry out the syntactic tree transfer. This English-Vietnamese bilingual syntactic tree set is the basic training data to carry out transferring automatically from English syntactic trees to Vietnamese ones by machine learning models. We tested the syntax analysis by comparing over 10,000 sentences in the amount of 500,000 sentences of our English-Vietnamese bilingual corpus and first stage got encouraging result $(analyzed\;about\;80\%)[5].$ We have made use the TBL algorithm (Transformation Based Learning) to carry out automatic transformations from English syntactic trees to Vietnamese ones based on that parallel syntactic tree transfer set[6].

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.10
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• pp.917-923
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• 2010

Direct numerical simulation (DNS) of a spatially developing turbulent boundary layer (TBL) with regularly arrayed cubical roughness elements was performed to investigate the effects of three-dimensional (3D) surface elements. The staggered cubes downstream were periodically arranged in the streamwise and spanwise directions with pitches of $p_x$/k=8 and $p_z$/k=2, where $p_x$ and $p_z$ are the streamwise and spanwise spacings of the cubes; the roughness height (k) was k=$1.5{\theta}_{in}$, where ${\theta}_{in}$ is the momentum thickness at the inlet. Spatially developing characteristics over the 3D cubical roughness were compared with the data obtained from the DNS over the two-dimensional (2D) rod roughened wall and smooth wall. Introduction of the cubical roughness on the TBL affected the turbulent Reynolds stresses not only in the roughness sublayer but also in the outer layer; and these effects are consistent with those observed over the 2D rough wall.

• Journal of KIISE
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• v.43 no.1
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• pp.80-86
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• 2016

A speech-act is a behavior intended by users in an utterance. Speech-act classification is important in a dialogue system. The machine learning and rule-based methods have mainly been used for speech-act classification. In this paper, we propose a speech-act classification method based on the combination of support vector machine (SVM) and transformation-based learning (TBL). The user's utterance is first classified by SVM that is preferentially applied to categories with a low utterance rate in training data. Next, when an utterance has negative scores throughout the whole of the categories, the utterance is applied to the correction phase by rules. The results from our method were higher performance over the baseline system long with error-reduction.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.139-155
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• 2023

The purpose of this study is to improve the digital literacy of pre-service home economics education teachers by designing and applying 'teaching materials and methods of home economics education' class using the Metaverse platform in virtual classes during the Covid-19 pandemic. For this purpose, six lessons of the 'Teaching Materials and Methods of Home Economics Education' classes were designed and applied as a class using the Metaverse platform, and the effectiveness was analyzed. In this study, three types of classes(TBL, discussion, and PBL) were developed and evaluated. The results of the study showed that most of the learners were satisfied with the classes utilizing the Metaverse platform, and the effectiveness of the classes was shown in terms of learner-instructor interaction and the realism of actual classroom cases. Based on these results, it is expected that various home economics education classes utilizing metaverse platforms will be developed and applied to school sites to increase the realism of lessons.