• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.161-177
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• 2023

Scientific explanation is composed of various representations such as texts, diagrams, and graphs, and each representation contributes to expanding scientific meaning by connecting similar but slightly different meanings as a 'mode'. Based on this perspective of social semiotics, we aimed to identify the characteristics of meaning formation demonstrated in students' science writing (verbal mode) and science drawing (visual mode) and to discuss the pedagogical use of multimodal representations. To that end, 18 science drawings and 18 scientific writings constructed by science-gifted elementary students on air pressure were collected. The characteristics of the drawn and written explanations were then analyzed from the affordance perspective in social semiotics. In science drawing, students showed a tendency to use the affordance of the visual mode to infer concrete changes from the particle view, such as the movement of air particles, the number of air particles, and the collision of particles. In science writing, students used the affordance of the verbal mode mainly to infer the causal relationship between the concept of air pressure and other related factors at an abstract level. Based on those results, we discuss the educational implications and provide concrete examples of how to use the unique affordances of each form to complement one another.

• Annual Conference of KIPS
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• 2019.10a
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• pp.742-745
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• 2019

SNS 의 발달로 이를 활용한 제품의 광고가 활발하게 이루어지고 있다. 다양한 제품군 중에서도 사용자의 피부 및 건강의 개선 효과가 나타나는 화장품, 건강보조제 등은 후기 글을 보고 실제 효과를 판단하기에 어려움이 있다. 이는 많은 양의 광고에 가려진 실질적 후기를 찾는 것이 어렵고, 포스팅의 전문을 읽는 것은 비효율적이라는 점에서 기인한다고 할 수 있다. 본 논문에서는 소셜 미디어를 바탕으로 아토피 치료법의 효과를 분석할 수 있는 효과 분석 모델을 개발하고 그 결과를 제시하였다. 먼저 많은 후기가 존재하는 키워드를 기반으로 최대 1000 개의 블로그 포스팅을 수집하였고, 광고성 글을 제외하는 자동 처리 알고리즘을 실시하였다. 다음으로 각각의 후기 글에 나타난 효과를 한눈에 알아볼 수 있도록 점수화하는 효과 분석 알고리즘을 제안하고 실험하였다. 실험결과 감마리놀렌산, 플라즈마, 락토바실러스 등이 긍정적 효과가 있는 치료법으로 나타났다. 본 논문에서 제시한 알고리즘은 제품의 효과를 점수화할 수 있으므로 아토피 치료법에 한정되지 않고, 해당 제품군인 화장품 및 건강보조제 등에 다양하게 적용될 수 있을 것으로 보인다.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.277-283
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• 2022

사주 풀이란 주어진 사주에 대해서 그에 맞는 해석 글을 생성해주는 작업을 의미한다. 전통적으로 사주 풀이는 온전한 사람의 영역으로 인식되어왔으나, 우리는 본 연구를 통해 사주 풀이 영역도 인공지능으로 대체할 수 있을 것이라는 가능성을 탐구한다. 본 연구에서 우리는 최근 연구되고 있는 자연어 생성분야의 연구들에서 영감을 받아, 사주 유형과 사주 풀이 내에 포함할 명사 키워드를 기반으로 풀이글을 생성하는 인공지능 모델 SaJuTeller를 설계한다. 특히 이전 문맥을 고려하여 풀이글을 생성하는 모델과 단순 사주 유형 및 명사 키워드를 기반으로 풀이글을 생성하는 두가지 모델을 제안하며, 이들 각각의 성능을 분석함으로써 각 모델의 구체적인 활용 방안을 제안한다. 본 연구는 우리가 아는 한 최초의 인공지능 기반 사주풀이 연구이며, 우리는 이를 통해 사주풀이에 요구되는 전문인력의 노력을 경감시킴과 동시에, 다양한 표현을 가진 사주 풀이 글을 생성할 수 있음을 제안한다.

• KSBB Journal
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• v.22 no.4
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• pp.234-238
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• 2007

We used electrospary ionization ion trap tandem mass spectrometry (ESI-IT tandem MS) to structural elucidation of three different biantennary-type glycans having zero, one, two galactoses (G0, G1, G2). The highest fragment ion in the MS/MS spectra of three glycans was produced by 0,2-ring cleavage of fucose-linked N-acetylglucosamine (GlcNAc) in reducing end. The fragment ions both from precursor ions and 0,2-ring cleaved ions ($^{0.2}An$; n=5 for G0, n=6 for G1 and G2) were not overlapped each other. As results of $MS^n$ analyses, tandem fragmentation trees of each glycans were generated and 2,4-ring cleavages ($^{2.4}A_6$) were occurred in GlcNAc linked to reducing end GlcNAc. This structural elucidation and fragmentation study of N-linked glycans by tandem mass spectrometry can be applied to structural analysis of more complicated glycans.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.

• Journal of Labour Economics
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• v.25 no.1
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• pp.97-129
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• 2002

It is well known that the quality of job match has strong influence on the efficient allocation of labor resources in the economy on the macro level and also on the productivity of individual worker. Regarding this point we assumed that the selection of preferred job at the job entry can be interpreted as a subjective indicator of job match quality and tried to estimate the effects of such selection on the wage level. For this purpose we suggested random effects switching regression model and applied this model to the data of the Korea Labor Institute Panel Study from 1998 to 2000. As the results of estimation, we found that there exists large wage differentials at least more than fifty percent caused by such selection. Considering the fact that such wage differentials can not be suitably explained by the traditional reasons of the wage discrimination, we suggest the possibility that there also exists large productivity gap caused by the job mismatch and the necessity of improving the job placement service activity.

• Journal of the KSME
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• v.50 no.12
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• pp.45-49
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• 2010

이 글에서는 기존의 운동학적(kinematics) 관점에서 주로 수행되어 오던 보행분석을 기계공학적으로 접근함으로써 보행특성에 대한 이해를 높인 사례들에 대해 소개하고자 한다.

• Journal of the Korean Geographical Society
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• v.36
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• pp.13-25
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• 1987

이 글에서는 다음의 내용을 다루었다. 1. 주성분분석의 결과 및 고찰 2. 기후구분

• Journal of the Korean Geographical Society
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• v.23
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• pp.1-14
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• 1981

이 글에서는 다음의 내용을 다루었다. 1. 지형분류 2. 퇴적물 입도분석 3. 화분분석

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.184-190
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• 2003

이 글은 활용 개념과 수형도를 근간으로 기술되어 온 한국어 문법 모델에 대한 대안으로 표지 개념과 모빌 구조를 제시하고 이를 바탕으로 개발된 한국어 구문분석기의 특성을 소개하고자 한다. 먼저, 조사와 어미를 독자적인 토사 단위인 표지로 처리함으로써 국부 구조의 통사 범주와 문법적 기능을 명확하고 일관되게 구분할 수 있으며, 모빌 구조는 한국어의(상대적) 자유 어순 현상을 효과적으로 기술할 수 있다. 이에 의거한 문법 모형은 언어학적 지식과 구문분석 엔진 사이의 독립성을 향상시킴으로써 향후 구문분석기의 성능 개선을 보다 용이하게 한다. 이 글에서 소개하는 구문분석기는 언어학자에 의해 구축된 지식을 이용한다는 점에서 지식기반적이라고 할 수 있는데 여기에는 동사의 하위범주화 정보, 첨어 유형정보, 의미정보가 핵심적인 언어 지식으로 이용된다. 모빌 구조에 의한 구문분석은 국부 구조를 단순화함으로써 구문적 중의성을 최소화하며, 의미정보는 주어진 술어의 논항적 자격을 검증하는 기준으로 작용하여 구문적 중의성을 감소시키고 정확한 분석을 가능하게 한다.