• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.573-576
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• 2004

High performance SFRC composed of mira-sized ultra fine particles is characterized by high strength, high ductility and excellent durability. therefore many researches about materials based on new composition like this are performed recently. many researchers have reported that adding steel fiber to concrete improved its tensile and flexural strength significantly. the main objective of this research is to examine the effect of adding steel fiber on the tensile strength of high performance SFRC. variables considered in this study are w/c ratio and fiber volume fraction.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.115-120
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• 2006

A Korean Road Roughness Classification(KRC) method is proposed. Using a dynamic road profiling device equipped with the Accelerometer Established Inertial Profiling Reference(AEIPR) method, road profile measurement is performed on various types of public paved roads in Korea. The road profiling data are processed to classify the characteristics of Korean road roughness. The resultant Korean road roughness classification(KRC) is shown different characteristics compared to the road classification proposed by ISO, MIRA, and Wong. The proposed KRC is composed of 8 classes(A-H, very good-poor) based on the power spectral density and is in good agreements with the characteristics of Korean paved road roughness and can be used well in vehicle ride comfort simulation using domestic road profile.

• Phonetics and Speech Sciences
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• v.10 no.4
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• pp.101-110
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• 2018

This study aimed to show that Selkirk's concept of resyllabification offers a better analysis than Kahn's ambisyllabification to account for phonetic resyllabification. We conducted two production experiments to investigate the acoustic characteristics of the English /s/ in real words and nonce words. Ten English native speakers and six English native speakers participated in experiment 1 and experiment 2, respectively. Three acoustic cues - frication duration, center of gravity and aspiration duration of word-medial /s/ - were measured. We found that these three cues of the word-medial /s/ were realized significantly differently depending on the stresshood and openness of the preceding syllable. We preferred Selkirk's resyllabification to Kahn's ambisyllabification to explain this result because the word-medial and intervocalic /s/ behaved as the coda (as opposed to the onset) when the preceding syllable was stressed and open. The result thus suggested that two conditions must be met for the resyllabification rule to apply in English: a word-medial consonant is resyllabified only when its preceding syllable is stressed and open.

• Genomics & Informatics
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• v.16 no.4
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• pp.33.1-33.9
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• 2018

Recently, there have been many studies in medicine related to genetic analysis. Many genetic studies have been performed to find genes associated with complex diseases. To find out how genes are related to disease, we need to understand not only the simple relationship of genotypes but also the way they are related to phenotype. Multi-block data, which is a summation form of variable sets, is used for enhancing the analysis of the relationships of different blocks. By identifying relationships through a multi-block data form, we can understand the association between the blocks in comprehending the correlation between them. Several statistical analysis methods have been developed to understand the relationship between multi-block data. In this paper, we will use generalized canonical correlation methodology to analyze multi-block data from the Korean Association Resource project, which has a combination of single nucleotide polymorphism blocks, phenotype blocks, and disease blocks.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2711-2719
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• 2018

When an observable is described by a single value, the statistic significance may be estimated by construction of null distribution using permutation and counting the portion of it that exceeds the observed value by chance. Genome-wide association study usually focuses on the association measure between a single or interacting genotypes with a single phenotype. However investigation of common genotypes associated simultaneously on multiple phenotypes may involve the observables that should be described with multiple numbers. Statistical significance for such an observable would involve null distribution in multiple dimensions. In this study, extension of the p-value estimation process using null distribution in one dimension has been sought that may be applicable to two dimensional case. Comparison of the position of points within the set of points they form has been proposed to use a positioning parameter inspired by the extension of the Kolmogorov-Smirnov statistic to two dimensions.

• Asia Marketing Journal
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• v.25 no.1
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• pp.26-36
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• 2023

This study examines the effects of disclosing sales commissions pertaining to an influencer discount code on perceived sincerity of an influencer and attitude toward using the discount code. In Study 1, consumers participated in a two-cell (commission disclosure: absent vs. present) between-subjects experimental design. In Study 2, consumers participated in a two (commission disclosure: absent vs. present) by two (discount level: low vs. high) between-subjects experimental design. The findings of Study 1 demonstrate that the sales commission disclosure pertaining to discount codes results in a higher perceived sincerity of the influencer. The results of Study 1 also reveal that the perceived sincerity of the influencer mediates the effect of the disclosure (vs. no disclosure) on attitude toward using the discount code. Further, the findings of Study 2 demonstrate the robustness of these disclosure effects regardless of whether the discount level is low or high.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.626-628
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• 2021

사건 관계 추출 태스크는 구조화되지 않은 텍스트 데이터에서 사건의 구조화된 표현을 얻는 것이다. 하나의 문장에서도 많은 정보를 얻을 수 있는 중요한 태스크임에도 불구하고, 다양한 사전 학습 모델을 적용한 연구는 아직 활발하게 연구되지 않고 있다. 따라서 본 연구에서 사전 학습된 모델의 임베딩 기법 중 BERT, RoBERTa, SpanBERT에 각각 base, large 아키텍처를 적용하여 실험하였다. 사건을 식별하기 위한 trigger와 해당 trigger의 세부 argument를 식별하기 위한 분류기를 상위레이어로 각각 설계하였고, 다양한 배치 크기를 적용하여 실험하였다. 성능평가는 trigger/argument 각각 F1 score를 적용하였고, 결과는 RoBERTa large 모델에서 좋은 성능을 보인 것을 확인하였다.

• Asia Marketing Journal
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• v.25 no.3
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• pp.160-172
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• 2023

This study examines factors influencing gift sharing on social media. An online survey gathered data from American adults. It investigates how motivations for social media content posting, gift attributes, giver characteristics, and recipient reactions affect gift-sharing behavior. Findings show self-expression motives in content posting drive sharing, while social interaction motives do not. Gifts perceived as experiential and expensive are more likely to be shared. Recipient-centric gifts positively influence gift sharing, while giver-centric gifts hinder sharing. Attitude towards the gift predicts sharing, while appreciation does not. The study enhances understanding of gift sharing on social media and offers marketing insights for leveraging this behavior.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.601-604
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• 2023

기술이 발전함에 따라 복합적인 모달리티 정보를 포함하는 멀티미디어 데이터의 수집이 용이해지면서, 사람의 성격 특성을 이해하고 이를 개인화된 에이전트에 적용하고자 하는 연구가 활발히 진행되고 있다. 본 논문에서는 비디오 스트림 구조를 활용하여 사용자 특성을 예측하기 위한 동적 키프레임 추출 방법을 제안한다. 비디오 데이터를 효과적으로 활용하기 위해서는 무작위로 선택한 프레임에서 특징을 추출하던 기존의 방법을 개선하여 영상 내 시간에 따른 정보와 변화량을 기반으로 중요한 프레임을 선택하는 방법이 필요하다. 본 논문에서는 제 3자가 평가한 Big-five 지표 값이 레이블링된 대표적인 데이터셋인 First Impressions V2 데이터셋을 사용하여 외면에서 발현되는 특징들을 기반으로 영상에서 등장하는 인물들의 성격 특성을 예측했다. 결론에서는 선택된 키프레임에서 멀티 모달리티 정보를 조합하여 성격 특성을 예측한 결과와 베이스라인 모델과의 성능을 비교한다.