• Title/Summary/Keyword: 세이마이트

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A Study on the Cultural Exchange of the Weaving Skills and Patterns Witnessed in Geum-textiles between the East and West - from Ancient Times to the Tang Dynasty - (제직기술과 문양을 통해 본 금직물(錦織物)의 동서교류에 관한 연구 - 고대부터 당시대를 중심으로 -)

  • Shin, Hey-Sung
    • Journal of the Korean Society of Costume
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    • v.62 no.4
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    • pp.107-122
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    • 2012
  • The purpose of this study is to investigate the changes and developments that occurred as a result of the exchanges of gyeong-geum(經錦), a warp-faced compound weave of East Asia, and wie-geum(緯錦), a weft-faced compound weave of West Asia. In order to maximize the efficiency of this research, topics were narrowed down to the weaving skills and patterns, and the period was limited to the Tang dynasty. The systematic characteristics and differences of gyeong-geum and wie-geum were compared and contrasted through different works of literature. Then the excavated remains of geum-textiles were analyzed and the characteristics of the geum-textiles were defined in chronological order. The origin of wie-geum is traced back to the time when West Asia started to imitate the weaving style of the East Asian gyeong-geum. When combined with the weaving skills of the West Asian, gyeong-geum, which broke through the West and developed into the weft-faced compound twill silk, or samite. The exchange of geum-textiles took place as the techniques of gastric filament woven geum-textiles returned to the East. Along with the pearl roundel motifs of Sassanian Persia, mythical animals and western motifs of hunter patterns were used for the patterns of wie-geumin during the early Tang dynasty. This tendency is related to pa-sa-geum(波斯錦), ho-geum(胡錦), beon-geum(番錦) according to the recorded literature. The 8th and 9th century are periods when the West Asian Persian style was abandoned and the East Asian style, samite, was established. Not only did S twist silk threads replace Z twists, but also the repetition of patterns unfolded along with the weft and the warp. As this tendency was strengthened after the 9th century, the expression of patterns became more vividly colorful and showed both elements of naturalism and realism. The characteristics of the Bosangwha(寶相花) pattern in the Tang period were established with the rampantly repeated rosettes with birds often holding auspicious branches, that fly amid floral compositions.

A Study on the Bio-Based Polyurethane (바이오 폴리우레탄에 관한 연구)

  • Ko, Jong-Sung;Lee, Jin-Hui;Sung, Ki-Chun
    • Journal of the Korean Applied Science and Technology
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    • v.29 no.3
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    • pp.531-542
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    • 2012
  • The thesis covers the trend of research on bio-based polyurethane which is made from polyols derived mainly from plant oils and isocyanates. Castor oil is a triglyceride of ricinoleic acid containing hydroxyl group. Hydroxylation is done on the unsaturated bonds of the oils by the reactions of epoxidation/ring opening, hydroformylation/hydrogenation, ozonolysis/hydrogenation, and thiol-ene reaction. Polyols from hyperbranch, primary alcohol, polysaccharide have been studied to control the reactivity of the polyol and morphology of the microdomains. Besides, researches cover biodegradable polylactic acid polyol for medical use, fatty acid dimer polyol for the prevention of hydrolysis, and polyol with ionic group for water-borne polyurethane. Bio-based polyurethanes are being used in flexible and rigid foams, coatings, sealants, and elastomers.

A Study on Content Marketing for Travel Brand Focus on Youtube Vlog Formed Travel Video - (여행 브랜드를 위한 콘텐츠 마케팅 연구 -여행 영상 형태의 유튜브 Vlog를 중심으로-)

  • Jo, Jang-Hwan;Park, Bo-ram
    • Journal of Digital Convergence
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    • v.17 no.12
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    • pp.445-450
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    • 2019
  • lock in effect This study aims to examine the viewing pattern of travel vlog on video-sharing platform YouTube. Preliminary survey was conducted with in-depth interviews on the usability and sensibility aspects of creating pleasurable interfaces model. As a result, first, viewers obtains general information on travel using travel vlog. Second, there were difficulties from the informational quantity. Third, the contents marketing using travel vlog could have limitation when it comes to the consistency of product's exposure which common mass media advertisement format have. Improvements driven from this study may provide insight in contents marketing strategy to travel-related companies and provide practical help to creators in contents production.

What Is a Monster Narrative? Seven Fragments on the Relationship between a Monster Narrative and a Catastrophic Narrative (괴물서사란 무엇인가? - 괴물서사에서 파국서사로 나아가기 위한 일곱 개의 단편 -)

  • Moon, Hyong-jun
    • Cross-Cultural Studies
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    • v.50
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    • pp.31-51
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    • 2018
  • The concept of 'monsters' have become popular, again, in recent times. A number of 'monster narratives' that discuss monsters such as zombies, humanoids, viruses, extraterrestrials, and serial killers have been made and re-made in popular media. Noting such an interesting cultural context, this article attempts, first, to find out some essential prototypical elements of a monster narrative and, second, to relate it with a catastrophic narrative. Correspondingly, the word 'monster' has been used as a conceptual prototype category that denies universal and clear definition, which makes it as one of the most widely used and familiar subjects of the use of metaphor. The prototypical meanings of various monster figures can be converged on a certain creature of being in this way held out as bizarre, curious, and abnormal. The monster figure that surpasses existing normality is also connected to 'abjection,' such as something that is cast aside from the body such as the bodily functions seen in its associated blood, tears, vomit, excrement, or semen, and so on. Nevertheless, both the monster figure and abjection produce disgust and horror in the minds of ordinary spectators or readers of media using this metaphor to heighten excitement for the viewers. The abject characteristic of the monster figure also has something in common with the posthuman figure, meaning to apply to a category of inhuman others who are held outside of the normal category of human beings. In the similar vein, it is natural that the most typical monster figures in our times are posthuman creatures embodied in such forms as seen with zombies, humanoids, cyborgs, robots, and so on. In short, the monster figure includes all of the creatures and beings that disarray normalized humanist categories and values. The monster narrative, in the same sense, is a type of story that tells about others outside modern, anthropocentric, male-centered, and Westernized categories of thought. It can be argued that a catastrophic narrative, a literary genre which depicts the world where a series of catastrophic events demolish the existing human civilization, ought to be seen as a typical modern-day monster narrative, because it also discounts and criticizes normalized humanist categories and values as is the result of the monster narrative. Going beyond the prevailing humanist realist narrative that are so familiar with existing values, the catastrophic narrative is not only a monster narrative per se, but also a monstrous narrative which disrupts and reinvents currently mainstream narratives and ways of thinking.

General Geochemical Characteristics of Dashinchilen Nb-Ta and Sant Cu Occurrences in Southeastern Part of Khangai Area, Mongolia (몽골 항가이 남동부 지역 다신칠렌 탄탈륨-니오븀 및 산트 동 산출지의 지구화학적 특성 개요)

  • Kim, In Joon;Lee, Bum Han;Heo, Chul-Ho
    • Economic and Environmental Geology
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    • v.46 no.5
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    • pp.455-468
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    • 2013
  • We performed reconnaissance survey on Dashinchilen Nb-Ta REE area and Sant Cu area which are located in southeastern part of Khangai rare metals mineralized belt. In Dashinchilen area, Nb and Ta have been found in pegmatitic granite that is largely distributed in the survey area and muscovite in pegmatite which is an intrusion in paleozoic sedimentary rocks which are mostly composed of sandstone. While grades of Nb and Ta are not high, an outcrop that has high Th and U contents (542 ppm of Th and 56.9 ppm of U) has been found. Average and maximum REE contents in the survey area is three times and seven times, respectively, larger than average REE contents in the crust of the Earth. In Sant area, copper oxides such as malachite has been found in quartzite in paleozoic sedimentary rocks. A sedimentary rock formation that has high grade of Mn (12.4-34.6 %) has been found in the survey area. This sedimentary rock formation is the same formation with that of Ugii Nuur Fe-Mn mineralization which is located about 200 km northwest of the survey area. Average and maximum REE contents in the survey area is two and half times and seven times, respectively, larger than average REE contents in the crust of the Earth. According to the factor analysis for the data of the geochemical analysis, Nb and Ta in Dashinchilen area are highly correlated with muscovite and Cu in Sant area is highly correlated with Mo, Sn, and Bi. Furthermore, the factor analysis results show that Fe in Sant area was deposited with rare earth elements.

A Development of Defeat Prediction Model Using Machine Learning in Polyurethane Foaming Process for Automotive Seat (머신러닝을 활용한 자동차 시트용 폴리우레탄 발포공정의 불량 예측 모델 개발)

  • Choi, Nak-Hun;Oh, Jong-Seok;Ahn, Jong-Rok;Kim, Key-Sun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.36-42
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    • 2021
  • With recent developments in the Fourth Industrial Revolution, the manufacturing industry has changed rapidly. Through key aspects of Fourth Industrial Revolution super-connections and super-intelligence, machine learning will be able to make fault predictions during the foam-making process. Polyol and isocyanate are components in polyurethane foam. There has been a lot of research that could affect the characteristics of the products, depending on the specific mixture ratio and temperature. Based on these characteristics, this study collects data from each factor during the foam-making process and applies them to machine learning in order to predict faults. The algorithms used in machine learning are the decision tree, kNN, and an ensemble algorithm, and these algorithms learn from 5,147 cases. Based on 1,000 pieces of data for validation, the learning results show up to 98.5% accuracy using the ensemble algorithm. Therefore, the results confirm the faults of currently produced parts by collecting real-time data from each factor during the foam-making process. Furthermore, control of each of the factors may improve the fault rate.

The Relative Effects of Business-to-Business (vs. Business-to-Consumer) Business Model Innovation on Innovation Performance (B2B (vs. B2C) 비즈니스모델혁신이 혁신성과에 미치는 상대적 효과)

  • Yejin Park;Chaeeun Lee;Wonjoo Yun
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.6
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    • pp.159-172
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    • 2023
  • This study aims to empirically investigate the relative effects of business-to-business (vs. business-to-consumer) business model innovation (BMI) on innovation performance. The research examines the impact of three key components of BMI: 1. value creation, 2. value proposition, and 3. value capture, on innovation performance. The 2022 Entrepreneurship Survey data by the Korean Entrepreneurship Foundation was used to analyze 2,879 companies. An exploratory data analysis (EDA) including various categories such as industry, firm, CEO, and technology chracteristics was conducted to show the latest startup status in Korea. The results show that value creation of B2B (vs. B2C) firms has a more positive and significant impact on innovation performance. Whereas, value proposition of B2C (vs. B2B) firms was found to have a more positive and significant effect on innovation performance. Interestingly, value capture did not show any effects for either type of firms. Additionally, the study employed seemingly unrelated regression (SUR) analysis for robustness checks. These findings provide important insights about the relative effects of B2B-BMI (vs. B2C-BMI).

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Mineral chemistry and major element geochemistry of the granitic rocks in the Cheongsan area (청산 일대에 분포하는 화강암류의 광물조성과 주성분원소 지구화학)

  • 사공희;좌용주
    • The Journal of the Petrological Society of Korea
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    • v.6 no.3
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    • pp.185-209
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    • 1997
  • Granitic rocks in the Cheongsan area cosist of three plutons-Baegrog granodiorite, Cheongsan porphyritic granite, and two mica granite. Amphilboles from the Baegrog granodiorite belong to the calcic amphilbole group and show compositional variations from magnesio-hornblende in the core to actinolitic hornblende in the rim. Biotites from the three granites represent intermediate compositions between phlogopite and annite. Muscovites from the two mica granite are considered to be primary muscovite in terms of the occurrence and mineral chemistry. Each granitic rock reveals systematic variation of major oxide contents with $SiO_2$. Major oxide variation trends of the Baegrog granodiorite are fairly different from those of Cheongsan porphyritic granite and two mica granite. The latter two granitic rocks are also different with each other in variation trends for some oxides. Thus three granitic rocks in the Cheongsan area were solidifield from the independent magmas of chemically different, heterogeneous origin. The granitic rocks in the area show calc-alkaline nature. The whole rock geochemistry shows that the Baegrog granodiorite and Cheongsan porphyritic granite belong to metaluminous, I-type granite, whereas the two mica granite to peraluminous, I/S-type granite. The opaque mineral contents and magnetic susceptibility represent that the granitic rocks in the area are ilmenite-series granite, indicating that each magma was solidified under relatively reducing environment. The tectonic environment of the granitic activity in the area seems to have been active continental margin. Alkali feldspar megacryst in the Cheongsan porphyritic granite is considered to be magmatic, judging from the crystal size, shape, arrangement, and distribution pattern of inclusions. The petro-graphical characteristics of the Cheongsan porphyritic granite can be explained by two stage crystallization. Under the smaller degree of undercooling the alkali feldspar megacrysts rapidly grew owing to slow rate of nucleation and fast growth rate. At the larger degree of undercooling the nucleation rate and density drastically increased and the small crystals of the matrix were formed.

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Product Evaluation Criteria Extraction through Online Review Analysis: Using LDA and k-Nearest Neighbor Approach (온라인 리뷰 분석을 통한 상품 평가 기준 추출: LDA 및 k-최근접 이웃 접근법을 활용하여)

  • Lee, Ji Hyeon;Jung, Sang Hyung;Kim, Jun Ho;Min, Eun Joo;Yeo, Un Yeong;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.26 no.1
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    • pp.97-117
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    • 2020
  • Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.

Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.