• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.274-281
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• 2020

N-gram analysis casts a new look at the n-word cluster in use different from the previously known idioms. It analyzes a corpus of English textbooks for frequently occurring n consecutive words mechanically using a concordance software, which is different from the previously known idioms. The current paper aims at extracting and comparing 4-gram words clusters between South Korean high school English textbooks and its North Korean counterpart. The classification criteria includes number of tokens and types between the two across oral and written languages in the textbooks. The criteria also use the grammatical categories and functional categories to classify and compare the 4-gram words clusters. The grammatical categories include noun phrases, verb phrases, prepositional phrases, partial clauses and others. The functional categories include deictic function, text organizers, stance and others. The findings are: South Korean high school English textbook contains more tokens and types in both oral and written languages. Verb phrase and partial clause 4-grams are grammatically most frequently encountered categories across both South and North Korean high school English textbooks. Stance is most dominant functional category in both South and North Korean English textbooks.

• Journal of The Korean Association For Science Education
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• v.24 no.6
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• pp.1143-1157
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• 2004

The purpose of this study was to develop HS-VOSTS(High School Students' Views On Science-Technology-Society), which is an instrument that monitors high school students' views on STS. For this study, 23 multiple-choice items were developed on four categories. First, a categorial scheme was constructed. The categorial scheme was based on many instruments that evaluate students' understanding on STS, literature review, and STS learning goal that many researchers had asserted. Second, the multiple-choice items were developed. The development of the items was carried out through four steps. In the first step, some pairs of statement on each subordinate category were formed. Next, the student statement questionaries which were based on the pairs of statement were responded by 772 students. In the second step, the response written by the students were analyzed to common viewpoints and the first multiple-choice items were constructed. In the third step, the semistructured interview with 28 high school students was implemented and the second multiple-choice items were constructed. In the fourth step, the final version of the instrument was developed through the analysis of the students' response on the second multiple-choice items. HS-VOSTS is an useful instrument for monitoring students' beliefs and viewpoints on STS topics. The results of the students' responses to HS-VOSTS items reflect the students' own thoughts directly. These results will give some implications for the curriculum developers, the authors of text books and the educational policy makers as well as the teachers.

• Journal of Music and Human Behavior
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• v.13 no.1
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• pp.61-87
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• 2016

With broad individual variability in social communication skills of children with autism spectrum disorders and increasing focus on interventions targeting social communication of this population, there is a need for systematic analysis of how social communication outcomes are measured. This study aimed to systematically analyze the measurement tools used in the music therapy interventions for improving social communication of children with ASD. Electronic databases and music therapy journals were searched for controlled studies published between 1980 and 2015. A total of 21 studies were included for the analysis. The results demonstrated that direct observation of behaviors was the most frequently used and the combination of targeted social communication areas and specific measurements used for a specific skill varied among the studies. In addition, 90.4% of studies reported interrater reliability. These results indicate that there has been a diversity in approaches to measure social communication skills despite increasing attempts for systematic measurements. In consideration of the nature of social communication development in children with ASD, multifaceted strategy to understand and assess the target skills in terms of specific behavior acquisition, social functioning in general, and social cognition was recommended.

• Journal of Music and Human Behavior
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• v.13 no.1
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• pp.89-110
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• 2016

This study examined the effect of an interactive instrument playing program on the social interaction of adults with autism spectrum disorder (ASD). A single subject design with multiple baselines across participants was applied, and three adults with severe ASD in their late 20s living at a group home participated in this study. Participants received a total of 25 group sessions. During the intervention, participants engaged in structured instrument playing in which initiation and response to socially interactive behaviors were musically cued, and target behaviors were reinforced in the musical environment. At pre- and posttest, the frequency of initiation of and responding to social interaction behaviors were recorded and analyzed. The results of this study showed that the frequency of both initiation of, and response to, social interaction increased for all participants during the intervention phase, compared to the baseline phase. This result demonstrates that interactive instrument playing increased social behaviors of adults with ASD. It also shows that musically delivered social information can facilitate adults with ASD understanding the intention of social partners in social contexts and motivate this population to engage in social interaction.

• Journal of Gifted/Talented Education
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• v.24 no.6
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• pp.1073-1097
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• 2014

The working concept of the disadvantaged gifted is meant by those who hardly can have a chance to develop one's own gifts because of the environmental conditions and factors. The main purpose of this study is to explore the inherent trait of the music giftedness, which is composed of musical ability, creativity, and task commitment. Grounded upon the phenomenal research, this study purposefully samples ten disadvantaged students who participated in the arts gifted camp hosted by Korean National Research Institute for the Gifted in Arts. Thus, it explores the inherent traits of the disadvantaged gifted by coding, segmenting, and analyzing the interview with ten disadvantaged, and the evaluation reports of the expert group. The inherent trait of music giftedness of the disadvantaged gifted is shown as this: the inherent trait of the disadvantaged gifted in music is closely interrelated with one's own concept of giftedness. Whereas they show the high motivation and task commitment, they are hardly observed to have the creativity in their musical activities and learning. Finally, this study give a proposition for the strategy to stimulate and improve the inherent trait of the disadvantaged gifted in music: the importance of parents education and parent screening, meta-cognitive skills, the leaning-based creativity education, and the significant role of intrapersonal catalyst.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.257-264
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• 1999

자연언어 처리에 있어 문장의 성분 구조를 파악하는 통사적 해석에서는 애매성 있는 결과가 많이 생성된다. 한국어의 경우 어순 등의 통사적 특성뿐 아니라 상황과 의미, 문맥이 문장의 분석에 더 중요한 역할을 하기 때문에 문맥 자유 문법에 의한 접근 방법만으로는 중의적 구조의 해결이 어렵다. 이는 또한 의미 분석시 애매성을 증가시키는 원인이 된다. 이러한 통사적, 의미적 중의성 해결을 위해 용언 중심의 하위범주화 사전을 구축하였다. 본 논문에서는 용언에 따라 제한될 수 있는 하위범주 패턴을 정의하고 패턴에 따라 하위범주 사전을 구축하였다. 하위범주화 사전에는 명사의 시소러스와 정합하여 보어를 선택 제한(Selectional Restriction)할 수 있도록 용언과 명사와의 의미적 연어 관계에 따라 의미마커를 부여했다. 말뭉치를 통해 수집된 용언 12,000여개를 대상으로 25,000여개의 하위범주 패턴을 구축하였고 이렇게 구축한 하위범주화 사전이 120,000여 명사에 대한 의미를 갖고 있는 계층 시소러스 의미 사전과 연동하도록 하였다. 또한 논문에서 구현된 하위범주화 사전이 구문과 어휘의 중의성을 어느 정도 해소하는지 확인하기 위해 반자동적으로 의미 태깅(Sense Tagging)된 2만여 문장의 말뭉치를 통해 검증 작업을 수행하고, 의존관계와 어휘의 의미를 포함하고 있는 말뭉치에 하위범주 패턴이 어느정도 정합되는지를 분석하여, 하위범주 패턴과 말뭉치의 의존관계만 일치하는 경우와 어휘의 의미까지 일치하는 경우에 대해 평가한다. 이 과정에서 하위범주 패턴에 대한 빈도 정보나, 연어 정보를 수집하여 데이터베이스에 포함시키고, 각 의미역과 용언의 통계적 공기 정보 등을 추출하는 방법도 제시하고자 한다.을 입증하였다.적응에 문제점을 가지기도 하였다. 본 연구에서는 그 동안 계속되어 온 한글과 한잔의 사용에 관한 논쟁을 언어심리학적인 연구 방법을 통해 조사하였다. 즉, 글을 읽는 속도, 글의 의미를 얼마나 정확하게 이해했는지, 어느 것이 더 기억에 오래 남는지를 측정하여 어느 쪽의 입장이 옮은 지를 판단하는 것이다. 실험 결과는 문장을 읽는 시간에서는 한글 전용문인 경우에 월등히 빨랐다. 그러나. 내용에 대한 기억 검사에서는 국한 혼용 조건에서 더 우수하였다. 반면에, 이해력 검사에서는 천장 효과(Ceiling effect)로 두 조건간에 차이가 없었다. 따라서, 본 실험 결과에 따르면, 글의 읽기 속도가 중요한 문서에서는 한글 전용이 좋은 반면에 글의 내용 기억이 강조되는 경우에는 한자를 혼용하는 것이 더 효율적이다.이 높은 활성을 보였다. 7. 이상을 종합하여 볼 때 고구마 끝순에는 페놀화합물이 다량 함유되어 있어 높은 항산화 활성을 가지며, 아질산염소거능 및 ACE저해활성과 같은 생리적 효과도 높아 기능성 채소로 이용하기에 충분한 가치가 있다고 판단된다.등의 관련 질환의 예방, 치료용 의약품 개발과 기능성 식품에 효과적으로 이용될 수 있음을 시사한다.tall fescue 23%, Kentucky bluegrass 6%, perennial ryegrass 8%) 및 white clover 23%를 유지하였다. 이상의 결과를 종합할 때, 초종과 파종비율에 따른 혼파초지의 건물수량과 사료가치의 차이를 확인할 수 있었으며, 레드 클로버 + 혼파 초지가 건물수량과 사료가치를 높이는데 효과적이었다.\ell}$ 이었으며 , yeast extract 첨가(添加)하여 배양시(培養時)는 yeast extract

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.84-93
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• 2012

Most of the studies on reduction of buildings' environmental burden in the construction industry have been focused on carbon dioxide emission, although there are various kinds of environmental issues such as global warming, acidification, and etc. which are considered by many researchers. Therefore, this study defined and suggested six impact categories and the principles to assess each impact for the assessment of comprehensive environmental impacts of buildings. The six impact categories are abiotic depletion, global warming, ozone layer depletion, acidification, eutrophication, and photochemical oxidation. A case study has been conducted through comparative analysis of two structural design alternatives to confirm the necessity of assessing the six impact categories. That is, the results of global warming potential and the six impacts proposed in this study were compared. By comparing the results of only global warming potential, the second design alternative using 24MPa concrete was chosen as a better alternative, while the first design alternative using 21MPa concrete was resulted as a better alternative when six impact categories were considered. The results mean that the assessment of various environmental impacts is an appropriate and reasonable approach and the comprehensive assessment offers more reliable results of environmental impacts in the building construction.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.287-311
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• 2021

It is not easy for information users to find books that are suitable for them in a knowledge information society. There is a growing need for libraries to break away from traditional services and provide user-tailored recommendation services, but there are few qualitative studies on user satisfaction so far. In this study, a user-customized book recommendation was performed by applying Apriori, a correlation analysis algorithm, and satisfaction factors were analyzed in depth through interviews. The experimental data was the loan data of 100 people who used the most frequently used loan data for 10 years from 2009 to 2019 of the S library in Seoul. The interviewees of the experiment were those who could be interviewed in depth. After the correlation analysis, the concepts and categories derived by analyzing the interview data were 59 concepts, 6 sub-categories, and 2 upper categories, respectively. The upper categories were 'reading' and 'book recommendation service'. In the 'reading' category, there were 16 concepts of motivation for reading, 8 concepts of preferred books, and 12 concepts of expected effects. Also, in the category of 'reading recommendation service', there were 10 'reflection factors', 4 'reflection methods', and 9 'satisfaction factors'.

• Science of Emotion and Sensibility
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• v.26 no.1
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• pp.55-64
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• 2023

This research investigated category-based feature inference when category features were connected in common cause and common effect causal networks. Previous studies that tested feature inference in causal categories showed unique inference patterns depending on causal direction, number of related features, whether the to-be-inferred feature was cause or effect, etc. However, these prior studies primarily focused on inference pattens that arise from causal relations, and few studies directly explored how the effects of causal relations vary depending on causal strength. We tested feature inference in common cause (Expt. 1) and common effect (Expt. 2) causal categories when casual strengths were either strong or weak. To this end, we had participants learn causal categories where features were causally linked and then perform feature inference task. The results showed that causal strengths as well as causal relations had important impacts on feature inference. When causal strength was strong, inference for common cause feature became weaker but that for the common effect feature became stronger. Moreover, when causal strength was strong and common cause was present, inference for the effect features became stronger, whereas the results were reversed in common effect networks. In particular, in common effect networks, casual discounting was more evident with strong causal strength. These results consistently demonstrate that participants consider not only causal relations but also causal strength in feature inference of causal categories.